Efficiency Of Maize Production Research Articles

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.

Determinants of Production Efficiency of Maize-Dominated Farmers in Western Parts of Ethiopia in Gudeya Bila District: Evidence under Shifting Cultivation Area

Background In Ethiopia, maize is produced as major food crop that is based on traditional methods of production, and there exists inefficiency in the use of available scarce resources. Thus, poor people are failing to achieve rapid economic growth, development, and food security still today in the country. Hence, the best possible means of achieving development is through increasing the production efficiency of farmers. Thus, to estimate the levels of production efficiency, this study specifically used only data of farmers who are producing without ploughing by oxen and without using fertilizers in the study area under shifting cultivation. Method Stochastic frontier production is used to estimate the technical efficiency score, and the cost frontier model is used to estimate production efficiency. To determine the determinants of production efficiency, the Tobit model was used in this study. Result The Tobit model results show that loss due to wild animals, experience of household, and off-farm income had a negative impact on production efficiency of farmers. Regarding the positive determinants of production efficiency, land conservation practice and mobile use have a positive influence. Conclusion and recommendation. The farmers in the study area are inefficient in the production of maize. Since the loss of maize products is high due to wild animals such as pigs, apes, and monkeys that results in production inefficiency, the agricultural policies and strategies of Ethiopian governments should be directed toward providing tourism to protect those wild animals. Additionally, to increase the production efficiency, construction of terraces and soil bunds to conserve land and supporting the farmers by providing network facilities for mobile usage that boost maize production efficiency of farmers is essential for policymakers.

Optimizing fertilizer use efficiency for sustainable maize production in strongly acid soils of the Sudan Savanna agroecological zone of Northern Ghana

Given the importance of maize as a staple crop in northern Ghana, and the prevalence of acid soils used for maize production in the region, identifying effective nutrient management is critical to realize the full benefits of fertilizer application in maize production. In a two-year field study, we evaluated different fertilization strategies in three communities to identify the one that will best optimize fertilizer use efficiency in maize production in poorly fertile acid soils. The fertilization strategies were: (i) farmer practice (FP), in which only NPK fertilizer was applied; (ii) NPK plus lime (NPK + L); (iii) balanced fertilization (BF), in which NPK fertilizer and limiting secondary and micronutrients were applied; (iv) balanced fertilization plus lime (BF + L); and (v) control, in which no fertilizer was applied. We determined maize grain yield, nutrient recovery, and agronomic efficiency and the potential profitability with the fertilization strategies. The greatest yield was obtained with the BF + L treatment, followed by NPK + L, BF, FP, and control, in that order. Compared to FP, the NPK + L treatment nearly doubled N recovery, tripled P recovery, and doubled K recovery from the applied fertilizer. Whereas a negligible increase in fertilizer recovery efficiency occurred with the BF treatment compared to FP; the N, P, and K recovery efficiency increased by nearly 3, 4, and 2.5 times, respectively, with the BF + L treatment compared with FP. Gross profit margin analysis showed that the greatest potential profit margin was obtained with the BF + L treatment, followed by NPK + L, BF, and FP, in that order. From the combined data, we conclude that addition of lime is key to increasing fertilizer efficiency in strongly acid soils, and with a holistic approach of simultaneous addition of lime and secondary and micronutrients to NPK fertilizers, farmers will optimize fertilizer efficiency and increase profitability of their farming operation substantially.

Maize response to coupled irrigation and nitrogen fertilization under center pivot, subsurface drip and surface (furrow) irrigation: Soil-water dynamics and crop evapotranspiration

Determination of crop evapotranspiration (ETc) and root zone soil-water dynamics/distribution coupled with nitrogen (N) management strategies is important for effective management of agricultural fields for enhancing production efficiency. However, limited data and knowledge exist that sufficiently inform how soil-water dynamics and ETc response may vary with coupled irrigation levels and different N application timings under different irrigation methods. Extensive field experiments were conducted in 2016 and 2017 under center pivot (CP), subsurface drip irrigation (SDI), and furrow irrigation (FI) at full irrigation treatment (FIT), 80% FIT, 60% FIT, and rainfed treatment (RFT) with N application timing treatments of traditional N (TN), non-traditional-1 (NT-1), and non-traditional-2 (NT-2) to quantify and compare seasonal maize (Zea mays L.) grain yield, soil-water dynamics, ETc, and ETc vs. seasonal irrigation and total water supply relationships. Soil-water status and plant water extraction exhibited substantial differences between the irrigation levels and N management and with the irrigation methods. Irrigation method significantly (p < 0.05) influenced ETc. CP had significantly higher ETc than SDI; and SDI had significantly higher ETc than FI. The NT-1 and NT-2 treatments had significantly higher ETc than TN. ETc was greatly influenced by the water availability more than N timing applications. The slope of maize ETc exhibited inter-annual and intra-annual variation between N treatments, irrigation methods, and years. CP had higher slope than FI and SDI and FI had higher slope than SDI under traditional and NT N management in both years (except NT-2 at SDI in 2017). These important findings can provide guidance to improve maize production efficiency by considering the coupled irrigation and N management strategies under different irrigation methods.

Optimized Nitrogen Rate, Plant Density, and Regulated Irrigation Improved Grain, Biomass Yields, and Water Use Efficiency of Maize at the Oasis Irrigation Region of China

Nitrogen is a key factor in maize (Zea mays L.) grain and biomass production. Inappropriate application with sub-optimum plant density and irrigation can lead to low productivity and inefficient use. A two-year field experiment was conducted to determine which nitrogen rate, plant density, and irrigation level optimize grain, biomass yield, and water use efficiency. Three nitrogen rates of urea (46–0–0 of N–P2O5–K2O) (N0 = 0 kg N ha−1, N1 = 270 kg N ha−1, and N2 = 360 kg N ha−1), with three maize densities (D1 = 75,000 plants ha−1, D2 = 97,500 plants ha−1, and D3 = 120,000 plants ha−1), and two irrigation levels (W1 = 5250 m3/hm2 and W2 = 4740 m3/hm2) were investigated. The results show that both grain and biomass yields were affected by the main factors. The interaction between nitrogen rate and irrigation level significantly (p &lt; 0.001) affected grain yield but not biomass. It was observed that the grain yield increased correspondingly with nitrogen rate and plant density, while it decreased as the irrigation level increased. Water use efficiency was significantly (p &lt; 0.001) affected by the main factors and their interactions. Nevertheless, water use efficiency was highest at (5250 m3/hm2) × 270 kg N ha−1; × 360 kg N ha−1 × 120,000 plants ha−1 and increased from 62% to 68%. In addition, the highest biomass yield was recorded at 5250 m3/hm2 × 270 kg N ha−1; × 360 kg N ha−1 × 120,000 plants ha−1 while the interaction of either irrigation level with 0 and 270 kg ha−1 or 97,500 and 120,000 plants ha−1 yielded the lowest water use efficiency. Thus, optimized nitrogen rates, plant density, and alternate irrigation levels can support optimum grain and biomass yields. It can also improve nitrogen and water use efficiency in maize production.