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Optimizing maize irrigation strategies is essential for improving water use efficiency and crop yields in arid regions. However, limited quantitative research exists on these optimizations. This study focuses on the Heihe River Basin in China, aiming to (1) optimize maize irrigation strategies using a differential evolution (DE) algorithm integrated with the AquaCrop model and remote sensing data; (2) compare the DE algorithm's performance with the traditional Nelder–Mead (fmin) algorithm regarding yield improvement and irrigation water use; and (3) assess the benefits of different irrigation strategies under limited water availability. Covering 22 irrigation management zones in Zhangye City, Gansu Province, the study utilized soil, weather, and crop data from Google Earth Engine to drive the AquaCrop model. Results indicate that the DE algorithm achieved higher simulated maize yields, increasing by 0.5 to 1 t/ha on average compared to the fmin algorithm, albeit with a 30% rise in irrigation water usage. The integration of both the DE and fmin algorithms with the AquaCrop model facilitates the development of tailored irrigation strategies, providing a scientific foundation for sustainable agricultural water management. These findings can guide efficient irrigation management plans in the region and similar arid systems. [ABSTRACT FROM AUTHOR]

Reducing greenhouse gas (GHG) emissions and ammonia (NH3) volatilization by improving fertilization methods to increase crop yield is beneficial for the green and sustainable development of agriculture. This study evaluated the effects of farmer practice fertilization (FP), nutrient expert optimized fertilization (NE—optimized fertilizer usage and time), the application of stable compound fertilizer (SF), and the application of controlled-release coated urea (CRU) on greenhouse gases, NH3 volatilization, and corn yield through field experiments set up in the corn planting area in western Liaoning Province. The results showed that compared with FP treatment, NE could significantly reduce NH3 volatilization by 28% and increase N2O release by 41%. Compared with FP treatment, SF could significantly reduce NH3 volatilization by 48.54%, N2O release by 38.54%, CO2 release by 13.96%, global warming potential (GWP) by 16.60%, and greenhouse gas emission intensity (GHGI) by 27.23%, and could significantly increase corn yield by 15.86%. Compared with FP treatment, CRU could significantly reduce NH3 volatilization by 63.46%, CO2 release by 11.98%, GWP by 10.73%, and GHGI by 13.77%, while increasing N2O release by 6.71%. Overall, NE, SF, and CRU treatments all showed better effects than FP treatment in increasing corn yield or reducing NH3 volatilization and GHG emissions. Among them, SF treatment demonstrated superior performance over NE and CRU treatments in terms of NH3 volatilization, corn yield, and GHGI. Therefore, the application of stable compound fertilizer is the optimal choice for corn planting in western Liaoning, with broad application prospects. [ABSTRACT FROM AUTHOR]

Drainage is an important aspect of effective water management in row-crop agriculture. Drainage systems can be broadly categorized as either subsurface or surface drainage. A significant amount of design goes into subsurface drainage installations, such as tile networks, and permanent surface drainage installations, such as waterways and berms. However, many farmers also implement temporary surface drainage installations to drain localized areas within their fields each year. This practice involves creating shallow water paths, typically using spinner ditchers, and it is especially commonplace in areas with poor soil permeability. However, this practice is traditionally performed using only observations by farmers and without any data-based workflows. The objective of this study was to analyze the potential yield benefits from a more data-informed approach to surface drainage on a production row-crop farm by exploring corn and soybean yield data from 2008–2021 from two fields where a data-informed approach to surface drainage was implemented. Field topography and drainage information were combined with yield maps from prior years with traditional ad hoc drainage and the years following the incorporation of the data-informed approach to better understand the impact of the workflow. Geospatial distribution of the average normalized crop yields and elevation maps for the fields were analyzed to isolate the yield impacts of the areas affected by the data-informed on-farm surface drainage artifacts. In the years after implementation of the data-informed surface drainage approach, Field 1 and Field 2 showed respective increases of 18.3% and 13.9% in average corn yields. Further analysis isolating three areas affected by the surface drainage using topography and drainage layout showed that all three isolated areas improved more than the field averages, ranging from 15.9–26.5% for Field 1 and 21.4–40.2% for Field 2. Similarly, soybean yields were also higher in the isolated affected areas after the data-informed drainage ditch construction. The findings highlight the effectiveness of data-informed on-farm surface drainage, a relatively straightforward approach that proved beneficial for both soybean and corn production. [ABSTRACT FROM AUTHOR]

