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Research Article

Research on corn production efficiency and influencing factors of typical farms: Based on data from 12 corn-producing countries from 2012 to 2019

Roles Conceptualization, Data curation, Investigation, Methodology, Resources, Software, Writing – original draft

Affiliation Institute of Agricultural Economics and Development, Chinese Academy of Agricultural Sciences, Beijing, China

Roles Conceptualization, Funding acquisition, Validation, Visualization, Writing – review & editing

* E-mail: [email protected]

• Jiamei Wang, 
• Xiangdong Hu

• Published: July 9, 2021
• https://doi.org/10.1371/journal.pone.0254423
• Reader Comments

Globally, corn is characterised by high production and high export concentrations, yet the world is experiencing an unprecedented, huge change in this regard. Ensuring the global supply of corn, and thereby the energy and food security of nations has become particularly important. To understand the importance of corn production as an influencing mechanism of global food supplies, the present study researched the corn production of typical farms in major corn-producing and importing countries around the world. I selected the corn input and output data of 18 typical farms in 12 countries from 2012 to 2019, used the data envelopment analysis (DEA) model to calculate the technical efficiency of corn production, and built a tobit model to explore the impact of farming methods, input elements, supporting services, and other factors on efficiency. The study established that the average comprehensive technical efficiency of corn production on a typical farm was 0.863, and the average loss was 13.7%. In addition, it concluded that intensive tillage and conservation tillage have high technical efficiency. It also demonstrated that the proportion of mechanical labour and technical efficiency is in a ‘U’-shaped relationship, among others.

Citation: Wang J, Hu X (2021) Research on corn production efficiency and influencing factors of typical farms: Based on data from 12 corn-producing countries from 2012 to 2019. PLoS ONE 16(7): e0254423. https://doi.org/10.1371/journal.pone.0254423

Editor: Carlos Alberto Zúniga-González, Universidad Nacional Autonoma de Nicaragua Leon, NICARAGUA

Received: March 26, 2021; Accepted: June 25, 2021; Published: July 9, 2021

Copyright: © 2021 Wang, Hu. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: This research is supported by Science and Technology Innovation Engineering Talent Project of Chinese Academy of Agricultural Sciences (ASTIP-IAED-2021-RC-05) and Science and Technology Innovation Project of Chinese Academy of Agricultural Sciences (ASTIP-IAED-2021- 01). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Corn is one of the most widely-planted crops in the world. It is grown in more than 170 regions globally. Corn production is highly concentrated in certain regions like North America, Asia, and South America. According to the United States Department of Agriculture, in 2020, corn production in the United States (US), China, Brazil, and Argentina accounted for 64.63% of global production [ 1 ]. In addition to holding inventory, a portion of the corn produced is consumed domestically, while the rest is exported. Corn exports and production are also highly concentrated. The main corn exporting countries are the US, Brazil, Argentina, and Ukraine. During 2020–2021, the cumulative corn exports of these four countries accounted for 88.12% of global exports [ 1 ]. This indicates that, although China is a major corn producer, it is not a major corn exporter. Global corn production is showing a slight downward trend, and the growth rate of consumption is higher than that of production. Global corn consumption is also highly concentrated. The US and China are the two largest corn consumers. In 2020, China’s corn consumption reached 279 million tons, an increase of 2 million tons from the previous year [ 1 ]. In recent years, the destocking speed of corn in China has accelerated, and nearly 260 million tons of stock have been consumed in 4 years [ 2 ]. With the continuous consumption of temporarily-stored corn, the overall corn supply has tightened, and the gap between supply and demand has gradually increased. According to UN Comtrade, China’s corn imports reached 11.3 million tons in 2020, a yearly increase of 135.73% [ 3 ]. China is a large corn consumer, most of which is from domestic production and a small part of it is from imports, but the import volume is showing an upward trend. Ukraine and the US are the main sources of China’s corn imports. In 2020, China’s corn imports from these two countries accounted for 94.20% of the total imports [ 3 ].

Grain production has achieved bumper harvests for 17 consecutive years, since China attaches great importance to food security, corn production has increased steadily in the past five years. However, there are still major problems in China’s corn production. From the perspective of supply and demand, the rapid development of animal husbandry has caused China’s corn consumption to exceed corn production since 2016, resulting in a large amount of imported corn. According to UN Comtrade, in terms of imports, corn reached 3.52 million tons in 2018, a yearly increase of 24.38%. In 2019, corn imports reached 4.79 million tons, a yearly increase of 36.08%. Simultaneously, since 2008, corn exports have reduced to 270,000 tons, a yearly decrease of 94.5%. Corn exports have been below 300,000 tons in the past 12 years [ 3 ]. Regarding production costs, China’s demographic dividend period has passed, and labour costs have increased significantly; land costs, seeds, fertilisers, and other agricultural materials costs have also increased, increasing the total cost of corn. From a pecuniary point of view, due to China’s policy of supporting the food market for many years, coupled with the increase in corn production costs, the phenomenon of domestic and foreign corn prices is inverted. Effectively ensuring corn production, increasing corn productivity, and ensuring food security have become particularly important. This study examines the production technology efficiency of 12 major corn-producing countries around the world from a macro perspective, analyses the main influencing factors, explores its influence mechanism, and proposes policy recommendations for improving China’s corn production capacity.

Literature review

Agricultural growth mainly depends on the improvement of production efficiency, which is a key indicator of agricultural progress [ 4 ]. Improvements in technical efficiency are necessary to increase food production and release production potential [ 5 ]. To effectively improve technical efficiency, it is required to accurately estimate technical efficiency, analyse important factors affecting corn production efficiency, and propose targeted policy recommendations [ 6 ]. This article reviews the research on the technical efficiency of corn and other important agricultural products. One is to compare and sort out the methods of measuring efficiency in existing research, the other is to provide reference for the methods used in their own research programs, and the third is to compare and verify the existing research results with their own conclusions. Many scholars use certain methods to measure the technical efficiency of corn production, which can be roughly divided into two categories: parametric and non-parametric methods. One is to use the non-parametric data envelopment analysis (DEA) method to measure technical efficiency. Zhang, Meng and Gao [ 7 ] calculated the average technical efficiency of corn production in the Xiliao River Basin to be 0.88, based on the DEA of investment-oriented BCC model. They established that, compared with the traditional technology, the use of the non-film shallow drip irrigation technology improves the technical efficiency. Gao, Liu and Dai [ 8 ] conducted efficiency calculations on nine major corn-producing areas in Xinjiang in 2006. Two output indicators and two input indicators are used. The output indicators are mainly corn yield and output value per unit area. The input indicators use the working price and material cost per hectare in turn. Pei and Zhou [ 9 ] used the DEA method to evaluate corn production efficiency in Heilongjiang Province in 2014. The study established that the overall efficiency of corn production in Heilongjiang was 78.80%. Koc, Gul and Parlakay [ 10 ] measured through the DEA model that the technical efficiency of corn farms in the Eastern Mediterranean region of Turkey is 81%. Mulwa, Emrouznejad and Muhammad [ 11 ] used the DEA model to measure the technical efficiency of corn production in western Kenya and determined that the production efficiency was only 67.70%, which is technically inefficient. However, agricultural training can reduce this inefficiency. The extension agents organize farmer training sessions to inform of farmer field schools to inform farmers about modern farming methods. DEA is used to model efficiencies as an explicit function of seed, fertiliser, family labour, hired labour and hired capital costs. This study constructs a meta-frontier for the two regions.

Another way is to use a parametric method to measure technical efficiency using the stochastic frontier model. Based on the stochastic frontier analysis, at the end of the 20th century and the beginning of the 21st century, the average technical efficiency of corn production in China was above 0.8 [ 12 , 13 ]. Moreover, there are obvious gaps in technical efficiency between regions, and the degree of technology utilisation is different [ 14 ]. The application of scientific research and development in corn production has an advancing effect on corn production, and technological progress is conducive to improving the efficiency of corn production technology [ 15 ]. By 2015, technical efficiency had slightly improved, stabilising above 0.9 [ 16 ]. Abdallah and Awal [ 17 ] reported that the technical efficiency of Ghana’s corn production from 2001 to 2004 was 53%. A Cobb-Douglas production function was used as the functional form of the stochastic frontier production function to define the relationship between outputs and inputs. Chiona, Kalinda and Tembo [ 18 ] conducted a stochastic frontier analysis of the technical efficiency of smallholder corn growers in the central province of Zambia and measured an average technical efficiency of 50%. This study specifies the stochastic frontier production function using the flexible translog specification. A likelihood test was conducted that the translog stochastic frontier production function can be reduced to a Cobb Douglas. Using the stochastic frontier method, Siaw et al. [ 19 ] measured the average technical efficiency of corn production in Ghana to be 74% and established that agricultural credit can increase technical efficiency by 8%. Some scholars use DEA and stochastic frontier method to measure the technical efficiency of corn production at the same time, and find that the efficiency calculated by DEA method is higher than that by stochastic frontier method. Hassan et al. [ 20 ] measured the technical efficiency of corn production in Nigeria from 1971 to 2010. The efficiencies measured by the stochastic frontier method and DEA were 64.1% and 87.7%, respectively. The average level of corn production efficiency in Indonesia calculated by Asmara using the stochastic frontier method was 0.78, and the technical efficiency calculated using the DEA method was 0.91 [ 21 ].

Technical efficiency measurement of other important agricultural products. The above summarizes the measurement of the transnational technical efficiency of corn. Some scholars have also measured the technical efficiency of other agricultural products. Here I mainly review the measurement of the efficiency of soybean, wheat, cotton, and coffee bulk agricultural products. For soybean varieties, some scholars use the super-logarithmic stochastic frontier model to measure the efficiency. Otitoju and Arene [ 22 ] measured the technical efficiency of soybean production in Benue State, Nigeria as 0.73, and Asodina et al. [ 23 ] measured 0.58 in Upper West Region, Ghana. For wheat varieties, Tuna and Oren [ 24 ] used DEA to measure the technical efficiency of wheat production in south-eastern Anatolia, Turkey to be 0.78. Some scholars use the stochastic frontier production function to measure the efficiency of wheat production technology. Jaime and Salazar [ 25 ] measured the efficiency of Chile as 0.6, and Kamruzzaman and Islam [ 26 ] measured the efficiency of Dinajpur District, Bangladesh as 0.7. Ojo [ 27 ] measured the technical efficiency of food crops in Swaziland to be 0.77. Some scholars used DEA to measure the technical efficiency of other agricultural products. Poudel, Yamamoto and Johnson [ 28 ] used DEA to measure the technical efficiency of coffee production in Nepal as 0.83. Gul [ 29 ] measured the cotton technical efficiency in Turkey to be 0.89. The above-mentioned scholars’ technical efficiency measurement and use methods of corn and other agricultural products in different regions are shown in Table 1 . More about the measurement method of efficiency, from the beginning of Farrell to the improvement and innovation of the original method by later scholars, is presented by Zuniga who carried out a detailed and systematic combing [ 30 ].

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https://doi.org/10.1371/journal.pone.0254423.t001

Numerous scholars have researched the factors affecting corn production efficiency from different perspectives. Miho [ 31 ] studied corn planting efficiency in two areas of Tanzania and established that there is a positive relationship between the number of people who can work in the family and technical inefficiency. Production input inhibits the improvement of technical efficiency, and good living conditions can promote efficiency. Olarinde [ 32 ] established that the main determinants of the technical efficiency of maize planting in Nigeria include extension services, farming experience, and farm distance. Boundeth, Nanseki and Takeuchi [ 33 ] established that the technical inefficiency of corn growers in the northern provinces of Laos decreases with an increase in farm size. When studying the factors affecting corn production technology in China, Liu et al. [ 16 ] determined that the power of agricultural machinery has a positive effect on the technical efficiency of corn production and that the basic conditions of agriculture will affect the loss of technical efficiency. They proposed an increase in machinery investment to promote mechanised production. Wang and Wu [ 34 ] established that the use of biochemical inputs such as chemical fertilisers and the use of mechanical agricultural materials improved the technical efficiency of corn production and proposed increasing chemical fertiliser subsidies and promoting large-scale production. Jia and Xia [ 35 ] established that the scale efficiency and the corn planting area indicated an ‘inverted U-shaped relationship’. It can be seen that promoting the scale operation of grain is not the bigger the better. The government should give the guidance and standardization to farmers and make them seek the appropriate degree of scale operation.

Based on the above literature, it can be determined that many scholars use non-parametric analysis methods to measure efficiency in addition to parametric analysis methods. The parametric analysis method has higher requirements for the correct construction of the model and the selection of variables. Scholars have mostly used the envelope analysis method and linear programming to measure efficiency. Concurrently, it can also be established that most scholars focused on the perspective of corn production in a certain country, region, province, or state. They rarely explored the technical efficiency and factors influencing corn production across multiple countries. Therefore, in this study, the corn input and output data of 18 typical farms in 12 countries worldwide from 2012 to 2019 were selected. I used the DEA model to measure technical efficiency and the tobit model, considering the measured technical efficiency as the dependent variable, to explore the impact of the farming system, business scale, and quantity and structure of factor inputs on the efficiency of corn production technology.

Materials and methods

Model settings.

