Efficiency Of Maize Production Research Articles

Technical efficiency of maize production and their determinants among smallholder farmers in Ethiopia: a case study in Sidama Region

Technical efficiency of maize production and their determinants among smallholder farmers in Ethiopia: a case study in Sidama Region

Resource use efficiency of maize production in Balrampur and Kondagaon district of Chhattisgarh

Resource use efficiency of maize production in Balrampur and Kondagaon district of Chhattisgarh

Analysis of the Impact of Agricultural Mechanization on the Economic Efficiency of Maize Production

Against the background of comprehensively promoting the rural revitalization strategy, the replacement of agricultural labor by agricultural machinery in the hilly area of southwest China has become an indispensable input in the maize production process. Based on the national statistics from 2016 to 2022, the changes of maize planting area, yield, production costs and mechanization level in the southwest hilly area were analyzed through multiple regression. The grey correlation method was used to analyze the influence of production costs and mechanization level of maize planting on its economic efficiency, and the relationship between comprehensive mechanization rate and cost profit margin was predicted by the ridge regression model. The results show that (1) In addition to the planting area, the maize yield, production costs and mechanization level in the southwest hilly area showed an overall upward trend, among which the net profit was negative for six consecutive years, mainly because the labor costs accounted for too much of the total costs; (2) The average annual increase in the level of maize mechanization is 16%, but it is still lower than the national average; (3) Under the condition that other factors remain unchanged, for every 1% increase in the comprehensive mechanization rate, the cost profit margin increases by 0.467%, and it is determined that the most important factors affecting the growth of maize production economic efficiency are the sowing rate and the yield rate. It put forward suggestions to strengthen the mechanization of maize planting and develop maize agricultural harvesting machinery suitable for the hilly area.

EFFECTS OF CLIMATE CHANGE ADAPTATION STRATEGIES ON MAIZE PRODUCTION EFFICIENCY IN OTUKPO LOCAL GOVERNMENT AREA OF BENUE STATE, NIGERIA

The study examined the effects of climate change adaption strategies on maize production efficiency in Otukpo Local Government Area of Benue State, Nigeria. Multi-stage sampling procedure was employed to select 100 respondents for the study. Data were collected with the aid of structured questionnaire and analyzed using descriptive statistics and Stochastic Frontier Analysis (SFA). The results revealed that maize farmers were in their productive age with mean age of 31years. Majority (55%) of the maize farmers were married. The average household size, farm size and years of farming experience were 6 persons, 2.5 hectares and 8 years of experience in farming, respectively. The result on the climate change adaptation strategies used by the maize farming households revealed that most of the farmers adopted adjustment Improved/multiple varieties (17.6%), multiple planting dates (18%) and fertilizer application (20.6%) as climate change adaptation strategies in the study area. The result of predicted Stochastic Frontier model showed that the minimum and maximum technical efficiencies (TE) of the maize farmers were 0.11 and 0.98, respectively, with the mean efficiency of 0.88. This showed that if the efficiency of resources usage is increased by 12.0 percent, the maize farmers would operate on the production frontier given the existing technology. The result on the influence of climate change adaptation strategies used by maize farmers in the study area further revealed that the coefficient of farm size, fertilizer and agrochemicals had positive relationship with the value of maize output at P≤0.05, P≤0.10 and P≤0.01 levels, respectively. The result of the inefficiency model revealed that improved/multiple varieties and fertilizer application increased inefficiency of maize production at P≤0.05 and P≤0.10 levels, respectively, while alternative tillage practices decreased inefficiency of maize production at P≤0.01 level. The study concluded that maize production in the study area was not optimally efficient. The study recommended that farmers should be provided with credit facilities to help improve their capacity to adapt to climate change. Also, development partners should focus on awareness creation of farmers on better production techniques and climate change adaptation strategies through mass media and agricultural extension.