Corn (Zea mays L.) silage yield monitor data offer crucial insights into spatial and temporal yield variability. However, equipment's sensor malfunctioning can result in data loss, and yield sensor systems are expensive to purchase and maintain. In this study, we analyzed corn silage yield data from two fields and three years each for two dairy farms (Farm A and B). We aimed to explore the potential of integrating high-resolution satellite data, topography, and climate data with machine learning models to estimate missing yield data for a field or a year. Our objectives were to identify key yield-explaining features and assess the accuracy of different machine learning models in estimating silage yield. Results showed that the features differed among farms with a Two-Band Enhanced Vegetation Index, EVI2 (Farm A), and elevation (Farm B) emerging as the most prominent predictors. Ensemble-based models like XGBoost, Random Forest, and Extra Tree regressors exhibited superior predictive performance. However, XGBoost performed poorly when applied to unseen fields or years, whereas Extra Tree regressor, followed closely by Random Forest, emerged as a more reliable model for predicting missing data. Despite achieving reasonable accuracy, the best performance for estimating data for a missing field (6.46 Mg/ha) and year (5.51 Mg/ha) fell short of the acceptable error threshold of 4.9 Mg/ha currently used in state policy to evaluate if a management change resulted in a yield increase. These findings emphasize the need for higher-resolution data and extended years of yield records to better capture the trends in farm-scale yield applications. [ABSTRACT FROM AUTHOR]

Despite the critical need for nitrogen (N) in cropping systems, excessive N fertilizer application has severe environmental consequences. The synergistic interaction between sulfur (S) and N in plant nutrition could be exploited to increase N utilization, thereby maximizing N recovery and reducing losses. In a three-year study at six locations across three countries (USA, Ghana, and Mali), we evaluated the effect of S availability on N leaching losses from N fertilizer application using corn as the study crop. The study consisted of three S sources (micronized elemental sulfur [MES], untreated elemental sulfur [ES], and ammonium sulfate [AS]); five S application rates [(i) site-specific recommended S rate (SR), (ii) ¼ of the recommended S rate (25%_SR) (iii) ½ of the recommended S rate (50%_SR), (iv) ¾ of the recommended S rate (75%_SR); and (v) 1¼ of the recommended S rate (125%_SR)]; and a single N application rate (site-specific recommended N rate). Regardless of the S source, N recovery progressively increased with increasing S application rate. For the AS and MES sources, leachate nitrate concentration from the treatments with S application ≥ SR was statistically similar to that of the background concentrations, and the highest concentrations occurred with the treatment with no S application. Thus, for environmental stewardship, a critical look into S application in cropping systems is a necessity due to its synergistic interaction with N. In addition to improving productivity and enhancing efficient recovery of applied N fertilizers, S availability will minimize nitrate leaching commonly associated with application of N fertilizers. [ABSTRACT FROM AUTHOR]

Sustainable use of croplands is facing a challenge to maintain organic carbon (C) in soil. Pyrolyzed coal or coal char (CC) is a porous C material produced from the pyrolysis of coal containing high organic C, large surface area, and low bulk density like biochar (BC). This study evaluates corn (Zea mays L.) grain yield and selected soil properties in soil amended with CC and BC at two rates (22 and 44 Mg ha−1) with farmyard manure (FM) (66 Mg ha−1) and without FM addition. This field experiment was performed in sandy loam soil at the University of Wyoming's Sustainable Agricultural Research and Extension Center (SAREC), Lingle, WY, USA. Two years of field study results indicated CC and BC applied at 22 Mg ha−1 with FM resulted in significantly greater average corn grain yields (13.04–13.57 Mg ha−1) compared to the no char's treatment (11.42 Mg ha−1). Soil organic matter (SOM) content was significantly greater in the higher application rates of CC and BC than in treatments without chars. Overall, soil nitrate nitrogen (NO3-N), phosphorous (P), and potassium (K) were found significantly greater in CC and BC co-applied with FM treatments. Soil water-holding capacity (WHC) significantly improved in sandy loam soil (up to 27.6% more than the no-char treatment) at a greater concentration of char materials. This study suggests that char materials applied at a moderate rate (22 Mg ha−1) with FM can improve soil properties and crop yield. [ABSTRACT FROM AUTHOR]