The production unit that needs to be measured in DEA is called a decision-making unit (DMU). There are n units that measure efficiency, denoted as DMU j , each of which has m types of inputs denoted as x i , and q types of outputs denoted as y r . The current DMU to be measured is denoted as DMU K , and the linear combination coefficient of the DMU is represented by λ. With a certain input, technical efficiency is the ratio of the actual output of a production unit to the production frontier. Under the assumption that the return to scale is constant, the production frontier can be represented by the OB ray in Fig 1 , and B is the only effective production unit. In the case of variable returns to scale, the production frontier is a curve formed by MABD that is convex to the left.

https://doi.org/10.1371/journal.pone.0254423.g001

Tobit model.

To further study the influencing factors of technical efficiency, the technical efficiency measured by DEA was used as the dependent variable, and the influencing factors were regressed. As the efficiency value of a typical farm calculated by DEA is truncated data between 0 and 1, estimating it using the ordinary least squares method will cause bias and inconsistency. The tobit model can effectively reduce the deviation [ 38 , 39 ] and is suitable for analysing the factors influencing technical efficiency [ 40 ]. Therefore, this study uses the tobit model, which is expressed as formula ( 2 ), and the maximum likelihood estimation method is used for the regression analysis. The data used in this study are from 2012 to 2019, which are short panel data. Due to the lack of sufficient statistics for individual heterogeneity, the fixed-effects tobit model cannot perform a maximum likelihood estimation, and the regression results are usually biased [ 41 ]. The use of the random effects estimation is effective [ 42 ]; therefore, this study adopts the tobit model of random effects.

Data source

The data used in this study are sourced from agri-benchmark, a global, non-profit network of agricultural economists, advisors, producers and specialists. It is managed by the Thünen Institute and global networks under the German Federal Ministry of Food and Agriculture. According to agri-benchmark, the standard definition of a typical farm is that a region or country has medium-scale and large-scale farms to reflect the average management level of most farms, that is, the average profit level. The areas where the selected typical farms are located are the intensive and main production areas of a particular crop. The cost-benefit data of a typical farm are collected in a comprehensive group with the participation of farmers and consultants, and standard questionnaires are issued to ensure that each figure reflects a typical situation.

This study selects corn input and output data of typical farms in 12 countries, that is, Argentina, Brazil, and Uruguay (South America), Russia, France, Ukraine, Bulgaria, Poland, Czech Republic, and Hungary (Europe), as well as the US (North America) and South Africa (Africa) including 18 typical farms such as AR330ZN, AR700SBA, AR900WBA, BR65PR, BR1300MT, US700IA, US1300ND, etc. from 2012 to 2019. The first two digits of the farm code represent the country, the number represents the size of the farm, and the last few alphabets represent the area where the farm is located. Consider US700IA as an example, which means a 700-hectare farm in Iowa, USA.

Variable selection and descriptive analysis

Based on the scholarly research of Yang and Lu [ 43 ], Zhao, Wang and Zhang [ 44 ], and Xiao and Zhao [ 45 ], this study selected corn yield per unit area as the output indicator, and land, labour, machinery and fuel, construction costs, and other miscellaneous expenses as input indicators. The land input is the corn planting and operating area of the farm, and the labour input is the amount of labour per unit area of corn production. Machinery and fuel inputs are machinery and fuel costs, and construction costs include depreciation, repair, and financial costs. Other miscellaneous expenses include inventory insurance premiums and taxes, consulting fees, and accounting costs. A descriptive analysis of the corn input and output indicators for typical farms is presented in Table 2 .

https://doi.org/10.1371/journal.pone.0254423.t002

Liu et al. [ 46 ] used the comprehensive technical efficiency measured by DEA as the dependent variable and land, machinery, and seed prices as independent variables to study the factors affecting corn production efficiency. They established that land cost, machinery cost, and seed price affect comprehensive technical efficiency. All of these factors have a positive impact. Tian and Zhu [ 39 ] used grain-sown area, labour input (indicated by agriculture, forestry, animal husbandry, and fishery), and fertiliser application as explanatory variables when studying the factors affecting food production efficiency in China. The results showed that chemical fertilisers and machinery promoted the efficiency of food production. The main factors for the improvement, the grain-sown area, and labour input have no significant impact on efficiency.

The technical efficiency measured by the DEA model was selected as the dependent variable, and farming methods, input elements, supporting services, and other factors were used as independent variables to perform the random-effects tobit model regression analysis. The statistical descriptions of the explanatory variables are presented in Table 3 . The farming system is divided into five methods: no-tillage, conservation farming (reducing stubble and covering seeds), conservation farming (covering seeds), intensive farming, traditional farming, and deep farming. I constructed dummy variables for the farming system. The proportion of mechanical labour is the proportion of mechanical labour to total labour, which is used to reflect the degree of mechanisation. To explore the influence of the degree of mechanisation on technical efficiency, the square term of the proportion of mechanical labour was added to the constructed model. The proportion of hired workers indicates the ratio of the number of employees to the total labour force. The total labour force includes family and hired labour. Land cost refers to the cost of renting a unit area of land or the opportunity cost of land. Drying costs refer to the costs incurred when drying corn. Insurance premium is the cost of purchasing agricultural insurance for farms. Consultation fees refer to the expenses incurred by consulting experts in agricultural production. The addition of time-trend variables reduces the impact of time on technical efficiency. Regional dummy variables were set up, and North America was used as the benchmark group to compare regional technical efficiency differences with South America, Europe, and Africa.

https://doi.org/10.1371/journal.pone.0254423.t003

Results and discussion

The use of the DEA model for efficiency measurement needs higher requirements for the selection of input items, and the difference in the selection of input items directly leads to differences in the results of the efficiency calculation. After the input items were determined, multiple collinear tests were performed to ensure that the selected input items were not redundant. Using Stata to test this, the results show that the input variables selected by the DEA model are all less than 10, with an average value of 2.85, indicating that the input variables selected by the DEA model are not redundant. A multicollinearity test was also performed on the explanatory variables selected by the tobit model. The results indicated that the variance expansion factors of the selected explanatory variables were all less than 10, with an average value of 2.02, indicating that there was no multicollinearity in the variable settings of the tobit model [ 47 , 48 ].

Technical efficiency and decomposition of corn production in typical farms

DEAP2.1 software was used to calculate the technical efficiency of 18 typical farms, which is shown in Table 4 . The average level of technical efficiency of corn production was 0.863, and the average loss of efficiency was 13.7%. Table 3 shows that the comprehensive technical efficiency of nine typical farms is 1, indicating that half of the farms in the research group have corn production at the forefront of production, and corn production is DEA-effective. These farms are in Europe and South America, of which three are in Argentina, one is in Brazil, and the others are in the Czech Republic, Poland, Russia, Ukraine, and Uruguay. The comprehensive technical efficiency of US1215INC farms in Bulgaria, Hungary, and the US was approximately 0.5. This is because the pure technical efficiency of corn production is low, which reduces the contribution of scale efficiency. From the perspective of scale efficiency, the average level is 0.939, which is relatively high. However, half of the farms are still in a state of ineffective scale. Farms in Bulgaria, Brazil, Hungary, and South Africa are in a state of increasing returns to scale, and five farms in France and the US are experiencing diminishing returns to scale.

https://doi.org/10.1371/journal.pone.0254423.t004

Based on the two aspects of the main corn-producing countries and the production technology being at the forefront, the corn production conditions in the US, Brazil, and Argentina are analysed.

The pure technical efficiency of corn production in two typical farms in the US is 1, the scale efficiency is above 0.9, and the returns to scale are both in a diminishing stage. As the main agricultural business entity in the US, a large number of family farms have a long history of development. In 2010, the number of family farms in the US reached more than 1.9 million. On average, each family farm has a large area of arable land. The development of family farms requires a higher degree of mechanisation. Therefore, the US attaches great importance to the research and development of agricultural science and technology. The use of agricultural technology reduces labour input and saves transaction costs propagated by hired labour, which is an important reason for maintaining a high level of agricultural production efficiency [ 49 – 51 ]. Furthermore, the US government has always attached great importance to agricultural protection. Due to the surplus of agricultural production, the return to scale of farm corn production is in a diminishing stage. To avoid excessive production by farmers, the government has issued several compensation policies to encourage farmers to participate in fallow programs to adjust supply and protect farmers’ income [ 52 ].

The comprehensive technical efficiency, pure technical efficiency, and scale efficiency of the BR1300MT farms in Brazil and three farms in Argentina are all 1, and the return to scale remains unchanged.

Natural conditions. Brazil, Uruguay, and Argentina are all located in South America. Corn growth has more intensive water requirement. Abundant rainfall and vertical and horizontal river networks provide irrigation conditions, and corn has become the main crop in these areas.

Government support. The Brazilian government has issued several policies to support the soybean planting industry. Brazil convened soybean farmers across the country to form farm consortiums, which purchase materials for soybean planting and production in a unified manner and provide farmers with financing, product transportation, and storage services [ 53 ]. It is beneficial to reducing procurement costs, promoting the consistency of soybean product quality, and achieving large-scale mass production. Soybean varieties grown in Brazil were introduced in the US and transferred to the country for research and breeding. The new varieties cultivated by scientific research institutions based on the country’s soil and climatic conditions are more adaptable to the country’s natural conditions and more suitable for growth in the tropics and subtropics. Consequently, the yield of corn improved [ 54 ]. The Argentine government has always attached great importance to the research, development, and promotion of agricultural science and technology [ 55 ]. It has established several scientific research institutions to promote the development of agricultural science and technology, establish extension stations to provide farmers with agricultural knowledge, train the use of new technologies, promote the implementation and transformation of scientific research results [ 56 ], and establish specialised corn production areas; production specialisation has greatly improved the production efficiency of corn. The export strategy has been formulated to focus on reducing production costs and increasing output per unit area. Consequently, its competitiveness in international trade has improved [ 56 ].

Influencing factors of corn production technology efficiency

The regression results of the tobit model are presented in Table 5 .

https://doi.org/10.1371/journal.pone.0254423.t005

Regional difference.

The North American region represented by the US was considered a benchmark. The regression results indicate that the average technical efficiency level of South America does not show a significant difference from that of North America. At the 1% level, the technical efficiency of Europe and Africa is significantly lower than that of North America to varying degrees. Among them, Africa, represented by South Africa, has the lowest technical efficiency. North America, represented by the US, and South America, represented by Brazil and Argentina, have the highest maize production efficiency. The US, Brazil, and Argentina are the main corn producers and exporters. In addition to having a unique natural resource endowment, government agencies have invested heavily in science and technology and issued several policies to protect the interests of farmers and promote and guarantee the effective production of corn [ 56 ].

Time difference.

At the 1% significance level, the time variable had a positive effect on technical efficiency. This shows that over time, the technical efficiency of agricultural production is constantly increasing, and the level of agricultural technology is constantly improving. The advancement of agricultural production technology relies on economic growth. In the exogenous technological progress growth model, the technological factor is regarded as a function of time.

Tillage system.

The regression coefficients of deep tillage and no-tillage did not pass the significance test, indicating that the technical efficiency of deep tillage and no-tillage did not show obvious differences compared with conservation tillage (reducing stubble and covering seeds). At a significance level of 1%, seed mulching and intensive farming have higher technical efficiency than conservation tillage, and seed-covering farming modes have higher technical efficiency. Covering seeds can replace fallow in summer, protect soil organic carbon, and have beneficial effects on maintaining soil fertility and improving soil quality, thereby effectively disposing biological waste [ 57 ]. Conservation tillage integrated mulch technology can effectively coordinate crop yield, water consumption, and reducing carbon emissions, which can increase the water use efficiency of corn and improve corn production efficiency [ 58 ].

Supporting service.

The input of the drying fee reflects that typical farms dry harvested corn. However, not all production entities dry corn, but the harvested corn has a high moisture content. If stored improperly, the corn will deteriorate and produce mildew, resulting in food waste and economic losses [ 59 ]. In the regression results, the drying fee has a significant promoting effect on the improvement of technical efficiency, indicating that the drying treatment of corn significantly reduced the loss of harvested fruits, promoted agricultural efficiency, and improved corn production efficiency.

The farm insurance premium did not pass the significance test in the regression results, indicating that agricultural insurance did not fully promote the production of planting entities. Due to the risks of agricultural production that are difficult to control, the agricultural insurance market system is unsophisticated [ 60 ], the implementation of insurance is arbitrary, and the protection of agricultural production is not enough; therefore, the interests of farmers have not been effectively protected [ 61 ]. Expert consulting fees have a significant inhibitory effect on corn production efficiency at the 1% level. On the one hand, the methods used to collect farmers’ knowledge are flawed, resulting in inaccurate or incomplete information. The use of inaccurate information or misunderstandings between farmers and scientists result in the development and extension of unprofitable, unsustainable or inappropriate management recommendations [ 62 ]. On the other hand, a small number of experts are far from the reality of agricultural production and fail to propose practical solutions to farmers. Moreover, farmers are restricted by their level, unable to achieve effective docking between farmers and experts, and have not played a role in improving agricultural production efficiency [ 63 ].

Regarding input factors, at a significance level of 1%, land cost has a positive impact on technical efficiency, but the impact is relatively small. This indicates that when the cost of land input factors increases, it will curb the input of land factors, which in turn will increase the utilisation rate of existing land and promote an increase in land productivity. They cope with the increase in the cost of production materials by increasing the output per unit area of land and promoting the improvement of production technology. The regression coefficient of the proportion of hired workers is significantly positive at the 1% level, indicating that it is difficult to improve technical efficiency by relying solely on family labour. The increase in the proportion of hired labour in labour input has a positive effect on the development of agricultural production. Additionally, as agricultural production reaches a certain stage, the demand for labour will inevitably increase. The limited family labour force has led to a large demand for hired labour, which has met the expansion of agricultural production and stimulate technical efficiency.