Modernizing smallholder agriculture and achieving food security: An exploration in machinery services and labor reallocation in China

AbstractThis study discusses the modernization of smallholder agriculture in China, where most farms are small, and farms' parcels are fragmented. The study puts forward a framework of agricultural modernization by vertical division of labor and specialized production in agriculture. We posit that hiring machinery services could be a pathway to connect smallholders with modern agriculture and achieve food security in China. Using household‐level data from China, this study examines how hiring machinery services affects farm productivity and rural households' welfare. Findings show that mechanization services increased rural Chinese families' food security and agricultural productivity. Hiring machinery services improves smallholders' income by influencing the input efficiency of maize production and increasing participation in off‐farm work. Our findings highlight the importance of technology to improve smallholder agriculture and food security, not only in China but also in other South and Southeast Asian countries.

Determinants of Smallholder Farmer Maize Production Efficiency in Western Parts of Oromia in Boneya Boshe woreda, East Wollega Zone: Evidence under Shifting Cultivation Area

Farming in Ethiopia can offer assistance in bringing dejected needs. Hence, the best possible means of achieving growth is by increasing the production efficiency of farmers. To estimate the levels of production efficiency, this study specifically used only data from farmers who are producing without plowing by oxen and without using fertilizers in the study area under shifting cultivation. Method: To determine the determinants of production efficiency, the Tobit model was used in this study. Result. The Tobit model results show that age of household, and herbicide use had a negative impact on the production efficiency of farmers. Regarding the positive determinants of production efficiency, labor, seed, and fertilizer (NPS) have a positive influence. Conclusion and Recommendation: The farmers in the study area are efficient in the production of maize. The government should give due attention to farmers' training by strengthening farmers' education and farmer training centers to make farmers more efficient producers and profitable by integrating local and traditional knowledge of farmers with formal knowledge of using herbicides. Farmers should also be advised, as they are youngest farmers engaging in farming work. Otherwise, the government should supply fertilizer and improve seed on credit.

Impact of Microdosing Practices on Technical Efficiency: An Analysis Accounting for Selection Bias Among Smallholder Maize Farmers in Burkina Faso

Smallholder maize farmers are currently confronted with the arduous challenge of managing limited financial resources while incessantly facing the issue of land degradation. To address this issue, an alternative solution has been implemented to optimize the use of chemical fertilizer by adopting microdosing. This innovative system not only helps them enhance their agricultural productivity but also allows them to protect the environment. However, it is unclear how microdosing adoption could increase the technical efficiency (TE) of maize production. Therefore, this research aims to assess how the adoption of microdosing affects the technical efficiency of maize production as well as identify the key factors that influence the technical efficiency of maize production in Burkina Faso. To achieve this goal, farm household survey data was conducted with 210 randomly selected farmers from the Plateau Central and northern regions of Burkina Faso. To account for potential selection biases that could result from both observable and unobservable factors, we used a sample selection stochastic production frontier model and a propensity score matching approach. A stochastic meta-frontier approach was applied to estimate TE differences and the technology gap between adopters and non-adopters. The findings showed that adopters of microdosing have an average efficiency of 68 percent, which is higher than the 53 percent estimated for non-adopters. Adopters of microdosing have been found to have high TE and better agricultural technology than non-adopters. The meta-frontier estimation revealed that the adoption of improved maize varieties would yield better returns. This study contributes significantly to the literature on how fertilizer microdosing affects maize productivity, as well as the policy implications of targeting and encouraging smallholder maize farmers in Burkina Faso to optimize the use of productive inputs and improve maize output by using microdosing.