Straw return is an effective measure to increase soil sustainability. However, few studies have examined the effects of different straw return methods on soil structure, soil organic carbon content and maize yield or the potential relationships between those variables. Therefore, we developed a field orientation experiment to study the effects of different straw return methods on soil porosity, soil aggregate stability, the soil organic carbon content and maize yield. Four treatments were established: flat no-tillage with full straw mulching (FM), ridge no-tillage with full straw mulching (LM), rotary tillage with full straw incorporation (LX), and conventional tillage without straw (CK) as the control treatment. Compared with those of the CK treatment, the soil porosities (f) in the FM, LM and LX treatments significantly increased by 6.7%, 8.8% and 7.9%, respectively; the soil aggregate destruction rates (PAD) decreased by 17.3%, 34.3% and 16.9%, respectively. In addition, the FM, LM and LX treatments effectively increased the mean mass diameters (MWDs) of the soil aggregates and the soil organic carbon content. Compared with those in the CK treatment, the three-year average yields in the FM, LM and LX treatments significantly increased by 5.2%, 7.2% and 4.1%, respectively. Moreover, the f, MWD, soil organic carbon content and corn yield were positively correlated. Our study indicates that the LM treatment was most effective in improving soil structure and increasing soil organic carbon content with corn yield. [ABSTRACT FROM AUTHOR]

The objective of this study is to promptly and accurately allocate resources, scientifically guide grain distribution, and enhance the precision of crop yield prediction (CYP), particularly for corn, along with ensuring application stability. The digital camera is selected to capture the digital image of a 60 m × 10 m experimental cornfield. Subsequently, the obtained data on corn yield and statistical growth serve as inputs for the multi-source information fusion (MSIF). The study proposes an MSIF-based CYP Random Forest model by amalgamating the fluctuating corn yield dataset. In relation to the spatial variability of the experimental cornfield, the fitting degree and prediction ability of the proposed MSIF-based CYP Random Forest are analyzed, with statistics collected from 1-hectare, 10-hectare, 20-hectare, 30-hectare, and 50-hectare experimental cornfields. Results indicate that the proposed MSIF-based CYP Random Forest model outperforms control models such as support vector machine (SVM) and Long Short-Term Memory (LSTM), achieving the highest prediction accuracy of 89.30%, surpassing SVM and LSTM by approximately 13.44%. Meanwhile, as the experimental field size increases, the proposed model demonstrates higher prediction accuracy, reaching a maximum of 98.71%. This study is anticipated to offer early warnings of potential factors affecting crop yields and to further advocate for the adoption of MSIF-based CYP. These findings hold significant research implications for personnel involved in Agricultural and Forestry Economic Management within the context of developing agricultural economy. [ABSTRACT FROM AUTHOR]

Corn-soybean rotation is a cropping pattern to optimize crop structure and improve resource use efficiency, and nitrogen (N) fertilizer application is an indispensable tool to increase corn yields. However, the effects of N fertilizer application levels on corn yield and soil N storage under corn-soybean rotation have not been systematically studied. The experimental located in the central part of the Songnen Plain, a split-zone experimental design was used with two planting patterns of continuous corn (CC) and corn-soybean rotations (RC) in the main zone and three N application rates of 0, 180, and 360 kg hm-2 of urea in the secondary zone. The research has shown that RC treatments can enhance plant growth and increase corn yield by 4.76% to 79.92% compared to CC treatments. The amount of N fertilizer applied has a negative correlation with yield increase range, and N application above 180 kg hm-2 has a significantly lower effect on corn yield increase. Therefore, a reduction in N fertilizer application may be appropriate. RC increased soil N storage by improving soil N-transforming enzyme activity, improving soil N content and the proportion of soil organic N fractions. Additionally, it can improve plant N use efficiency by 1.4%-5.6%. Soybeans grown in corn-soybean rotations systems have the potential to replace more than 180 kg hm-2 of urea application. Corn-soybean rotation with low N inputs is an efficient and sustainable agricultural strategy. [ABSTRACT FROM AUTHOR]