At a significance level of 5%, the proportion of mechanical labour can promote technical efficiency. Due to the continuous increase in labour costs, the main body of production has increased the use of machinery [ 64 ], shortened the operation time of unit agricultural production, substantially increased labour productivity [ 65 ], and improved corn production efficiency. However, at the 1% significance level, the regression coefficient of the square term of the proportion of mechanical labour is negative, indicating that there is an inverted U-shaped relationship between the proportion of mechanical labour and technical efficiency. When the proportion of mechanical labour exceeds the critical value, continuing to invest in machinery will lead to a decline in technical efficiency, which is due to the use of machinery restricted by topographical characteristics and agricultural production conditions [ 66 ]. Plain areas are easier to mechanise than hilly areas. Small machinery can be used in hilly areas. Excessive machinery investment leads to low agricultural production efficiency and economic losses. The use of machinery also has requirements for the extent of the entire land. It is difficult for these fragmented lands to implement large-scale mechanised production. Agricultural operations still rely mostly on human labour. The proportion of machinery investment is too high, and it is difficult for them to be effective, resulting in technical inefficiency.

Conclusions

The main conclusions of this study are as follows: first, the overall level of technical efficiency of corn production on family farms in Argentina, the US, Ukraine, and other countries is at a relatively high level and is at the forefront of production technology. However, some farms are affected by the low efficiency of pure technology. Technical inefficiency reached 50%, and the average loss of technical efficiency was 13.7%. Second, among the five farming modes, seed-covering, intensive farming, and conservation farming have higher production efficiency than no-tillage and deep tillage. The increase in the cost of production factors of land and labour forces has caused the continuous improvement of technology, thereby increasing the efficiency of corn production. Third, corn drying can promote production efficiency. Farm insurance premiums and expert consultation fees have not played a role in stabilising agricultural production and promoting crop management. The transformation of the economic benefits of agricultural production equipment services is still lacking. Finally, the input and use of machinery are within a certain threshold, which improve labour productivity and promote the development efficiency of corn planting agriculture. However, if the mechanical input exceeds the turning point, it will cause redundancy in the input of elements, resulting in waste and loss of efficiency.

The findings of this study are as follows. First, to achieve the goal of improving corn production efficiency, reducing biological waste, and realizing green and economical production, it is necessary to innovate the production and farming mode of corn, promote the diversification of production methods, and develop a protection farming method that combines with bean crops. Second, improving and refining the construction of agricultural insurance regulations and systems, effectively protecting farmers’ interests, and sharing the risks faced by agricultural production for farmers, are all conducive to improving the efficiency of food production and its sustainability. Third, it is high time to promote the landing and transformation of agricultural scientific research results, strengthen the training and support of scientific research institutions, experts and scholars to production entities, and earnestly take farmers as the main resource for agricultural production ideas. Fourth, it is imperative to consider to promote land circulation and reduce fragmented land to create conditions for mechanised agricultural production and provide basic guarantees for modern agricultural production. Simultaneously, various types of machinery should be developed as well as a technical strategy that combines large-scale and small-scale machinery. For areas where it is difficult to operate large-scale machinery, small-scale agricultural machinery with characteristics of adapting to local conditions should be considered. Finally, strengthen the construction and improvement of the agricultural service system and provide farmers with various forms of information services so that agricultural products can better meet the market demand. At present, there is a large gap between socialised service funds and unreasonable use. Agricultural socialised services must be considered with high importance to effectively serve both farmers and agriculture, ensure agricultural production, and improve economic benefits.

Supporting information

S1 table. corn production input and output indicators in typical farms for 2012–2019..

https://doi.org/10.1371/journal.pone.0254423.s001

S2 Table. Model variable settings and descriptive statistics.

https://doi.org/10.1371/journal.pone.0254423.s002

Acknowledgments

The authors thank agri-benchmark for providing the data. We would like to thank the editor and three reviewers whose comments helped to greatly improve this manuscript.

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• 52. USDA Expands and Renews Conservation Reserve Program in Effort to Boost Enrollment and Address Climate Change. USDA Press. 2021 April 21. Available from: https://www.usda.gov/media/press-releases/2021/04/21/usda-expands-and-renews-conservation-reserve-program-effort-boost
• 54. Government of Brazil. Schedule strategic 2010–2015 corn and sorghum. Available from: https://www.gov.br/agricultura/pt-br/assuntos/camaras-setoriais-tematicas/agendas/arquivos/milho.pdf
• 55. USDA. Agricultural Biotechnology Annual– 2020. [2020 December 11]. Available from: https://apps.fas.usda.gov/newgainapi/api/Report/DownloadReportByFileName?fileName=Agricultural%20Biotechnology%20Annual_Amman_Jordan_10-20-2020

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A comparative study on the effect of different organic fertilizers on the growth and yield of sweet corn

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Growth and Yield of White Corn Varieties at Different Fertilization Techniques for Phosphorus INTRODUCTION Background of the Study

This study will conducted at Barangay Bagong Silang, Tagkawayan, Quezon from august to November 2017. Covering an area of 75 by 25 square meters including the drainage, arranged in rows for easy monitoring and visitation during the gathering of needed data in the conduct of the study. The main objective if the study is to evaluate the growth and yield of selected white corn variety responses at different soil mixture (100% of garden soil, 50% of garden soil + 50% of carbonized rice hull, 50% of garden soil + 50% rice straw, 50% of garden soil + 50% of native pig manure and 50% of garden soil+ organic fertilizer as negative control). Specifically the study will identify which better soil mixture will give the higher growth yield and better quality of selected white corn varieties.

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Maize (Zea mays L) is one of the most versatile and multi utility crops, having wider adaptability in diverse ecologies. Globally, it is known as queen of cereals because of its highest genetic potential. It is the major source of food, feed, fodder and industrial raw material and provides enormous opportunity for crop diversification, value addition and employment generation. Maize is also grown for many other special purposes viz. quality protein maize, sweet corn, baby corn, pop corn, waxy corn, high oil and high amylase corn. It is also a solution for various stresses like weed and lowering water table and abiotic stresses like drought, terminal heat, cold, etc. besides providing opportunity for farm mechanization and conservation agriculture and consequently increasing the resource-use efficiency and farm profitability. Presently, maize production is 21.8 million tons and projected demand of maize to be 45 million tonnes by 2030. This demand of maize will be met either by techn...

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This study was conducted to investigate the yield and yield components of sweet corn genotypes with different endosperm types (su, se and sh2) at Tokat-Kazova, Hatay and Samsun locations in 2009 and 2010 growing seasons. Thirteen F1 sweet corn varieties with different kernel colors and sugar contents and a composite variety were experimented in randomized blocks design with 3 replications. The following yield, yield components, morphological and agronomic traits were studied: tasseling period, silking period, fresh kernel ripening period, plant height, ear length and diameter, number of rows per ear, percent of barren tip, number of kernels per ear, single ear weight, fresh kernel weight per ear, number of ears per plant, number of marketable ears per decare, fresh ear yield per decare, fresh kernel yield per decare and fodder yield. Present findings revealed that Tokat, Hatay and Samsun ecologies were appropriate for production of high yield and quality sweet corn varieties. Among the sweet corn genotypes, early-ripening Bodacious and Fantastic varieties and the varieties of Lumina, Fantastic and Sunshine with well ear characteristics, the varieties of Sunshine and Vega with the greatest number of ears per decare, the varieties of Sunshine, Vega, Fantastic and Silver Queen with the first places in fresh ear yield per decare, fresh kernel yield and fodder yield were identified as prominent varieties. The varieties of Vega, Fantastic, Bodacious and Lumina with desired values of investigated parameters were identified as stable varieties for fresh ear and kernel yield per decare and such a stability indicated that these varieties could successfully be used in different locations. The first principle component included barren tip and explained 47.1% of the total variation, thus it was seen that assessment of barren tips will be sufficient to put forth the differences of genotypes.

Context: Development of early maturing maize cultivars that remain productive under low N fertilizer farming system, consistent with the farmers' technologies is a prerequisite to improving adoption of new varieties without increasing production cost. Objective: To assess the performance of ten early open pollination maize varieties (OPVs) and their F1 hybrids for grain yield and nitrogen use efficiency (NUE), and also identify productive cultivars under low N fertilizer regimes. Materials and Methods: The trials were set up in a split plot arrangement with three N fertilizer levels (0, 45 and 90 kg N ha-1) as main plot and the genotypes as sub-plot. Each plot within N level was four-row, laid out in a randomized complete block design of four replications. Ten OPVs were crossed in a half diallel to generate 45 F1 hybrids during 2004 and 2005 growing seasons. Planting were carried out on 20 th July, 2005 and 2 nd July, 2006. Agronomic characters studied were grain yield, maize establishment count, days to 50% tasselling and silking as well as plant and ear heights. Results: The year 2005 growing season was better for all observed characters amongst all the genotypes than the year 2006. Although, expressions of these traits in the hybrids were relatively higher than the OPVs including the grain yield. The total increase in grain yield observed was 1.72 t ha-1 and 1.95 t ha-1 for OPVs and hybrids respectively on application of 90 kg ha-1 over no N-application. However, NUE was optimum at 45 kg N ha-1 in both groups. Grain yield and NUE correlated positively with growth characters measured except for days to 50% silking. Higher genetic gains were recorded for plant and ear heights. Conclusion: Two drought tolerant varieties (Acr 90 Pool 16-Dt and Tze Comp3 Dt) that combined well with specific cultivars for grain yield and NUE probably have gene pools for low N-tolerance.

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How To Write A Research Proposal

A Straightforward How-To Guide (With Examples)

By: Derek Jansen (MBA) | Reviewed By: Dr. Eunice Rautenbach | August 2019 (Updated April 2023)

Writing up a strong research proposal for a dissertation or thesis is much like a marriage proposal. It’s a task that calls on you to win somebody over and persuade them that what you’re planning is a great idea. An idea they’re happy to say ‘yes’ to. This means that your dissertation proposal needs to be   persuasive ,   attractive   and well-planned. In this post, I’ll show you how to write a winning dissertation proposal, from scratch.

Before you start:

– Understand exactly what a research proposal is – Ask yourself these 4 questions

The 5 essential ingredients:

• The title/topic
• The introduction chapter
• The scope/delimitations
• Preliminary literature review
• Design/ methodology
• Practical considerations and risks 

What Is A Research Proposal?

The research proposal is literally that: a written document that communicates what you propose to research, in a concise format. It’s where you put all that stuff that’s spinning around in your head down on to paper, in a logical, convincing fashion.

Convincing   is the keyword here, as your research proposal needs to convince the assessor that your research is   clearly articulated   (i.e., a clear research question) ,   worth doing   (i.e., is unique and valuable enough to justify the effort), and   doable   within the restrictions you’ll face (time limits, budget, skill limits, etc.). If your proposal does not address these three criteria, your research won’t be approved, no matter how “exciting” the research idea might be.

PS – if you’re completely new to proposal writing, we’ve got a detailed walkthrough video covering two successful research proposals here . 

How do I know I’m ready?

Before starting the writing process, you need to   ask yourself 4 important questions .  If you can’t answer them succinctly and confidently, you’re not ready – you need to go back and think more deeply about your dissertation topic .

You should be able to answer the following 4 questions before starting your dissertation or thesis research proposal:

• WHAT is my main research question? (the topic)
• WHO cares and why is this important? (the justification)
• WHAT data would I need to answer this question, and how will I analyse it? (the research design)
• HOW will I manage the completion of this research, within the given timelines? (project and risk management)

If you can’t answer these questions clearly and concisely,   you’re not yet ready   to write your research proposal – revisit our   post on choosing a topic .

If you can, that’s great – it’s time to start writing up your dissertation proposal. Next, I’ll discuss what needs to go into your research proposal, and how to structure it all into an intuitive, convincing document with a linear narrative.

The 5 Essential Ingredients

Research proposals can vary in style between institutions and disciplines, but here I’ll share with you a   handy 5-section structure   you can use. These 5 sections directly address the core questions we spoke about earlier, ensuring that you present a convincing proposal. If your institution already provides a proposal template, there will likely be substantial overlap with this, so you’ll still get value from reading on.

For each section discussed below, make sure you use headers and sub-headers (ideally, numbered headers) to help the reader navigate through your document, and to support them when they need to revisit a previous section. Don’t just present an endless wall of text, paragraph after paragraph after paragraph…

Top Tip:   Use MS Word Styles to format headings. This will allow you to be clear about whether a sub-heading is level 2, 3, or 4. Additionally, you can view your document in ‘outline view’ which will show you only your headings. This makes it much easier to check your structure, shift things around and make decisions about where a section needs to sit. You can also generate a 100% accurate table of contents using Word’s automatic functionality.

Ingredient #1 – Topic/Title Header

Your research proposal’s title should be your main research question in its simplest form, possibly with a sub-heading providing basic details on the specifics of the study. For example:

“Compliance with equality legislation in the charity sector: a study of the ‘reasonable adjustments’ made in three London care homes”

As you can see, this title provides a clear indication of what the research is about, in broad terms. It paints a high-level picture for the first-time reader, which gives them a taste of what to expect.   Always aim for a clear, concise title . Don’t feel the need to capture every detail of your research in your title – your proposal will fill in the gaps.