A Stochastic Frontier Analysis of Maize Production Efficiency and Its Climate-Smart Agricultural Practice Determinants in Southeast, Nigeria

Efficient maize production and resource allocation are crucial for agricultural sustainability, particularly in climate-vulnerable areas like Southeast Nigeria. This study employs stochastic frontier analysis (SFA) to investigate the efficiency of maize production and the determinants of allocative efficiency under climate-smart agricultural practices (CSAPs). The study includes 375 maize farmers selected randomly for the research sample. The analysis begins with estimating the efficiency parameter of maize production, revealing a relatively low Sigma-square value (0.029) and a moderate Gamma value (0.786). The study found a positive association between various inputs such as landholding, seed quality, and organic manure application. The mean TE and AE are 0.894 and 0.747 respectively. Allocative efficiency analysis reveals that while water management practices significantly affect technical efficiency positively, they unexpectedly lead to lower AE. Access to information and adoption of early planting positively influence allocative efficiency. Further examination of socioeconomic determinants indicates the role of extension services (3.07)*** in enhancing AE, while cooperative membership negatively impacts it, possibly due to information asymmetry. These findings emphasize the need for tailored interventions to optimize resource allocation strategies and enhance agricultural productivity and sustainability in Southeast Nigeria, particularly amidst the challenges posed by climate change. Comprehending the complex dynamics of resource allocation and efficiency in agriculture is crucial for crafting efficient policies and interventions aimed at improving productivity and resilience amidst changing climate conditions.

Enhancing Corn Pest and Disease Recognition through Deep Learning: A Comprehensive Analysis

Pests and diseases significantly impact the quality and yield of maize. As a result, it is crucial to conduct disease diagnosis and identification for timely intervention and treatment of maize pests and diseases, ultimately enhancing the quality and economic efficiency of maize production. In this study, we present an enhanced maize pest identification model based on ResNet50. The objective was to achieve efficient and accurate identification of maize pests and diseases. By utilizing convolution and pooling operations for extracting shallow-edge features and compressing data, we introduced additional effective channels (environment–cognition–action) into the residual network module. This step addressed the issue of network degradation, establishes connections between channels, and facilitated the extraction of crucial deep features. Finally, experimental validation was performed to achieve 96.02% recognition accuracy using the ResNet50 model. This study successfully achieved the recognition of various maize pests and diseases, including maize leaf blight, Helminthosporium maydis, gray leaf spot, rust disease, stem borer, and corn armyworm. These results offer valuable insights for the intelligent control and management of maize pests and diseases.

ASSESSMENT ON ECONOMICS OF PRODUCTION AND MARKETING OF MAIZE IN SHANTINAGAR, DANG, NEPAL

The research was conducted to assess the production economics, different marketing channel and efficiency of resource use of maize farming in Shantinagar, Dang district of Nepal. The study was conducted with 60 farmers and 20 traders. Data was gathered using a pre-tested semi-structured questionnaire survey applied to the randomly selected samples. SPSS and Microsoft excel were used for entering the data and analysis of data. Resource use efficiency of maize production was determined by using Cobb-Douglas production function. Majority of respondents were engaged in agriculture (55%). Average maize cultivated land was 2.04 hectares. Maize production was profitable in the research area as indicated by benefit cost ratio of maize growing farmer was 1.52. Discovered different marketing channel were four. Price spread and producers share were in the range from 0-6.8 and 100-80.94% respectively. 10 % increase in cost of fertilizers, seed, FYM created in increase of outcome by 3.94, 5.24% and 0.04% respectively. The sum of coefficients was 0.933. For optimal allocation of resource, expenses on fertilizers, seed, pesticides and FYM were need to be increased by 84.89% 92.90%, 92.03%, 85.07% labour, tractor, bullock and thresher were found to be over utilized resource. The sum of coefficients was 0.933 which suggested return to scale is decreasing, factor of production included in the model if increased by 100% then it would result in 93.30% increase in maize production. Further, lack of timely availability of fertilizers, incidence of disease and pest/insects, lack of influence in price determination, improper coordination between market players, producers, and government agencies were the major difficulties in the production and marketing of maize in Shantinagar, Dang. This study has highlighted the maize production’s economic feasibility, marketing channels’s efficiency, Resource use efficiency and major difficulties in maize production and marketing in Shantinagar, Maize block, Dang.