In this research, within the specified years, corn in Türkiye by years; It is aimed to determine the existence of a causality between the production amount, cultivation area, yield, export amount, import amount and economic crises added as dummy variables. For this purpose, corn production, corn cultivation area, corn yield, corn export amount and corn import amount in the statistical tables between 1995 and 2020 published by the Turkish Grain Board (TMO; 2021). In addition, the crisis years were added to the data set as a dummy variable to see the crisis effect. In the research, Augmented Dickey Fuller method is the test that checks whether the series is stationary. After deciding that the series is non-stationary with the ADF test, the most appropriate lag length was determined with the VAR (Variance Autoregressive Model) model, and the analysis was carried out with the help of the VAR Granger Causality method. According to the estimation results, corn in the statistical tables between 1995-2020; In the data set, in which the crisis years were added as a dummy variable to see the effects of the crisis in terms of production, cultivation area, yield, export amount and import amount; First difference is stationary, Akaike Information Criterion is the smallest, 2nd lag length is the most suitable lag length, and corn; corn; It has been determined by the analysis that production amount, import amount and economic crises are a one-way cause of exports, and corn cultivation area is a one-way cause of economic crises. [ABSTRACT FROM AUTHOR]

Previous research has demonstrated the ability of isolate Pseudomonas thivervalensis SC5 to express the enzyme 1-aminocyclopropane-1-carboxylate deaminase (ACC), which regulates ethylene levels, one of the most important phytohormones in the regulation of plant growth and development. Thus, the present study evaluated the agronomic efficiency of a biological conditioner based on P. thivervalensis SC5 in the growth and productivity increases of corn in Brazil. It was found that corn was highly responsive to the inoculation of P. thivervalensis SC5, with increments ranging from 10.1 to 40.6% in the production of dry shoot biomass (DSB) compared to the control, while for grain yield the increments ranged from 9.0 to 27.8%. The increments are related to the levels and accumulations of N and P in the shoots of the plants. This suggested the participation of P. thivervalensis SC5 in mechanisms of soil modulation and nutrient acquisition. The inoculation of P. thivervalensis SC5 provided average increments in FDA hydrolysis ranging from 16.7 to 47.4% compared to the control, confirming the ability of this strain to increase the supply of nutrients to plants. Therefore, it is concluded that Pseudomonas thivervalensis SC5 participates in key mechanisms in the soil-plant system, with a consequent improvement in soil quality and other plant-related parameters. [ABSTRACT FROM AUTHOR]

Winter cover crops can provide multiple ecosystem services but can reduce succeeding maize (Zea mays L.) yield and water-use efficiency (WUE) by depleting soil water compared with no cover crop in arid and semi-arid regions. We examined the impacts of winter cover crops (lentil [Lens culinaris L.], oat [Avena sativa L.], lentil/oat mixture, and no cover crop) and nitrogen fertilization rates (0, 165, and 220 kg N ha1) to succeeding maize on soil water storage at planting (SWP) and harvest (SWH) at the 0–2 m depth, evapotranspiration (ET), maize yield, and water use efficiency (WUE) from 2017 to 2022 in the Loess Plateau of China. We measured cover crop biomass and maize yield at harvest, SWP and SWH using a soil probe, and ET and WUE based on growing season precipitation and water use. Cover crop biomass yield was 59–134 % greater for oat with 220 kg N ha−1 than lentil with other N fertilization rates. The SWP was 5–22 % greater for no cover crop with 0 kg N ha−1 than other cover crops with N fertilization rates. The SWH and ET varied with cover crops, N fertilization rates, and years. Maize yield and WUE were 12–42 % greater for lentil with 220 kg N ha−1 than oat and no cover crop with other N fertilization rates. Although cover crops depleted soil water at maize planting, lentil cover crop with 220 kg N ha−1 can enhance maize yield and WUE compared with other cover crops and N fertilization rates in the Loess Plateau of China.

Past research has shown that controlled corn seed orientation at planting leads to symmetrically oriented leaves across rows, resulting in increased grain yields. This study determined the financial outcome, in terms of net present value (NPV), of implementing new corn planter technology that allows for corn seed orientation. NPV's were estimated using stochastic analysis for input prices, yield, and revenue. Additionally, the payback period was calculated. Sensitivity analysis was conducted using potential price points and usage levels for the new corn planter technology. Three producer usage levels were evaluated: 647 ha (low), 971 ha (medium), and 1295 ha (high). All scenarios were analyzed over 5 years. Three potential machine (technology) costs were also evaluated: $32,000, $96,000, and $160,000. The use of oriented corn seed placement technology (OSP) outperformed traditional methods for all usage levels when sold at $32,000. The use of OSP was about equal for the high-usage producer at a price of $96,000. Within the parameters evaluated, some producers would benefit from adopting the oriented corn seed placement technology if the technology was offered at a price of $32,000. This research is of interest to developers and manufacturers interested in developing such technology, as well as researchers considering further evaluation of oriented corn seed placement. Further research is needed to better establish yield benefits and prices for oriented corn seed technology. [ABSTRACT FROM AUTHOR]