Need a helping hand?

Ingredient #2 – Introduction

In this section of your research proposal, you’ll expand on what you’ve communicated in the title, by providing a few paragraphs which offer more detail about your research topic. Importantly, the focus here is the   topic   – what will you research and why is that worth researching? This is not the place to discuss methodology, practicalities, etc. – you’ll do that later.

You should cover the following:

• An overview of the   broad area   you’ll be researching – introduce the reader to key concepts and language
• An explanation of the   specific (narrower) area   you’ll be focusing, and why you’ll be focusing there
• Your research   aims   and   objectives
• Your   research question (s) and sub-questions (if applicable)

Importantly, you should aim to use short sentences and plain language – don’t babble on with extensive jargon, acronyms and complex language. Assume that the reader is an intelligent layman – not a subject area specialist (even if they are). Remember that the   best writing is writing that can be easily understood   and digested. Keep it simple.

Note that some universities may want some extra bits and pieces in your introduction section. For example, personal development objectives, a structural outline, etc. Check your brief to see if there are any other details they expect in your proposal, and make sure you find a place for these.

Ingredient #3 – Scope

Next, you’ll need to specify what the scope of your research will be – this is also known as the delimitations . In other words, you need to make it clear what you will be covering and, more importantly, what you won’t be covering in your research. Simply put, this is about ring fencing your research topic so that you have a laser-sharp focus.

All too often, students feel the need to go broad and try to address as many issues as possible, in the interest of producing comprehensive research. Whilst this is admirable, it’s a mistake. By tightly refining your scope, you’ll enable yourself to   go deep   with your research, which is what you need to earn good marks. If your scope is too broad, you’re likely going to land up with superficial research (which won’t earn marks), so don’t be afraid to narrow things down.

Ingredient #4 – Literature Review

In this section of your research proposal, you need to provide a (relatively) brief discussion of the existing literature. Naturally, this will not be as comprehensive as the literature review in your actual dissertation, but it will lay the foundation for that. In fact, if you put in the effort at this stage, you’ll make your life a lot easier when it’s time to write your actual literature review chapter.

There are a few things you need to achieve in this section:

• Demonstrate that you’ve done your reading and are   familiar with the current state of the research   in your topic area.
• Show that   there’s a clear gap   for your specific research – i.e., show that your topic is sufficiently unique and will add value to the existing research.
• Show how the existing research has shaped your thinking regarding   research design . For example, you might use scales or questionnaires from previous studies.

When you write up your literature review, keep these three objectives front of mind, especially number two (revealing the gap in the literature), so that your literature review has a   clear purpose and direction . Everything you write should be contributing towards one (or more) of these objectives in some way. If it doesn’t, you need to ask yourself whether it’s truly needed.

Top Tip:  Don’t fall into the trap of just describing the main pieces of literature, for example, “A says this, B says that, C also says that…” and so on. Merely describing the literature provides no value. Instead, you need to   synthesise   it, and use it to address the three objectives above.

Ingredient #5 – Research Methodology

Now that you’ve clearly explained both your intended research topic (in the introduction) and the existing research it will draw on (in the literature review section), it’s time to get practical and explain exactly how you’ll be carrying out your own research. In other words, your research methodology.

In this section, you’ll need to   answer two critical questions :

• How   will you design your research? I.e., what research methodology will you adopt, what will your sample be, how will you collect data, etc.
• Why   have you chosen this design? I.e., why does this approach suit your specific research aims, objectives and questions?

In other words, this is not just about explaining WHAT you’ll be doing, it’s also about explaining WHY. In fact, the   justification is the most important part , because that justification is how you demonstrate a good understanding of research design (which is what assessors want to see).

Some essential design choices you need to cover in your research proposal include:

• Your intended research philosophy (e.g., positivism, interpretivism or pragmatism )
• What methodological approach you’ll be taking (e.g., qualitative , quantitative or mixed )
• The details of your sample (e.g., sample size, who they are, who they represent, etc.)
• What data you plan to collect (i.e. data about what, in what form?)
• How you plan to collect it (e.g., surveys , interviews , focus groups, etc.)
• How you plan to analyse it (e.g., regression analysis, thematic analysis , etc.)
• Ethical adherence (i.e., does this research satisfy all ethical requirements of your institution, or does it need further approval?)

This list is not exhaustive – these are just some core attributes of research design. Check with your institution what level of detail they expect. The “ research onion ” by Saunders et al (2009) provides a good summary of the various design choices you ultimately need to make – you can   read more about that here .

Don’t forget the practicalities…

In addition to the technical aspects, you will need to address the   practical   side of the project. In other words, you need to explain   what resources you’ll need   (e.g., time, money, access to equipment or software, etc.) and how you intend to secure these resources. You need to show that your project is feasible, so any “make or break” type resources need to already be secured. The success or failure of your project cannot depend on some resource which you’re not yet sure you have access to.

Another part of the practicalities discussion is   project and risk management . In other words, you need to show that you have a clear project plan to tackle your research with. Some key questions to address:

• What are the timelines for each phase of your project?
• Are the time allocations reasonable?
• What happens if something takes longer than anticipated (risk management)?
• What happens if you don’t get the response rate you expect?

A good way to demonstrate that you’ve thought this through is to include a Gantt chart and a risk register (in the appendix if word count is a problem). With these two tools, you can show that you’ve got a clear, feasible plan, and you’ve thought about and accounted for the potential risks.

Tip – Be honest about the potential difficulties – but show that you are anticipating solutions and workarounds. This is much more impressive to an assessor than an unrealistically optimistic proposal which does not anticipate any challenges whatsoever.

Final Touches: Read And Simplify

The final step is to edit and proofread your proposal – very carefully. It sounds obvious, but all too often poor editing and proofreading ruin a good proposal. Nothing is more off-putting for an assessor than a poorly edited, typo-strewn document. It sends the message that you either do not pay attention to detail, or just don’t care. Neither of these are good messages. Put the effort into editing and proofreading your proposal (or pay someone to do it for you) – it will pay dividends.

When you’re editing, watch out for ‘academese’. Many students can speak simply, passionately and clearly about their dissertation topic – but become incomprehensible the moment they turn the laptop on. You are not required to write in any kind of special, formal, complex language when you write academic work. Sure, there may be technical terms, jargon specific to your discipline, shorthand terms and so on. But, apart from those,   keep your written language very close to natural spoken language   – just as you would speak in the classroom. Imagine that you are explaining your project plans to your classmates or a family member. Remember, write for the intelligent layman, not the subject matter experts. Plain-language, concise writing is what wins hearts and minds – and marks!

Let’s Recap: Research Proposal 101

And there you have it – how to write your dissertation or thesis research proposal, from the title page to the final proof. Here’s a quick recap of the key takeaways:

• The purpose of the research proposal is to   convince   – therefore, you need to make a clear, concise argument of why your research is both worth doing and doable.
• Make sure you can ask the critical what, who, and how questions of your research   before   you put pen to paper.
• Title – provides the first taste of your research, in broad terms
• Introduction – explains what you’ll be researching in more detail
• Scope – explains the boundaries of your research
• Literature review – explains how your research fits into the existing research and why it’s unique and valuable
• Research methodology – explains and justifies how you will carry out your own research

Hopefully, this post has helped you better understand how to write up a winning research proposal. If you enjoyed it, be sure to check out the rest of the Grad Coach Blog . If your university doesn’t provide any template for your proposal, you might want to try out our free research proposal template .

Psst… there’s more!

This post is an extract from our bestselling Udemy Course, Research Proposal Bootcamp . If you want to work smart, you don't want to miss this .

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29 Comments

Thank you so much for the valuable insight that you have given, especially on the research proposal. That is what I have managed to cover. I still need to go back to the other parts as I got disturbed while still listening to Derek’s audio on you-tube. I am inspired. I will definitely continue with Grad-coach guidance on You-tube.

Thanks for the kind words :). All the best with your proposal.

First of all, thanks a lot for making such a wonderful presentation. The video was really useful and gave me a very clear insight of how a research proposal has to be written. I shall try implementing these ideas in my RP.

Once again, I thank you for this content.

I found reading your outline on writing research proposal very beneficial. I wish there was a way of submitting my draft proposal to you guys for critiquing before I submit to the institution.

Hi Bonginkosi

Thank you for the kind words. Yes, we do provide a review service. The best starting point is to have a chat with one of our coaches here: https://gradcoach.com/book/new/ .

Hello team GRADCOACH, may God bless you so much. I was totally green in research. Am so happy for your free superb tutorials and resources. Once again thank you so much Derek and his team.

You’re welcome, Erick. Good luck with your research proposal 🙂

thank you for the information. its precise and on point.

Really a remarkable piece of writing and great source of guidance for the researchers. GOD BLESS YOU for your guidance. Regards

Thanks so much for your guidance. It is easy and comprehensive the way you explain the steps for a winning research proposal.

Thank you guys so much for the rich post. I enjoyed and learn from every word in it. My problem now is how to get into your platform wherein I can always seek help on things related to my research work ? Secondly, I wish to find out if there is a way I can send my tentative proposal to you guys for examination before I take to my supervisor Once again thanks very much for the insights

Thanks for your kind words, Desire.

If you are based in a country where Grad Coach’s paid services are available, you can book a consultation by clicking the “Book” button in the top right.

Best of luck with your studies.

May God bless you team for the wonderful work you are doing,

If I have a topic, Can I submit it to you so that you can draft a proposal for me?? As I am expecting to go for masters degree in the near future.

Thanks for your comment. We definitely cannot draft a proposal for you, as that would constitute academic misconduct. The proposal needs to be your own work. We can coach you through the process, but it needs to be your own work and your own writing.

Best of luck with your research!

I found a lot of many essential concepts from your material. it is real a road map to write a research proposal. so thanks a lot. If there is any update material on your hand on MBA please forward to me.

GradCoach is a professional website that presents support and helps for MBA student like me through the useful online information on the page and with my 1-on-1 online coaching with the amazing and professional PhD Kerryen.

Thank you Kerryen so much for the support and help 🙂

I really recommend dealing with such a reliable services provider like Gradcoah and a coach like Kerryen.

Hi, Am happy for your service and effort to help students and researchers, Please, i have been given an assignment on research for strategic development, the task one is to formulate a research proposal to support the strategic development of a business area, my issue here is how to go about it, especially the topic or title and introduction. Please, i would like to know if you could help me and how much is the charge.

This content is practical, valuable, and just great!

Thank you very much!

Hi Derek, Thank you for the valuable presentation. It is very helpful especially for beginners like me. I am just starting my PhD.

This is quite instructive and research proposal made simple. Can I have a research proposal template?

Great! Thanks for rescuing me, because I had no former knowledge in this topic. But with this piece of information, I am now secured. Thank you once more.

I enjoyed listening to your video on how to write a proposal. I think I will be able to write a winning proposal with your advice. I wish you were to be my supervisor.

Dear Derek Jansen,

Thank you for your great content. I couldn’t learn these topics in MBA, but now I learned from GradCoach. Really appreciate your efforts….

From Afghanistan!

I have got very essential inputs for startup of my dissertation proposal. Well organized properly communicated with video presentation. Thank you for the presentation.

Wow, this is absolutely amazing guys. Thank you so much for the fruitful presentation, you’ve made my research much easier.

this helps me a lot. thank you all so much for impacting in us. may god richly bless you all

How I wish I’d learn about Grad Coach earlier. I’ve been stumbling around writing and rewriting! Now I have concise clear directions on how to put this thing together. Thank you!

Fantastic!! Thank You for this very concise yet comprehensive guidance.

Even if I am poor in English I would like to thank you very much.

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• Dissertation

How to Write a Dissertation or Thesis Proposal

Published on September 21, 2022 by Tegan George . Revised on July 18, 2023.

When starting your thesis or dissertation process, one of the first requirements is a research proposal or a prospectus. It describes what or who you want to examine, delving into why, when, where, and how you will do so, stemming from your research question and a relevant topic .

The proposal or prospectus stage is crucial for the development of your research. It helps you choose a type of research to pursue, as well as whether to pursue qualitative or quantitative methods and what your research design will look like.

You can download our templates in the format of your choice below.

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Table of contents

What should your proposal contain, dissertation question examples, what should your proposal look like, dissertation prospectus examples, other interesting articles, frequently asked questions about proposals.

Prior to jumping into the research for your thesis or dissertation, you first need to develop your research proposal and have it approved by your supervisor. It should outline all of the decisions you have taken about your project, from your dissertation topic to your hypotheses and research objectives .

Depending on your department’s requirements, there may be a defense component involved, where you present your research plan in prospectus format to your committee for their approval.

Your proposal should answer the following questions:

• Why is your research necessary?
• What is already known about your topic?
• Where and when will your research be conducted?
• Who should be studied?
• How can the research best be done?

Ultimately, your proposal should persuade your supervisor or committee that your proposed project is worth pursuing.

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Strong research kicks off with a solid research question , and dissertations are no exception to this.