Dynamics of Maize Production in Changing Climatic Scenario of Bihar: A Stochastic Frontier Approach

"The study attempted to capture the changing scenario of maize production and its efficiency in Bihar agriculture using an unbalanced panel stochastic frontier model in a dataset of all three agro-climatic zones over a period of 15 years (2006-2020). The findings indicated that increasing crop area, machinery used, and irrigation all had a significant impact on maize productivity. A random effect of the Tobit model for panel data is employed to identify the factors that affect technical efficiency. The technical efficiency of maize production has an influence on the maximum temperature, increasing the maximum temperature limit that is detrimental to maize production. The technical score of the current maize production technology is 0.83 indicates that Bihar’s maize production is 83% technically efficient when accounting for climatic factors like maximum and minimum temperatures and rainfall. Technical efficiency scores for Zones 1 and 2, which are well known for being intensely maize-producing regions, are 0.84 and 0.88, respectively. Since crop leftover is distinct from maize production and may be utilized to increase technical efficiency, crop residue is strongly related to maize’s technical efficiency. The highest levels of technical efficiency were seen in Bihar’s maize production from 2006 to 2020, with an average technical efficiency of 0.88. Bihar’s agricultural Zone 2 has a maximum technical efficiency of 0.97, making it the state’s top producer of maize."

Does sending farmers back to school increase technical efficiency of maize production? Impact assessment of a farmer field school programme in Indonesia

A farmer field school programme aims to impart knowledge and promote new technology. The programme is expected to enhance farmers’ performances. However, the empirical evidence remains unclear. A few studies have examined the impact of this programme on technical efficiency in Indonesia. The current study specifically investigates the causal impact of the Farmer Field School of Integrated Crop Management (FFS-ICM) programme on technical efficiency of maize production in Indonesia. We used a stochastic production frontier model and propensity score matching (PSM) to examine the causal impact of FFS-ICM on the technical efficiency of maize production. The results show that the average farm technical efficiency is 68.3%, which suggests that the production can be further improved. The PSM estimation indicates that FFS-ICM increased the technical efficiency by 1.48%, demonstrating the importance of agricultural extension programmes in rural areas in Indonesia. Nevertheless, the relatively small estimated impact raises the issue of cost effectiveness of the programme.

Economic and Technical Efficiency of Maize Production in the Eastern District of Bhutan: Stochastic Frontier Approach

This research paper seeks to deal with the problem of economic and technical efficiency of maize farmers located in the eastern region of Bhutan. For the objective of this paper, the stochastic frontier parametric approach was employed. The socio-economic and production data were collected from 120 maize growing farmers using simple random sampling technique for the production year 2020-2021. Results show that maize producing farmers are 81.47 % technically efficient and 78.19 % economically efficient in producing maize. Farm size, household size, and training positively influences the maize efficiency. The paper presents supporting evidence for more government policy in terms of provision of subsidies on agrochemicals and providing training for better management skills to the farmers.

Resource use efficiency and factors influencing maize production in Kuje Area Council, Federal Capital Territory, Nigeria