The purpose of this study was to investigate the coupling effects of water and different mulching materials on the yield and nutrient components of silage corn. 'Long qingzhu No.1' maize was selected as experimental material. Two water gradients of full water irrigation (W1: 75%~95% of soil relative water content) and water stress (W2: 35%~55% of soil relative water content) were set, and four different plastic film mulching treatments, such as white plastic film (M1), black ground cloth (M2), biodegradable plastic film (M3) and liquid plastic film (M4), were selected. Eight treatments were set up, and full irrigation white plastic film mulching (W1M1) was used as control. The biological yield and nutrient content were measured at heading stage, filling stage and maturity stage respectively. The results showed that there was no significant difference in hay yield of silage maize at heading stage (initial stage of water stress) among different groups (P>0.05). Under water stress (W2M1, W2M2, W2M3, and W2M4), the yield of hay at maturity was significantly lower than that of W1M1 (P<0.05). The fresh grass yield of W2M4 at heading stage was significantly lower than that of full irrigation group (W1M1, W1M2, W1M3, and W1M4) (P<0.05). The fresh grass yields of water stress treatments (W2M1, W2M2, W2M3, and W2M4) was significantly lower than those of W1M1, W1M2, and W1M3 (P<0.05). At heading stage, the content of crude protein (CP) of maize treated with W2M1 and W2M3 was significantly lower than that of W1M1 (P<0.05), and the content of neutral detergent fiber (NDF) of W2M2, W2M3, and W2M4 was significantly higher than that of W1M1 (P<0.05). The relative feeding value (RFV) of W2M1, W2M2, and W2M3 was significantly lower than that of W1M1 at grain filling stage (P<0.05). At the mature stage, the content of crude fat (EE) in W1M4 and W2M4 was significantly lower than those in other treatments (P<0.05), and the content of NDF in W1M2, W1W3, and W1M4 was lower than those in W2M1 and W2M2 (P<0.05). Fresh grass yield was positively correlated with ADF and RFV (P<0.05) and negatively correlated with NDF (P<0.05). The study indicates that water stress and liquid plastic film mulching are not conducive to the improvement of silage corn yield and nutrient components compared with full irrigation and white plastic film mulching. [ABSTRACT FROM AUTHOR]

The vulnerability of corn yield to high temperature and insufficient rainfall in the US mid-west is widely acknowledged. The impact of extreme weather and genetic development on corn yield is less well known. One of the main reasons is that the multicollinearity in the variables can lead to confounding results. Here we model the impact of climate and genetic development by employing an elastic net regression model to address the multicollinearity issue. This allows us to develop a more robust multiple regression model with higher predictive accuracy. Using granular data for Iowa from 1981-2018, we find that corn yield is vulnerable to high mean summer temperatures particularly in July, a widening diurnal temperature range in June and dry summer conditions (due to extremely low rainfall) from June-August. We find that overall climate impact reduced average annual yield by 0.7%. We also find that genetic development which led to earlier planting dates, widening duration of the reproductive interval, higher growing degree day accumulation and larger net planted area had a beneficial impact on the Iowa corn yield during 1981-2018 resulting in an average annual yield improvement of 1.8% per annum. This provides a basis for optimism that these genetic developments and management practices will continue to adapt and improve in the future to counter the impact of climate change on corn yield. We have also modelled the impact of future climate change using the latest climate projections from the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR6). These climate projections show that the average temperature during the growing season (MayO-October) will increase by 2.4-2.9 °C by mid-century while the average spring temperature (March and April) will increase by a relatively slower 1.9-2.3 °C by mid-century. Additionally, climate projections show that both temperature and rainfall will also become more extreme in the future with the changes varying from spring to summer. Our results show that, just due to climate change alone in Iowa corn yield will decline between 1.4-1.7% per annum until mid-century (or 1.2-2.1% per annum until the late twenty first century). [ABSTRACT FROM AUTHOR]