Dissertation research questions should be:

• Focused on a single problem or issue
• Researchable using primary and/or secondary sources
• Feasible to answer within the timeframe and practical constraints
• Specific enough to answer thoroughly
• Complex enough to develop the answer over the space of a paper or thesis
• Relevant to your field of study and/or society more broadly
• What are the main factors enticing people under 30 in suburban areas to engage in the gig economy?
• Which techniques prove most effective for 1st-grade teachers at local elementary schools in engaging students with special needs?
• Which communication streams are the most effective for getting those aged 18-30 to the polls on Election Day?

An easy rule of thumb is that your proposal will usually resemble a (much) shorter version of your thesis or dissertation. While of course it won’t include the results section , discussion section , or conclusion , it serves as a “mini” version or roadmap for what you eventually seek to write.

Be sure to include:

• A succinct introduction to your topic and problem statement
• A brief literature review situating your topic within existing research
• A basic outline of the research methods you think will best answer your research question
• The perceived implications for future research
• A reference list in the citation style of your choice

The length of your proposal varies quite a bit depending on your discipline and type of work you’re conducting. While a thesis proposal is often only 3-7 pages long, a prospectus for your dissertation is usually much longer, with more detailed analysis. Dissertation proposals can be up to 25-30 pages in length.

Writing a proposal or prospectus can be a challenge, but we’ve compiled some examples for you to get your started.

• Example #1: “Geographic Representations of the Planet Mars, 1867-1907” by Maria Lane
• Example #2: “Individuals and the State in Late Bronze Age Greece: Messenian Perspectives on Mycenaean Society” by Dimitri Nakassis
• Example #3: “Manhood Up in the Air: A Study of Male Flight Attendants, Queerness, and Corporate Capitalism during the Cold War Era” by Phil Tiemeyer

If you want to know more about AI for academic writing, AI tools, or research bias, make sure to check out some of our other articles with explanations and examples or go directly to our tools!

Research bias

• Survivorship bias
• Self-serving bias
• Availability heuristic
• Halo effect
• Hindsight bias
• Deep learning
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• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
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Generally, an outline contains information on the different sections included in your thesis or dissertation , such as:

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Development and Utilization of Corn Processing by-Products: A Review

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As an important food crop, corn has an important impact on people’s lives. The processing of corn produces many by-products, such as corn gluten meal, corn husk, and corn steep liquor, which are rich in protein, oil, carbohydrates, and other nutrients, all of which are inexpensive. Their accumulation in large quantities during the production process not only results in a burden on the environment but also the loss of potentially valuable food materials that can be processed. In fact, the by-products of corn processing have been partially used in functional foods, nutrients, feed, and other industries. There is no doubt that the secondary utilization of these by-products can not only solve the problem of waste pollution caused by them, but also produce high value-added products and improve the economic benefits of corn. This paper describes in detail the processing and higher-value utilization of the five main by-products: corn gluten meal, corn husks, corn steep liquor, corn germ, and fuel ethanol by-product. The utilization status of corn processing by-products was discussed roundly, and the development trend of corn processing by-products in China and other countries was analyzed, which provided the reference for the development of the corn deep processing industry.

1. Introduction

In a world with an ever-growing population, it has become crucial to use raw materials in a green, environmentally friendly, and repeatable way. The increasing demand for quantity and quality of food will inevitably lead to the production of more waste and by-products during processing. Nowadays, health and development are the common ideals and goals of human beings. People’s lives are gradually changing to healthy and sustainable development. Reducing food waste and improving food utilization has become a mainstream phenomenon in society [ 1 ]. The European Union (EU) has planned a circular bioeconomy, an action plan that includes an approach based on reducing, reusing, recovering, and recycling materials and energy [ 2 ]. The agricultural and food processing sectors generate a large amount of waste each year [ 3 ], so it is necessary to process these agricultural wastes effectively to reduce the negative impact on the environment. Moreover, these agricultural wastes can be used as a cheap source of protein, carbohydrates, and dietary fiber. In particular, the processing by-products of grains or beans are also rich in many nutrients, they can effectively provide some nutritional products for human consumption, and have promising applications in the food industry. However, agricultural by-products are generally considered low-value assets in the post-harvest phase, with about 14% of food loss and waste occurring worldwide [ 4 ].

Corn ( Zea mays L.), which is native to the Americas and now widely distributed in the United States, China, Brazil, and other countries, is an important food crop in the world [ 5 ]. It is mainly composed of starch, protein, and fat, which are rich in trace nutrients such as vitamin A, vitamin E, and the trace element selenium. From 2016 to 2020, global corn production and consumption were both above 1000 million tons ( Figure 1 ). Corn is made up of the seed coat, cotyledon, and germ, with different chemical compositions. During processing, corn is broken down into main starch products and by-products. In China, corn by-products are mostly used as low economic value animal feed, which is very wasteful. For example, corn gluten meal contains 60% protein and is a valuable source of protein [ 6 ]. Corn husks are rich in oils and dietary fibre [ 7 ], corn pulp is rich in mineral elements [ 8 ], and each corn by-product has the potential to be used as a functional food component with antioxidant, anti-aging, and anti-obesity properties and can be obtained through secondary processing.

Map of global corn production.

At present, there are more than 1000 kinds of corn by-products processing products, which are widely used in food and chemical industries, fermentation, and other fields. Since the reform of China’s national corn purchasing and storage system in 2016, China’s corn by-product processing industry has developed rapidly. In 2018, China’s production of starch, lysine, monosodium glutamate, and maltitol accounted for 52%, 60%, 68%, and 85% of the world’s total production, respectively, with the export volume of monosodium glutamate, lysine, and citric acid ranking first in the world [ 9 ].

According to the different processing degrees of corn raw materials, corn processing can be divided into primary processing and deep processing of by-products. The initial processing of corn involved simple processing such as cleaning, soaking, crushing, separating, and dehydrating. The deep processing of corn by-products is the process of using the first processed corn product as the raw material, and then using external technology to perform secondary processing on it and transform it into the final product. From a single primary corn product to the production of more and more corn derivatives and its by-products, the processing varieties of corn have been continuously enriched, the diversification of the processing of corn by-products has been realized, and the industrial chain has been further extended.

In order to provide a reference for promoting the sustainable development of corn processing industry, this paper summarizes the research and utilization of corn processing by-product in recent years, and the new industrial uses and nutritional products of these corn by-products are introduced, which not only help to improve the economic benefits of corn, reduce the economic burden of farmers [ 10 ], but also reduce pollution and contribute to environmental protection. In addition, this paper also aims to discuss the recent advances in further processing and reuse of corn-industry by-products [ 11 ].

2. Corn Gluten Meal

According to research reports, about 180 kg of corn gluten meal (CGM) can be produced for every ton of corn starch syrup processed. The protein content of CGM is as high as about 60%, mainly consisting of zein, globullins, and glutellins [ 12 , 13 ], all of which are very high-quality plant protein sources. CGM contains a high percentage of hydrophobic amino acids, and the rest of the composition is mainly water, fiber, and fat [ 14 , 15 ]. At present, the deep processing products of CGM are described in the following paragraph.

2.1. Corn Peptide

CGM is rich in Glu, Leu, Pro, Ala, Phe, and Asp, and its nutritional value is very rich. However, it has low water solubility and is deficient in essential amino acids such as Lys, His, and Trp, considerably, which limits its nutritional value and its direct application as a food ingredient [ 16 ]. In order to further expand the application of CGM in the field of food and health care, it can be modified by enzymatic hydrolysis to prepare small molecule oligopeptides, which have better physiological activity and functional properties [ 17 ]. In recent years, research has shown that small-molecule oligopeptides have a beneficial effect on human digestion, absorption, and metabolism [ 18 ]. Corn peptides (CPs) are usually small molecular peptide fragments produced by the enzymatic hydrolysis of corn gluten powder under the action of proteases [ 19 ]. CPs are usually composed of 2–20 amino acids, and the relative molecular weight is between 300–1000 Da. CPs have the characteristics of easy digestion and absorption, and have shown good application prospects in the fields of food and medicine [ 20 ]. In 2010, China’s Ministry of Health approved it as a new resource for food [ 21 ].

There are many methods for preparing CPs, including enzymatic hydrolysis, microbial fermentation, and chemical synthesis [ 22 ]. At present, the more commonly used is enzymatic hydrolysis, which includes single and compound enzymatic hydrolysis. The optimization of enzymatic hydrolysis process for corn gluten meal has been relatively mature. The single enzymatic method mainly refers to the use of alkaline protease, neutral protease, or pepsin by optimal conditions for different catalytic reactions of different enzymes. Compound enzyme refers to the interaction and matching ratio between different enzymes, which optimizes the best ratio method, which is more convenient and efficient than single enzyme digestion, and the yield is also higher.

CPs have antioxidant activity, are anti-hypertension, and prevent alcohol injury, and have other unparalleled physiological functions [ 23 ]. Ma et al. found that CPs can effectively reduce the amount of ethanol in the blood after alcoholic intake by plasma alanine and leucine [ 24 ]. CPs have been found to have the potential ability to promote alcohol metabolism by activating the liver alcohol dehydrogenase (ADH), which leads to a decrease in blood alcohol concentration [ 25 ]. In addition, Wu et al. have reported the protective effect of CPs at a dose of 4 g/day may protect the alcoholic liver injury by regulating lipid metabolism and human oxidative stress responses [ 26 ].

In the field of food processing, CPs can improve antioxidant capacity of the foods without any decay in other quality parameters. CPs are rich in hydrophobic amino acids, which can promote the secretion of glucagon and can also be used to make sports drinks and other high-protein beverage products [ 27 ]. In addition, adding CPs to fresh milk fermented by probiotics and lactic acid bacteria can significantly improve the viscosity, flavor, taste, and health functions of the fresh milk. CPs have extensive application in the field of health food, and because CPs contain a high proportion of alanine and leucine, the concentration of alanine and leucine in the blood increases, which can enhance the alcohol dehydrogenase and acetaldehyde in the liver. The activity of dehydrogenase promotes the decomposition and metabolism of ethanol in the body to achieve the function of sobering alcohol. For this reason, CPs have been widely developed as foods and beverages with functions such as being anti-alcohol and offering liver protection [ 28 , 29 ]. Secondly, the content of leucine and alanine in CPs are high level and play a key role in the anti-fatigue effect, therefore, CPs have been added in sports food to improve muscle resistance to fatigue, there are functional foods that combine CPs with other biologically active substances in the market, and functional foods made of compound substances have the functions of being anti-fatigue, lowering blood pressure, and promoting anti-aging [ 30 ]. The main component, technology method, function, and major findings of corn gluten meal are summarized in Table 1 .

The main component, technology method, function, and major findings of corn gluten meal.

2.2. Zeaxanthin

Zeaxanthin is an important carotenoid derivative, which was first found in corn. Zeaxanthin (3,3′-dihydroxy-β-carotene) is a polyene molecule containing nine alternating conjugated double and single carbon bonds, with both ends of the carbon skeleton connected to a hydroxyl ionone ring. The 3′ chiral carbon atoms in both rings allow for three possible stereoisomers of zeaxanthin, including (3S, 3′S)-zeaxanthin, meso-zeaxanthin and (3R, 3′R)-zeaxanthin. The molecular formula of zeaxanthin is C 40 H 56 O 2 and the molecular weight is 568.88 Da [ 31 ]. Zeaxanthin and lutein are a pair of isomers, and the only difference is that the position of the double bond in the ionone ring is different. Zeaxanthin and lutein are widely found in human eyeballs [ 32 ], the pancreas, liver, and other tissues and organs that play an important role in human health [ 33 , 34 ]. Zeaxanthin and lutein are concentrated in the macular area of the central retina of the human eye. The human body cannot synthesize zeaxanthin and lutein, which must be consumed through diet [ 35 ]. In CGM, the content of zeaxanthin is about 0.20–0.37 mg/g [ 36 ].

Zeaxanthin in the CGM currently follows two extraction methods: (1) The organic solvent method, which can be used to extract zeaxanthin from CGM in organic solvents by utilizing the property of zeaxanthin dissolved in organic solvents. In consideration of the safety of organic solvents, ethanol is mostly selected as the extraction solvent of zeaxanthin. (2) Ultrasonic microwave extraction method. Through ultrasonic oscillation, air-conditioning effect, mechanical effect, thermal effect, etc., the internal structure and state of CGM are changed to increase the penetration of organic solvents into the cell wall, thereby enhancing the extraction efficiency [ 37 ].

Zeaxanthin has strong antioxidant and blue light absorbing properties, and is often added as a natural food additive to margarine, butter, beverages, meat, and egg products for the prevention and treatment of eye diseases such as age-related macular degeneration (AMD) and cataracts [ 38 , 39 , 40 ]. Zeaxanthin is the main macular pigment in the retina of the human body. It absorbs high-energy blue light energy through its own antioxidant activity, thereby preventing the occurrence of human retinal damage [ 41 , 42 , 43 ]. Zeaxanthin also has a certain anti-cataract effect, and cataracts is the main cause of vision loss in the elderly, as the lens in the eye become turbid. Studies have found that zeaxanthin can prevent cataracts by inhibiting oxidative damage [ 44 ]. In addition, because two six-membered carbon rings of zeaxanthin contain one oxygen-containing group, the chemical structure of zeaxanthin has greater stability, with strong coloring ability, and it is widely used in food additives and feed additives [ 45 , 46 ]. In addition, the molecular structure of zeaxanthin shows that there are 11 conjugated double bonds, which enable it to block the chain transmission of free radicals, thus having strong antioxidant activity, and it is often developed as a functional product.