This study estimated resource-use efficiency and factors influencing maize production in Kuje Area Council, Federal Capital Territory, Nigeria. The specific objectives were to; determine the socioeconomic characteristics of maize farmers; analyse cost and returns associated with maize production; evaluate factors influencing the output of maize production; determine the resource-use efficiency of maize production and identify the constraints faced by farmers in maize production in the study area. Multistage sampling technique was employed to select 60 7sampled maize farmers in the study area. The following tools of analysis were used to achieve the specific objectives of the study. Descriptive statistics; Gross margin analysis; resource-use efficiency and Cobb Douglass production function. The results showed that majority, 75 percent, of the sampled respondents were male while 73.3 percent were married. From the results it can further be deduced that 48.3 percent of the sampled respondents attended secondary school and 31.7 percent attended tertiary institution while the rest stopped at primary school level or did not have any formal education. The results also indicated that about 55 percent of the sampled maize farmers had household size ranges within 6-10. 100 percent of the sampled respondents had no access to credit and 83.4 percent had no access to extension services. From the analysis of cost and returns associated with maize production in the study area, the total revenue (TR) realized on average was N1,269,152.69 and the average total variable cost (TVC) was N188,462.69, the gross margin obtained was N1,080,690. With this result we can say that maize production is profitable in the study area. The results of the resource-use-efficiency revealed that farm size, seed input and labour input were underutilized while fertilizer input and chemical input were over utilized by maize farmers. The results of the Cobb Douglass production function model revealed that the factors influencing total output of maize production in the Study area were farm size (P<0.1), labour (P<0.01), chemical (P<0.01) and Fertilizer P<0.05). The major constraints faced by maize farmers in the study area include; inadequate capital, lack of fertilizer and lack of extension agent. Therefore, the study recommends that maize farmers should be encouraged to join the farmers’ association, and supported with credit facilities. Government should supply inputs like agrochemical, fertilizer and improved seed varieties to maize farmers at a subsidized rate and at appropriate time and extension agents are to guide the farmers in the usage of these inputs while mechanize farming system should be encouraged by providing tractors to replace local farm implements. Good roads are essential in linking maize production areas with available markets around the study area.

Optimization of sowing date and irrigation schedule of maize in different cropping systems by APSIM for realizing grain mechanical harvesting in the North China Plain

Grain mechanical harvesting can decrease the harvest cost and improve the efficiency of maize production. However, the optimization of the sowing date and irrigation schedule of maize in existing studies rarely considered the grain mechanical harvesting. Therefore, the sowing date and irrigation schedule of two maize cultivars in three cropping systems was optimized by considering yield, water use efficiency (WUE), and grain mechanical harvesting. The quality of grain mechanical harvesting is mainly influenced by grain moisture content. Thus, Agricultural Production Systems sIMulator (APSIM) was coupled with a grain dry down model to simulate maize production in the northern part of the North China Plain (NCP). The latest date for grain mechanical harvesting of maize was analyzed using the date when the grain moisture content decreased to 25% for the first time (DCM25). The DCM25, yield, WUE, and irrigation amount were used as constraints in the optimization. The results showed that, the optimal sowing dates under full irrigation of spring maize in SM (monocropping maize system), spring maize and summer maize in WMM (winter wheat-summer maize-spring maize system) for Huanong887 were from 6th May to 10th June, from 6th May to 16th May and 10th June, respectively. The optimal sowing dates of spring maize in SM were from 1st May to 5th June for Zhengdan958. The summer maize in DWM (winter wheat-summer maize double cropping system) could not achieve high-quality grain mechanical harvesting when using Huanong887 and Zhengdan958. In different hydrological year types, the optimal irrigation schedule with grain mechanical harvesting involved irrigation (80 mm each time) 1–3 times during sowing, jointing and flowering stages of spring maize in SM and summer maize in WMM. For spring maize in WMM, the optimal irrigation schedule involved irrigation 2–3 times during sowing, jointing, and flowering stages. The optimization method could provide a reference for other sites to promote high-efficient maize production.