Abstract The objective of this study is to promptly and accurately allocate resources, scientifically guide grain distribution, and enhance the precision of crop yield prediction (CYP), particularly for corn, along with ensuring application stability. The digital camera is selected to capture the digital image of a 60 m × 10 m experimental cornfield. Subsequently, the obtained data on corn yield and statistical growth serve as inputs for the multi-source information fusion (MSIF). The study proposes an MSIF-based CYP Random Forest model by amalgamating the fluctuating corn yield dataset. In relation to the spatial variability of the experimental cornfield, the fitting degree and prediction ability of the proposed MSIF-based CYP Random Forest are analyzed, with statistics collected from 1-hectare, 10-hectare, 20-hectare, 30-hectare, and 50-hectare experimental cornfields. Results indicate that the proposed MSIF-based CYP Random Forest model outperforms control models such as support vector machine (SVM) and Long Short-Term Memory (LSTM), achieving the highest prediction accuracy of 89.30%, surpassing SVM and LSTM by approximately 13.44%. Meanwhile, as the experimental field size increases, the proposed model demonstrates higher prediction accuracy, reaching a maximum of 98.71%. This study is anticipated to offer early warnings of potential factors affecting crop yields and to further advocate for the adoption of MSIF-based CYP. These findings hold significant research implications for personnel involved in Agricultural and Forestry Economic Management within the context of developing agricultural economy.

Corn (Zea mays L.) silage yield monitor data offer crucial insights into spatial and temporal yield variability. However, equipment’s sensor malfunctioning can result in data loss, and yield sensor systems are expensive to purchase and maintain. In this study, we analyzed corn silage yield data from two fields and three years each for two dairy farms (Farm A and B). We aimed to explore the potential of integrating high-resolution satellite data, topography, and climate data with machine learning models to estimate missing yield data for a field or a year. Our objectives were to identify key yield-explaining features and assess the accuracy of different machine learning models in estimating silage yield. Results showed that the features differed among farms with a Two-Band Enhanced Vegetation Index, EVI2 (Farm A), and elevation (Farm B) emerging as the most prominent predictors. Ensemble-based models like XGBoost, Random Forest, and Extra Tree regressors exhibited superior predictive performance. However, XGBoost performed poorly when applied to unseen fields or years, whereas Extra Tree regressor, followed closely by Random Forest, emerged as a more reliable model for predicting missing data. Despite achieving reasonable accuracy, the best performance for estimating data for a missing field (6.46 Mg/ha) and year (5.51 Mg/ha) fell short of the acceptable error threshold of 4.9 Mg/ha currently used in state policy to evaluate if a management change resulted in a yield increase. These findings emphasize the need for higher-resolution data and extended years of yield records to better capture the trends in farm-scale yield applications.

This research probes the potential of weather derivatives as tools for mitigating the variability of crop yields due to climatic uncertainties in China. Centered on Tongliao City in Inner Mongolia, the study exploits a long short-term memory (LSTM) network to dissect and simulate 32 years of local precipitation data, thereby achieving a simulation of high reliability. Further exploration through a multiple linear regression model confirms a marked positive relationship between rainfall amounts and maize yields. By combining precipitation put options and the total revenue function for farmers, mathematical derivations yield specific expressions for optimal trading quantities and risk hedging efficiency. The research findings show that, using an assumption of a maize price that is 3 CNY/kg, when farmers purchase around 6.22 precipitation put options they can achieve 67.9% risk hedging efficiency. This highlights the significant role of precipitation put options under specific conditions in reducing the risk of decreased maize yields due to reduced precipitation. However, in practical markets, variations in maize prices and the price change unit (λ) are inevitable. Through further analysis, this study reveals that as these factors change, the optimal trading quantity and hedging efficiency also undergo varying degrees of adjustment. The investigation lays a theoretical groundwork for the practical application and empirical validation of weather derivatives within China's agrarian sector. However, the study underscores the necessity of a holistic approach to market dynamics to refine hedging strategies. Future decision making must integrate market fluctuations, and adopting transparent pricing mechanisms is critical for enhanced risk management and the advancement of sustainable agricultural practices. [ABSTRACT FROM AUTHOR]