3. Corn Husks

Corn husks are the most abundant and least valuable by-product of corn industrial processing, accounting for 10% to 14% of the total fiber content of corn [ 47 ]. Corn husks contain 382 g cellulose, 445 g hemicellulose, 66 g lignin, 19 g protein, and 28 g ash per kg of dry matter [ 48 ]. Because it is rich in arabinoxylan (70%), it is used to produce xylo-oligosaccharides and dietary fiber. In addition, corn husks are rich in phenolic acids, 90% of which are ferulic acid, which is mainly distributed in the cell walls of aleurone and pericarp layers. Ferulic acid in corn husks exists in free, soluble, and insoluble forms. With a ratio of 1:10:1000, ferulic acid has a strong antioxidant capacity, which can regulate the oxidation state of cells and prevent biological macromolecules such as DNA and proteins from oxidative damage. Compared with the husks of grains such as rice, wheat, and sorghum, the content of phytic acid in corn husks that affects human mineral metabolism is relatively small [ 49 ]. Untreated corn husk has no significant beneficial effect on the human health, and excessive consumption of corn husk often leads to human gastrointestinal discomfort because of its insoluble dietary fiber. Therefore, the deep processing of husks can increase the nutritive and economic value of corn. The main processed products of corn husk by-products are as follows.

3.1. Carbohydrate

The main component, technology method, function, and major findings of corn husks are discussed in Section 3.1 , Section 3.2 and Section 3.3 and summarized in Table 2 .

3.1.1. Dietary Fiber

In the middle of the 20th century, the term “dietary fiber” was first used by Hipsley to refer to plant components that resist being decomposed by endoenzymes secreted by mammalian cells [ 50 ].

There are about 60% to 70% corn dietary fiber in corn husks, which can be widely used in functional food and medical fields. Dietary fiber has irreplaceable physiological functions in the human body, such as increasing satiety, slowing the rise of blood sugar, and maintaining the integrity of the intestinal mucosa. In addition, dietary fiber can improve human intestinal flora and provide energy and nutrition for the growth and reproduction of human probiotics [ 51 ]. Studies have shown that dietary fiber can help reduce the concentration of postprandial blood glucose, insulin, and triglyceride, reduce the concentration of cholesterol in human blood, and plays an important role in people’s health. The recommended daily dietary fiber intake is 28 g/day for adult women and 36 g/day for adult men [ 52 ].

As a kind of plant tissue, dietary fiber has a strong water absorption capacity, and corn dietary fiber has a water absorption capacity of 1.5 g water/g powder, so it can accelerate the transportation speed of human digestive tract feces, can increase the volume of feces, effectively clean the intestines, and reduce the pressure of the rectum and urinary system [ 53 ]. In addition, the number of dietary fibers can improve intestinal flora and increase the number of probiotic bacteria such as Lactobacillus and Bifidobacterium to prevent a series of gastrointestinal diseases, such as constipation and hemorrhoids, etc. [ 54 ]. At present, the treatment of diabetes and hypertension still lacks specific drugs, and treatment requires a reasonable diet. Dietary fiber can effectively reduce blood sugar, blood pressure, and blood lipids [ 55 , 56 , 57 ]. Dietary fiber has strong binding and exchange ability with cations, which can exchange with sodium ions and potassium ions in the intestinal tract, and promote the excretion of Na+ and K+ ions with urine and feces, thus reducing the ratio of Na+ and K+ ions in the blood, which directly play the role of lowering blood pressure [ 58 ]. Dietary fiber absorbs glucose, reduces the absorption of glucose by the human body, effectively reduces the content of glucose in the blood, and has the effect of treating diabetes [ 59 ].

Dietary fiber has good physical and chemical properties such as water retention, oil retention, emulsification and gel properties, and more functional properties for human health. In recent years, studies have shown that adding soluble dietary fiber to bread can effectively inhibit short-term degradation of bread and improve the stability of bread [ 60 ]. Adding dietary fiber into beverages can improve the stability and dispersion of the beverage. Adding dietary fiber to meat products can maintain the moisture of meat products, increase the viscosity and gel capacity of meat products, and inhibit the growth of microorganisms [ 61 ]. Corn dietary fiber, which consists of cellulose and hemicellulose, is one of the most important sources of dietary fiber in grains and was once discarded or used as animal feed. In addition, corn dietary fiber can also absorb nitrites, significantly reducing the risk of cancer [ 62 ]. Treatment of corn bran dietary fiber with xylanase increased its ability to bind bile salts in vitro [ 63 ]. Corn dietary fiber contains many potentially valuable components such as cellulosic fiber gel, corn fiber gel, corn fiber gum, xylo-oligosaccharides, corn fiber oil, and ferulic acid [ 64 ].

The main component, technology method, function, and major findings of corn husks.

3.1.2. Polysaccharides

Polysaccharides are polymeric carbohydrate macromolecules composed of long chains of monosaccharide units joined by glycosidic linkages. There are two types of polysaccharides: homo-polysaccharides and hetero-polysaccharides; homo-polysaccharides have only one monosaccharide repeated in the chain, and hetero-polysaccharides are composed of two or more monosaccharides [ 65 ]. With the development of molecular biology, the scientific community has gradually realized that polysaccharides with proteins are extremely important biomacromolecules and play an important role in the growth and development of organisms.

Polysaccharides in corn husks are usually extracted by water extraction combined with ethanol precipitation. Because polysaccharide molecules contain a large number of polar groups with good water solubility, the higher the temperature, the better the solubility of the polysaccharides. This method has mild reaction conditions and a simple operation, but the extraction cycle is too long and the extraction efficiency is low. Therefore, acid, alkali, or organic solvent extraction is usually used, as well as enzyme-assisted extraction, ultrasonic-assisted extraction, microwave extraction, etc. [ 66 , 67 ]. Polysaccharides are one of the main functional components of corn husks, which have significant functional activities such as immune regulation, anti-oxidation, anti-tumor, and blood pressure lowering functions [ 68 ]. For example, polysaccharides can improve immunity by affecting the morphology, phagocytosis, cytokine secretion, and other aspects of macrophages or by increasing the volume of macrophages. It can also enhance the secretion of immunoglobulin and cytokines by promoting the proliferation of lymphocytes [ 69 ]. Polysaccharides can reduce the chain length of lipid peroxidation and prevent or slow down the process of lipid peroxidation. Direct removal of reactive oxygen species can be achieved by capturing various reactive oxygen species in a chain reaction of lipid peroxidation. In addition, polysaccharides can also act as free radical scavengers by pairing with their single electrons so that their absorption gradually disappears, thus exerting their antioxidant power [ 70 , 71 , 72 ]. Corn polysaccharides also have a significant effect on lowering blood sugar, and corn colysaccharides are composed of xylose and arabinose, which is connected by β-1,4 glycosidic bonds. Xylose and arabinose can be obtained by hydrolysis of dilute sulfuric acid. Among them, L-arabinose is a five-carbon aldose, which can be used as a low-calorie sweetener without decomposition. Generating heat can inhibit the enzymes that hydrolyze disaccharides, block the metabolism of sucrose, and then have a significant inhibitory effect on the increase in blood sugar [ 73 ]. Black glutinous corn polysaccharides (BGCP) were isolated and the hypoglycemic activity of alloxan-induced diabetic mice was evaluated. In the study byZhang et al., mice were given 800, 500 or 200 mg/kg BGCP daily for 4 weeks. The results showed that blood glucose levels were reduced in all three groups with the addition of BGCP, with the 800 mg/kg treatment leading to greater hypoglycemic effects than low-dose treatments [ 74 ].

3.2. Protein

As corn gluten meal, the protein in corn husks is mainly zein. Zein is a safe, non-toxic, renewable, natural, low-cost, biocompatible, and degradable protein, and it is composed of four components (α, β, γ, and δ) with different peptide chains, molecular sizes, and solubility. The most abundant protein in commercial zein is alpha-zein. Zein is soluble in 60–95% ethanol, acetone, and alkaline aqueous solutions with pH ≥ 11.5. In practical application, zein contains hydrophobic and hydrophilic groups, which had good amphiphilicity [ 75 , 76 , 77 ].

Zein has a unique amino acid composition, which contains a high proportion of hydrophobic amino acids and more sulfur-containing amino acids, but lacks charged acidic, basic, and polar amino acids, which makes it uniquely soluble [ 78 , 79 ].

At present, in view of the difficulty of recycling plastic packaging and the difficulty of degradation, environmental pollution is becoming more and more serious. With the improvement of environmental awareness, people’s demand for biodegradable packaging materials is increasing. The film-forming performance of biological polymer materials has attracted people’s attention. The unique amino acid composition of zein makes it have good film-forming properties. The film-forming forces of zein are mainly hydrophobic bonds, hydrogen bonds, and limited disulfide bonds between proteins. The zein protein is quickly extracted from the ethanol solution, and the zein protein particles will bind together to form a fibrous structure. After the subsequent steps of coating, evaporation, dehydration, and other steps, a moisture-resistant, oxygen-resistant, oil-resistant, and degradable zein film can be formed [ 80 , 81 ].

Zein has been used widely in the field of the food industry, and is mainly used in food embedded agents, food emulsifiers, free gluten-free foods, food packaging materials, and reasonable development. For example, zein has excellent viscoelasticity as a substitute for gluten protein [ 82 ]. Zein can also encapsulate fat-soluble functional active substances, pigments, or flavor components. By encapsulating and protecting the centrally active substances, it can effectively improve the stability and partial functional properties of the active ingredients, and ensure the nutritional value of the centrally active substances. At the same time, the adhesion of zein can prolong the residence time of the drug on the surface of the intestinal mucosa, realize the enteric release of the central substance, and promote the absorption and utilization of the central substance. When fatty acids are added to zein solutions, they can be used as binders for food materials or wood, metal, and other materials. Zein contains a high content of branched chain amino acids and neutral amino acids, which can be used to prepare functional peptides with low molecular weight and high activity, such as high F-value oligopeptides and antioxidant peptides, which can be used in biological medicine and functional health products. Reasonable development and utilization of zein will bring huge economic benefits to the food industry [ 83 ].

3.3. Corn Husk Oil

There is about 5–12% oil in corn husks, and these oils contain more than 80% unsaturated fatty acids, which play an important role in the development of human brain function and the metabolism of human blood lipids, which can improve human immunity and prevent the risk of prostate and other diseases [ 84 , 85 ]. In addition, phytosterol is a kind of natural plant active substance with a similar structure to cyclic alcohol, which can be divided into the free type and the esterified type. Phytosterols widely exist in various vegetable oils, seeds, and nuts. They are distributed in the roots, stems, leaves, fruits, and seeds of plants. They are the main components of cell membranes and precursors of vitamin D and various hormones. Since the human body cannot synthesize sterols by itself, food is the only source of sterols. Corn husk oil is also rich in phytosterols, which play a critical role in maintaining cholesterol balance, anti-oxidation, and anti-aging in the human body. Numerous epidemiological studies have proven that phytosterols contribute to the incidence of chronic diseases inversely.

Corn husk oil is difficult to extract because of the tight structure of the husk. Some scholars have used ultrafine pulverization and dilute acid hydrolysis to improve the yield of corn husk oil, but the effect is not effective. The traditional preparation methods of corn husk oil mainly include the pressing method and organic solvent extraction method. For the subcritical extraction solvent, according to the physical properties of similar phase dissolution of organic matter, counter current extraction of materials is carried out through the molecular diffusion process between materials and the extraction solvent in the contact process, and then the extraction solvent is separated from the extracted target component through the process of decompression evaporation. This method is non-toxic, harmless, and pollution-free, and does not destroy the advantages of biological activity of the product, and can be effectively used to extract corn oil from corn husk, but can also reduce the production cost in the whole process of corn development, improving the comprehensive economic benefits of the corn processing industry [ 86 ].

4. Corn Steep Liquor

The first step of corn deep processing is to foam the corn, which will produce a large amount of soaking water. In order to break the -S-S- bond in the protein, the protein network in the corn kernel is broken in order to release the wrapped starch. The corn kernels should be soaked in an aqueous solution of sodium bisulfite first, and the viscous liquid obtained by concentrating the soaking solution is corn steep liquor (CSL) [ 87 ]. China is a big producer of corn starch. Most cornstarch on the domestic market is produced by a wet process, and a large amount of CSL will be produced during the production process. CSL contains a lot of protein, soluble sugar, and sulphide compounds; at present, corn steep liquor has not been used effectively, but is directly discarded, which not only increases the production cost of corn starch, and causes a lot of waste of resources, but also has a great impact on the development of the corn industry and causes environmental pollution and destroys the ecological environment. Therefore, the development of comprehensive utilization of CSL is of great significance to the recovery and secondary development of corn steep liquor, which is of great significance for increasing the added value of corn industry products and reducing environmental pollution.