Innovations in smallholder agricultural financing and economic efficiency of maize production in Ghana’s northern region

This study used PSM and the selectivity-corrected framework for stochastic frontiers to examine how innovative agricultural finance practices of maize farmers in northern Ghana affect economic efficiency. We find, consistently, that users of innovative financing have higher technical (TE), allocative (AE), and economic efficiency (EE) scores than nonusers. The efficiency gaps between users and nonusers are 4% for TE; 5% for AE; and 10% for EE. Contrary to expectation, farmers’ access to mechanized services diminished their TE. Our findings indicate that short-term policies to increasing maize output should focus on reducing inefficiency levels than introducing new technologies. This can be achieved by providing technical training to farmers through improved access to agricultural extension services, provisioning farmers with timely access to tractors and equipment, and facilitating access to profitable output markets. The positive efficiency effects of using innovative financing suggests that policies should favour creating further sources of informal financial options for poor rural farmers. Here, Village Savings and Loans Associations can mitigate credit supply risks by linking farmers directly to inputs and reducing the need for cash loans. Local governments must harness Ghana Government’s Planting for Export and Rural Development programme to create sustainable employment opportunities that enable farmers to raise farm investment capital in the off-season.

The analysis of the spatio-temporal differentiation characteristics of total factor productivity of maize: Introducing the perspective of financial support

The problem we studied is the analysis of the spatio-temporal differentiation characteristics of total factor productivity of maize. The importance lies in that maize is one of the prominent grain crops in China, the improvement of maize production efficiency is helpful to guarantee the national food security. From the perspective of financial support, deepened the connotation of DEA model, this paper innovatively constructs the Global Malmquist index method, in view of the data of 13 major grain producing areas in China from 2007 to 2017, talks over the temporal evolution characteristics and spatial distribution modes of total factor productivity (TFP) of maize. The main results show that the TFP of maize production in China’s major grain producing areas is mostly of a high level between 2007 and 2017, revealing a fluctuating upward drift, with an average annual rate of increase of 10.7%. The conclusion we draw from the results is that as shown in the decomposition index, the variation of TFP of maize production mainly attributes to the shift of technological progress. In terms of space, the TFP of maize production in the central district is the highest, the eastern and western districts are relatively low.

Comparative analysis of the effect of credit from FECECAM and SIAN'SON microfinance on the economic efficiency of maize production in northern Benin

Comparative analysis of the effect of credit from FECECAM and SIAN'SON microfinance on the economic efficiency of maize production in northern Benin

Impact of natural resource conservation technology on productivity and technical efficiency in rainfed areas of Southern India

This paper assessed the impact of natural resource management technology (NRCT) on productivity and efficiency in maize production using an endogenous switching regression model in rainfed areas of Southern India. We also identified factors influencing adoption of NRCT, and technical efficiency in maize production. For this study, plot-level primary data from 303 farm households cultivating maize on 419 plots were collected. Results show that adoption of NRCT has resulted in an increase in maize productivity by 490 kg per ha and has also reduced technical inefficiency by 28% as compared to non-adopters. Furthermore, access to credit, better extension services and training on natural resource management are crucial factors positively affecting the adoption of NRCT as well as enhancing the technical efficiency of maize production. Therefore, these factors need to be considered when formulating policies and programmes that aim to improve crop productivity in rainfed areas, as well as sustaining natural resources.

Technical Efficiency of Maize Production and Its Influencing Factors in the World’s Largest Groundwater Drop Funnel Area, China

Improving the efficiency of maize production is of great significance for global food security and the effective supply of agricultural products. Based on the survey data of 381 rural households, this study uses a stochastic frontier analysis to estimate the efficiency value and empirically analyze the factors affecting the technology efficiency of maize production in the Hengshui area of the North China Plain. First, higher costs were found to be related to extensive production methods of fertilization, pesticide application, and irrigation. Second, the results showed that there was an inverted U-shaped relationship between the irrigation cost and maize output. Specifically, when the irrigation cost was about 938 yuan/hectare, the maize output per unit area was optimal. Third, there was also an inverted U-shaped relationship between the fertilizer cost and maize output, and the loss of technical efficiency of maize output was minimal when the fertilizer cost is 2547 yuan/hectare. In addition, the findings of the inefficiency influencing factor model suggested that temperature and humidity were all positively associated with the non-efficiency of maize production. These findings can provide empirical support for improving the efficiency of maize production in North China or arid and semi-arid regions around the world.