CSL is the main by-product of corn starch production by the wet process. It is a viscous, acidic slurry with an aromatic smell and yellowish-brown color. It is considered a rich and cheap source of carbon, nitrogen, amino acids and minerals, and has a broad application prospect in the development of the biological process. Some studies have shown that using CSL as a nitrogen source to produce microbial metabolites (such as citric acid, amylopectin, enzyme, and bioenergy) has a very good effect [ 88 ]. The crude protein content of CSL is approximately 20% and the solids content is approximately 50%. Therefore, it can be used as an excellent animal feed ingredient; in addition, CSL is rich in sucrose, nutrients, and elements such as Ca, Mg, Al, Fe, Mn, Mo, P, and S, which provide a good source of organic nitrogen and carbon for microbial growth [ 89 ]. Selim, MT et al. studied the Lactic acid concentration of about 44.6 g/L with a high yield (0.89 g/g) obtained using 60 g/L of CSL sugar, inoculum size 10% ( v / v ), 45 degrees C, and sodium hydroxide or calcium carbonate as a neutralizing agent [ 90 ]. Biosurfactants extracted from CSL can be used in dairy production. These results demonstrate that adding this biosurfactant to drinkable yogurt can promote the growth of Lactobacillus casei, which is considered to be a probiotic bacterium [ 91 ]. Phytic acid, also known as inositol hexaphosphate, can bind with calcium ions to form calcium phytate, which has a very good therapeutic effect on gastritis, diarrhea, and rickets. The extraction of plant calcium from CSL has a simple operation, a short cycle, and is low cost. At present, the technology for extracting calcium phytate from corn steep liquor is relatively mature [ 92 , 93 ].

5. Corn Germ

Corn kernels are composed of the seed coat, endosperm, and embryo. Corn germ is a part of the corn embryo, which is located below the corn kernel and is mainly involved in the growth and development of corn (Different Strategies to Obtain Corn ( Zea mays L.) Germ Extracts with Enhanced Antioxidant Properties, Design of corn germ extractor based on S7-1200 PLC). Corn germ is the beginning of the growth and development of corn, and its weight only accounts for about 13% of corn, but it is very rich in nutritional value and rich in a variety of nutrients (Corn germ with pericarp in relation to whole corn: nutrient contents, food and protein efficiency, and protein digestibility-corrected amino acid score), concentrating more than 80% of fat and inorganic salt, 60% of sugar and 20% of the protein in the whole corn, and also contains phospholipids, sterols, and other nutritional ingredients [ 94 ]. Cornstarch is industrially separated from corn kernels through a process called dry or wet milling, leaving corn germ as the main residue [ 95 ]. Corn germ has been studied as a feed for ruminants due to its desirable nutritional properties [ 96 ]. The inclusion of whole corn germ in ruminant diets aims to increase energy density and polyunsaturated fatty acids, to obtain higher levels of conjugated linoleic acid (CLA) in the meat, which are beneficial to human health [ 97 ]. The addition of 120 g/kg dry matter corn germ into the diet of lambs did not affect the carcass characteristics, physicochemical composition, and sensory properties of the meat. When corn germ dosage was 76.7 g/kg dry matter, the distribution of polyunsaturated fatty acids in lamb meat was the best [ 98 ]. Corn germ can be used at low levels in the diet of broilers without compromising their productive rates [ 99 ]. Moreover, the main processed products of corn germ by-products are as follows.

5.1. Corn Germ Oil

Corn germ oil is a nutritious and healthy edible oil. It has a transparent golden yellow color and a fragrant fragrance. It is called “liquid gold” by Western countries. Corn germ oil contains 80–85% of unsaturated fatty acids, oleic acid, linoleic acid, and α-linolenic acid. The content of linoleic acid is as high as 56%. Linoleic acid is an essential fatty acid that the human body cannot synthesize by itself, and an important component of human cells. Corn germ oil is also rich in natural vitamin E, which can effectively prevent atherosclerosis and reduce the risk of coronary heart disease. In addition, corn germ oil is rich in phytosterols and phospholipids. Phytosterol is called “the key to life”, and the phytosterol content in corn germ oil is more than all food, up to 633 mg/100 g [ 100 , 101 , 102 ]. In recent years, more and more people are consuming corn oil, and the physical and chemical characteristics of corn germ oil are listed in Table 3 .

Physical and chemical properties of corn germ oil [ 103 ].

At present, there are many extraction methods for corn germ oil, and the traditional extraction method of corn germ oil is the pressing method. The pressing method is to squeeze the oil out through mechanical pressure, which is a method commonly used in oil factories. The process of this method is relatively simple, the supporting equipment is scarce, and the quality of the prepared corn germ oil is good, but its disadvantages are lower oil production efficiency and more serious waste. The “pre-leaching” method is the mainstream process of current edible oil production enterprises. The pre-pressing leaching method is a method in which the corn germ is first pressed, and then the oil is extracted with an organic solvent. Pre-pressing only squeezes about 70% of the fat in the embryo, and the pressing temperature and pressure are lower than those of the full pressing method. Therefore, the crude oil is light in color and high in quality. After pre-pressing, the corn germ press cake is extracted [ 104 ]. This method combines the advantages of the two technologies, but there are still many shortcomings. For example, protein denaturation also exists in the pre-pressing process, which affects the quality of oil. Supercritical CO 2 extraction technology is an emerging extraction technology, which has been widely used in the field of corn germ oil extraction. This method is used to extract corn germ oil efficiently by adjusting the influencing factors in the extraction process by using CO 2 in the supercritical state. The extraction efficiency of corn germ oil by this method is obviously improved and the quality of corn germ oil is better. The corn germ oil extracted by different methods had some differences in oil yield and the quality of corn germ oil products.

5.2. Corn Germ Protein

The protein in corn germ is of a high quality and has high nutritional value. Compared with corn, the content of crude protein, lysine, and methionine of corn germ meal is 2–3, 3.2, and 1.4 times that of corn, respectively and the content of vitamins and minerals is also much higher, so it has a great value of development and utilization [ 105 ]. Corn germ protein contains all the essential amino acids needed by the human body and has a high biological value (BV, 64–72%), second only to eggs (94%) and milk (85%). The protein efficacy ratio (PER) of corn germ protein was 2.04 to 2.56, comparable to soy protein (2.32, PER) and casein (2.5, PER) [ 106 ]. Among common grains, corn germ protein is one of the best plant protein nutrient sources, and its amino acid composition is in good agreement with the human protein standards recommended by the FAO/WHO. In addition to the rich nutritional value of corn germ protein, it has been reported that the antioxidant activity of its hydrolysate has been studied. The results show that the corn germ protein hydrolysate has strong antioxidant capacity, and has an inhibitory effect on the oxidation of linoleic acid. It has an inhibitory effect on the peroxide value of oils and fats, and has a good development prospect [ 107 ].

The proteins in corn germ are mainly albumin and globulin, which have good functional properties. Corn germ protein has good solubility, and its nitrogen solubility index (NSI) is very high under alkaline conditions. Corn germ protein also has better water absorption, much higher than soybean protein. The oil holding capacity of corn germ protein was also better, which was similar to that of soybean concentrate [ 108 ]. In addition, corn germ protein also has good emulsification, foaming, and gel properties, and is an excellent functional food raw material or food additive [ 109 ]. At present, people mainly focus on the extraction of corn germ oil, and corn germ protein is also a very high-quality protein. The industrialized production of corn germ protein can significantly improve the tissue structure and taste of the target product, increase the yield of the product, and prolong the shelf life.

The extraction method of corn germ protein is mainly the alkaline extraction method, which is a very common method for extracting vegetable protein. The protein is extracted mainly by utilizing the properties of corn germ protein, which is an amphoteric compound, with better solubility under alkaline conditions and less solubility near the protein’s isoelectric point. In the solution of soaking corn germ, an alkaline solution is slowly added, and when the pH of the solution reaches about 9.5, the protein is precipitated, and the corn germ protein can be obtained by centrifugation after standing for a period of time. This method is a very classical extraction method with a simple operation, high extraction rate, and a low cost, but the color of corn germ protein obtained by this method is poor, and the extraction process will affect the physical, chemical properties, and nutritional properties of corn germ protein.

The enzyme-alcohol method is also a common extraction method for corn germ protein, and cellulase and amylase were used to hydrolyze the corn germ to release the protein and fat, and then ethanol was used to extract the protein from the corn germ. The corn germ protein extracted by the method has a good taste, mild reaction conditions, and good specificity, and at the same time, it also avoids environmental pollution when the protein is extracted by the alkali-soluble acid precipitation method, but the cost is relatively high. The reverse micelle technology uses a non-polar organic solvent to dissolve the surfactant. When the concentration is excessive, micelles are formed in the organic solvent. The hydrophilic macromolecules dissolved in the water hole will be extracted in the form of micelles, so that the oil and protein can be separated. The extraction conditions of reverse micelle technology are mild, the solvent can be reused, and large-scale operation can be realized, which has broad industrial development and application prospects. The extraction of corn germ protein by reverse micellar technology can retain the maximum activity of corn germ protein components, and the oil absorption, emulsification, and emulsification stability are relatively excellent [ 110 ].

Corn germ protein has good functional properties and nutritional value, and it has been widely used in the food industry [ 111 ]. In baked foods, corn germ protein can be used as a good food nutritional additive, and adding corn germ protein can make up for the deficiency of lysine and threonine in wheat protein. With the improvement of people’s living standards, more attention is being paid to the balanced nutrition of the diet. As a high-quality vegetable protein, corn germ protein can be used as a substitute for milk to meet the needs of lactose intolerant people, and because corn germ protein has a better emulsifying ability, no emulsifier needs to be added to the formula. Corn germ protein drink is milky white in color, delicate in taste, and has a special corn flavor. Corn germ protein has good water absorption, oil absorption, and gel properties, and adding it into meat products can increase the water retention and oil retention properties of meat products, reduce fat separation, increase yield, and effectively improve the nutritional value of meat products [ 112 , 113 ]. Corn germ protein can effectively replace traditional protein additives such as casein, whey protein concentrate, and soy protein. Therefore, further in-depth exploration of corn germ protein research in the fields of food, health and medicine will be a future research trend. The main component, technology method, function, and major findings of corn germ are summarized in Table 4 .

The main component, technology method, function, and major findings of corn germ.

6. Fuel Ethanol by-Product

Corn distiller grains (DDGS) are produced by a mixed fermentation of corn seeds, selected yeast, and enzymes in a fuel ethanol plant. DDGS is mainly composed of dried distillate (DDG) and soluble concentrate (DDS), which is rich in protein, amino acids, vitamins, and other nutrients. Each 100 kg of corn can produce 34.1 kg of ethanol and 31.6 kg of DDGS. The yield is large but the price is low. Due to the high acidity and high viscosity of corn distillers grains, the COD (Chemical Oxygen Demand) value can reach 30,000–50,000 mg/L, and the BOD (Biochemical Oxygen Demand) value can reach 20,000–30,000 mg/L, and if the waste is directly discharged, it will not only cause serious pollution to the environment but also be a great waste of resources, so it should be fully utilized [ 114 ]. Figure 2 is a typical process flow chart of ethanol production by the corn whole grain method.

Process flow diagram of ethanol and DDGS production.

There is also much research on the application of corn DDGS in livestock and poultry. For example, two groups of Silurus glanis were fed for two consecutive weeks with DDGS in one group and no DDGS in the other. The results showed that the apparent digestibility of corn DDGS is beneficial to Silurus Glanis, and 30% DDGS can be added into the Silurus Glanis’ diet without affecting the growth performance and nutrient utilization of Silurus Glanis [ 115 ]. Determination of the effect of different levels of corn DDGS feed on broiler amino acid digestibility showed that higher levels of DDGS could reduce broiler amino acid digestibility [ 116 ]. Some scholars have used a combination of alkaline and enzymatic methods to extract cellulose from corn kernels and DDGS. The minimum crude cellulose yield of corn kernels and DDGS is 1.7% and 7.2%, respectively, and the cellulose content is 72% and 81%, respectively. When extracting solids with 35–81% cellulose content, the obtained cellulose can hold up to nine times its weight, so it can be used as an absorbent. Cellulose is also used as paper, composites, lubricants, and nutritional supplements [ 117 ].

7. The Challenges of Corn Processing by-Products

In recent years, with the continuous development of corn processing projects, corn processing is undergoing technical changes. In order to guarantee the success of the corn processing industry and promote the healthy and stable development of enterprises, it is necessary to strengthen the comprehensive utilization of corn by-products. At present, there are also many technical and process challenges. For instance, modern biotechnology (efficient enzymatic hydrolysis and fermentation technology) and separation and purification technology need to be developed to increase the added value of corn processing products and reduce environment pollution. How do we apply these advanced technologies, reduce costs to develop high-priced products, and reduce the discharge of environmental pollutants such as corn pulp and by-product of fermentation so as to maintain ecological balance is the main challenge we will meet.

8. Conclusions

As the demand and nutritional quality of corn products increase, the amount of by-products produced during corn processing also increases. In order to maximize the utilization value of corn, reduce waste of resources, and fully realize the sustainable development of the corn industry, it is necessary to seek reasonable processing and utilization of corn by-products. The high value processing of corn by-products has broad market prospects and huge business opportunities, and it is of great practical significance to strengthen the development of corn by-products processing.

Acknowledgments

We gratefully acknowledge all of the people who have contributed to this paper.

Funding Statement

This work was supported by the Major Science and Technology Program of the Hundreds and Thousands Project in Heilongjiang Province (2021ZX12B09-2), Heilongjiang Provincial Foundation for the Characteristic Discipline of Processing Technology of Plant Foods (YSTSXK202204), and the Fundamental Research Funds at Heilongjiang Provincial Universities (145109213).

Author Contributions

Conceptualization, Y.J.; methodology: H.H.; investigation: Y.C.; formal analysis: Y.J., Y.C. and H.H.; data curation: H.H., Y.C. and H.-D.C.; supervision: Y.J., Y.C. and H.-D.C.; writing—original draft: H.H.; writing—review and editing: Y.J., Y.C., H.-D.C. and H.H. All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

Conflicts of interest.

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Theses and dissertations 2006-present.

Sherwood, Patrick W. 2014 PhD Plant Pathology. Advisor: P. Bonello

Acharya, Bhupendra 2014 MS Plant Pathology. Advisor: A.E. Dorrance

Balk, Christine 2014 MS Plant Pathology. Advisor: A.E. Dorrance

Marty, DeeMarie 2014 MS Plant Pathology. Advisor: C.G. Taylor

Nauth, Brittany 2014 MS Plant Pathology. Advisor: C.G. Taylor

Salgado Moncada, Jorge David 2014 PhD Plant Pathology. Modeling the effects of fusarium head blight on wheat grain yield and quality and developing cost-effective strategies for minimizing losses. Advisors: P.A. Paul and L.V. Madden.

Andersen, Kelsey 2013 MS Plant Pathology. Influence of rainfall patterns on the development of Fusarium head blight, accumulation of deoxynivalenol and fungicide efficacy. Advisor: P.A. Paul

Chin, Ashlina 2013 MS Plant Pathology. Evaluation of the retention of human-pathogenic Caliciviruses on leafy greens weakened by phytopathogens. Advisor: F. Qu

D'Angelo, Daisy 2013 MS Plant Pathology. Effects of fungicide chemistry and application timing on Fusarium head blight and deoxynivalenol in soft red winter wheat. Advisor: P.A. Paul

Chewachong, Godwill 2013 PhD Plant Pathology. Engineering plant virus "vaccines" using Pepino Mosaid Virus as a model. Advisor: F. Qu

Shirsekar, Gautam 2013 PhD Plant Pathology. Ubiquitination in innate immunity of rice ( Oryza sativa ). Advisor: G-L Wang

Chen, Chenxi 2013 PhD Plant Pathology. Analysis of the molecular basis of virulence in pathogenic fungi.  Advisor: T. K. Mitchell

Rong, Xiaoqing 2013 PhD Plant Pathology. Genomic analysis, population quantification and diversity characterization of Cryptococcus flavescens . Advisor: B. Mcspadden Gardener.

Hu, Jinnan 2013 PhD Plant Pathology. Advisor: T. K. Mitchell

Cisneros Delgadillo (Carter), Fiorella 2013 PhD Plant Pathology.  Maize fine streak virus (MFSV) gene expression and protein interaction. Advisors: M. Redinbaugh and F. Qu.

Songkumarn, Pattavipha 2013 PhD Plant Pathology. Identification and characterization of in-planta expressed secreted effector proteins from Magnaporthe oryzae . Advisor: G-L Wang.

Gunadi, Andika 2012 MS Plant Pathology. Characterization of Rps8 and Rps3 resistance genes to phytophthora sojae through genetic fine mapping and physical mapping of soybean chromosome 13. Advisor: A. Dorrance

Cao, Chunxue 2012 MS Plant Pathology. Characterization of management and environment effects on cultivated tomatoes. Advisor: B. McSpadden Gardener

Cepeda, Maria Veronica 2012 MS Plant Pathology.  Effects of microbial inoculants on biocontrol and plant growth promotion . Advisor: B. McSpadden Gardener

Singh, Jasleen 2012 MS Plant Pathology.  Characterization of self-interaction of Arabidopsis thaliana double stranded RNA binding protein 4.  Advisor: F. Qu.

Francis, Bridget 2012 MS Plant Pathology.  Non-thesis MS.  Advisor: T. Mitchell.

Pack, Racheal A. 2012 MS Plant Pathology.  Non-thesis MS.  Advisor: T. Graham

Wallhead, Matthew 2012 MS Plant Pathology Foliar fungicide effects on gray leaf spot and yield of hybrid corn as influenced by application timing, hybrid characteristics and production practices. Advisor: P.A. Paul

Anco, Daniel J. 2011 PhD Plant Pathology Epidemiological Studies of the Sporulation Potential and Environmental Factors Affecting Sporulation of Phomopsis viticola on Infected Grapevines. Advisors: M. Ellis and L. Madden

Ellis, Margaret L. 2011 PhD Plant Pathology Soybean seedling disease complex: Pythium spp . and Fusarium graminearum and their management and host resistance.  Advisors: A. Dorrance and P. Paul

Ivey, Melanie L. L. 2011 PhD Plant Pathology Assessing microbial risks and management strategies in vegetables. Advisor: S.A.  Miller

Kriss, Alissa B. 2011 PhD Plant Pathology The Role of Environmental, Temporal, and Spatial Scale on the Heterogeneity of Fusarium Head Blight of Wheat.  Advisors: L. Madden and P. Paul

Park, Chan Ho 2011 PhD Plant Pathology The role of ubiquitination in the interaction between rice and Magnaporthe oryzae .  Advisor: G-L Wang

Wang, Hehe 2011 PhD Plant Pathology Identification and dissection of soybean QTL conferring resistance to Phytophthora sojae. Advisor: A. Dorrance

Cheng, Jiye 2011 PhD Plant Pathology Development of metabolomics strategies for novel natural product discovery and its application on the study of soybean defense responses.  Advisor: T. Graham.

Whitehill, Justin 2011 PhD Plant Pathology Investigations into mechanisms of ash resistance to the Emerald Ash Borer.  Advisor: P. Bonello

Burbano Figueroa, Oscar 2011 MS Plant Pathology.  Functional Characterization of Magnaporthe oryzae Effectors in the Infective Process of Rice. Advisor: T. Mitchell

Gearhart, Kate 2011 MS Plant Pathology Soybean diseases associated with reduced yields in southern Ohio.  Non-thesis MS.  Advisor: Anne Dorrance

Xu, Xiulan 2010 PhD Plant Pathology Transmission of Clavibacter michiganensis subsp. michiganensis from seed to seedling and development strategies to control the pathogen in seed.  Advisor: S. A. Miller

Elateek, Sawsan Youssef 2010 PhD Plant Pathology Molecular and biochemical genetic studies on some leafhopper-transmitted plant pathogens.  Advisor: S. A. Miller

Woltjen, Christine D. 2010 MS Plant Pathology Responding to industry needs from the field to the greenhouse: Dieback and cankers of Gleditsia triacanthos var. inermis and characterization of an Ohio isolate of Melon necrotic spot virus and its vector, Olpidium bornovanus , collected from Cucumis sativus .  Advisor: D. Lewandowski

De La Torre Cuba, Carola 2010  MS Plant Pathology Molecular characterization, differential movement and construciton of infectious cDNA colones of an Ohio isolate of Hosta virus X.  Advisor: D. Lewandowski

Fown, Aaron 2010 MS Plant Pathology Non-thesis master's degree.  Advisor: D. Coplin.

Li, Cunyu 2010 MS Plant Pathology The effects of fungicides and cultivar resistance on associations among Fusarium head blight, deoxyvalenol, and fungal colonization of wheat grain.  Advisor: P. Paul

Zhang, Zhifen 2010 MS Plant Pathology Mapping multiple novel race-specific resistance genes for Phytophthora sojae in soybean PI 408211B.  Advisor: Anne Dorrance

Nagle, Annemarie M. 2009 MS Plant Pathology Ecological and chemical aspects of white oak decline and sudden oak death, two sundromes associated with Phytophthora spp .  Advisor: P. Bonello.

Odenbach, Kylea J. 2009 MS Plant Pathology Epidemiology and variability of disease and deoxynivalenol in Fusarium head blight of wheat in Ohio.  Advisor: P. Paul

Ortega, Maria Andrea 2009 MS Plant Pathology Identification of molecular markers associated with the Rps8 locus in soybean and evaluation of microsporogenesis in Rps8/rps8 heterozygous lines.  Advisor: Anne Dorrance

Weber, Barry 2009 MS Plant Pathology Non-thesis master's degree.  Advisor: L. Rhodes

Koenig, John L. 2009 MS Plant Pathology Timing of fungicide applications for the management of dollar spot.  Advisor: M. Boehm.

Subedi, Nagendra 2009 MS Plant Pathology Use of biorational products for the control of diseases in high tunnel tomatoes and induction of certain defense genes in tomato by Trichoderma hamatum 382.  Advisor: S. Miller.

Kleczewski, Nathan M . 2009 PhD Plant Pathology Nutrient and drought effects on biomass allocation, phytochemistry, and ectomycorrhizae of birch.  Advisor: P. Bonello.

Broders, Kirk D . 2008 PhD Plant Pathology Seed and seedling disease of corn and soybean in Ohio: the role of Fusarium graminearum , Pythium species diversity, fungicide sensitivity, Pythium community composition, and soil properties in disease severity.  Advisor: Anne Dorrance

Cruz, Christian 2008 MS Plant Pathology Impact of foliar diseases on soybean in Ohio: Frogeye leaf spot and Septoria brown spot .  Advisor: Anne Dorrance

Benitez, Maria Soledad 2008 PhD Plant Pathology Applied T-RFLP analyses for the identification and characterization of microbial populations associated with damping-off incidence in a transient organic cropping system.  Advisor: B. McSpadden Gardener

Raudales, Rosa 2008 MS Plant Pathology Studies in biocontrol: enumeration, characterization and screening of Rhizobia .  Advisor: B. McSpadden Gardener

Vega Sanchez, Miguel E . 2008 PhD  Plant Pathology The E3 ligase SPL11 regulates both programmed cell death and flowering time in rice. Advisor: G. Wang

Palumbo, Rose 2008  PhD Plant Pathology Target Region Amplification Polymorphism (TRAP) analysis of Pelargonium.  Advisor: G. Wang.

Wallis, Christopher 2007  PhD  Plant Pathology Understanding the roles of phenolics and terpenoids in pine defense against fungal pathogens.  Advisor: P. Bonello.

Song, Jing 2007  PhD  Plant Pathology. Functional characterization of extracellular protease inhibitors of Phytophthora spp. and their targets tomato proteases.  Advisor: S. Kamoun.

Bos, Jorunn Indra Berit 2007   PhD   Plant Pathology Function, structure and evolution of the RXLR effector Avr3a of Phytophthora infestans .  Advisor: S. Kamoun.

Briar, Shabeg Singh 2007  PhD  Plant Pathology Nematodes as bioindicators of soil food web health in agroecosystems: a critical analysis.  Advisors: P. Grewal and S. Miller.

Niver, Amy Lee 2007  MS  Plant Pathology Effects of fungicides on dollar spot, caused by Sclerotinia homoeocarpa .  Advisor: M. Boehm.

Alviter, Angel Rebollar 2006  PhD  Plant Pathology Efficacy and physical mode of action of fungicides against Leather rot of strawberry and sensitivity of Phytophthora cactorum isolates to azoxystrobin.  Advisor: M. Ellis.

Saeb, Amr Tag El-Din 2006  PhD  Plant Pathology Phylogenetic and population genetic studies on some insect and plant associated nematodes.  Advisor: P. Grewal.

Briceno-Montero, Emilia G . 2006  MS  Plant Pathology Evaluation of biorational control options of bacterial spot and speck of tomato .  Advisor: S. Miller.

Jantasuriyarat, Chatchawan 2006  PhD  Plant Pathology Identification and characterization of genes involved in the interaction between rice and rice blast fungus, Magnaporthe grisea .  Advisor: G. Wang.

Mideros Mora, Santiago Xavier 2006  MS  Plant Pathology Study of incomplete resistance to Phytophthora sojae in soybean.  Advisor: A. Dorrance.

Nava Diaz, Cristian 2006  PhD  Plant Pathology Role of plant growth-promoting rhizobacteria in integrated disease management and productivity of tomato.  Advisor: S. Miller.

Computer Science Thesis Proposal

April 1, 2024 9:00am — 10:30am.

Location: 4405 - Reddy Conference Room, Gates Hillman 4405

Speaker: YIGE HONG , Ph.D. Student, Computer Science Department, Carnegie Mellon University https://www.cs.cmu.edu/~yigeh/

Understanding and Optimizing Complex Stochastic Systems Through Simple System

Complex stochastic systems that consist of a large number of interacting components naturally arise in various research domains, such as resource allocation in computing systems, congestion control in networks, wireless communication, machine maintenance, clinical trials, etc. 

The scale of these systems, coupled with the interactions among the components, makes the dynamics within them highly complex. Consequently, decision-making problems for such stochastic systems are often highly challenging. 

To understand and optimize these complex systems, we consider first solving a simple problem, and then converting the policy or performance bound obtained from the simple problem back to the complex problems. If the simple problem is properly constructed and the conversion is properly done, we can design a policy and prove its near-optimality. 

In this thesis proposal, we will present several pieces of work that investigate some example problems through the related simple systems. These problems include restless bandits, stochastic bin-packing, optimal scheduling of the G/G/k/setup queueing model, and multiserver-job scheduling. We will also present three problems that we plan to study. Two of these problems are related to restless bandits; the third problem is about the G/G/n queueing model. 

Thesis Committee:  

Weina Wang (Chair) Mor Harchol-Balter Alan Scheller-Wolf Jim Dai (Cornell University) Qiaomin Xie (University of Wisconsin-Madison) Yudong Chen (University of Wisconsin-Madison)  

 Information In Person and Zoom Participation. See announcement.

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