The vulnerability of corn yield to high temperature and insufficient rainfall in the US mid-west is widely acknowledged. The impact of extreme weather and genetic development on corn yield is less well known. One of the main reasons is that the multicollinearity in the variables can lead to confounding results. Here we model the impact of climate and genetic development by employing an elastic net regression model to address the multicollinearity issue. This allows us to develop a more robust multiple regression model with higher predictive accuracy. Using granular data for Iowa from 1981-2018, we find that corn yield is vulnerable to high mean summer temperatures particularly in July, a widening diurnal temperature range in June and dry summer conditions (due to extremely low rainfall) from June-August. We find that overall climate impact reduced average annual yield by 0.7%. We also find that genetic development which led to earlier planting dates, widening duration of the reproductive interval, higher growing degree day accumulation and larger net planted area had a beneficial impact on the Iowa corn yield during 1981-2018 resulting in an average annual yield improvement of 1.8% per annum. This provides a basis for optimism that these genetic developments and management practices will continue to adapt and improve in the future to counter the impact of climate change on corn yield. We have also modelled the impact of future climate change using the latest climate projections from the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR6). These climate projections show that the average temperature during the growing season (MayO-October) will increase by 2.4 -2.9 o C by mid-century while the average spring temperature (March and April) will increase by a relatively slower 1.9 -2.3 o C by mid-century. Additionally, climate projections show that both temperature and rainfall will also become more extreme in the future with the changes varying from spring to summer. Our results show that, just due to climate change alone in Iowa corn yield will decline between 1.4-1.7% per annum until mid-century (or 1.2-2.1% per annum until the late twenty first century).

Straw return is an effective measure to increase soil sustainability. However, few studies have examined the effects of different straw return methods on soil structure, soil organic carbon content and maize yield or the potential relationships between those variables. Therefore, we developed a field orientation experiment to study the effects of different straw return methods on soil porosity, soil aggregate stability, the soil organic carbon content and maize yield. Four treatments were established: flat no-tillage with full straw mulching (FM), ridge no-tillage with full straw mulching (LM), rotary tillage with full straw incorporation (LX), and conventional tillage without straw (CK) as the control treatment. Compared with those of the CK treatment, the soil porosities (f) in the FM, LM and LX treatments significantly increased by 6.7%, 8.8% and 7.9%, respectively; the soil aggregate destruction rates (PAD) decreased by 17.3%, 34.3% and 16.9%, respectively. In addition, the FM, LM and LX treatments effectively increased the mean mass diameters (MWDs) of the soil aggregates and the soil organic carbon content. Compared with those in the CK treatment, the three-year average yields in the FM, LM and LX treatments significantly increased by 5.2%, 7.2% and 4.1%, respectively. Moreover, the f, MWD, soil organic carbon content and corn yield were positively correlated. Our study indicates that the LM treatment was most effective in improving soil structure and increasing soil organic carbon content with corn yield.

ABSTRACT: Previous research has demonstrated the ability of isolate Pseudomonas thivervalensis SC5 to express the enzyme 1-aminocyclopropane-1-carboxylate deaminase (ACC), which regulates ethylene levels, one of the most important phytohormones in the regulation of plant growth and development. Thus, the present study evaluated the agronomic efficiency of a biological conditioner based on P. thivervalensis SC5 in the growth and productivity increases of corn in Brazil. It was found that corn was highly responsive to the inoculation of P. thivervalensis SC5, with increments ranging from 10.1 to 40.6% in the production of dry shoot biomass (DSB) compared to the control, while for grain yield the increments ranged from 9.0 to 27.8%. The increments are related to the levels and accumulations of N and P in the shoots of the plants. This suggested the participation of P. thivervalensis SC5 in mechanisms of soil modulation and nutrient acquisition. The inoculation of P. thivervalensis SC5 provided average increments in FDA hydrolysis ranging from 16.7 to 47.4% compared to the control, confirming the ability of this strain to increase the supply of nutrients to plants. Therefore, it is concluded that Pseudomonas thivervalensis SC5 participates in key mechanisms in the soil-plant system, with a consequent improvement in soil quality and other plant-related parameters.

In order to achieve profitable corn crops, implementing agricultural practices that take into account soil conservation, it is first necessary to identify and use the most effective types of tillage. Secondly, this approach must be completed with attention to the selection of productive hybrids, adapted to the pedological and climatic conditions of the cultivation area. Starting from this necessity, the objective of this paper is to present the results of the research carried out in the Constanța area in order to identify the best combination of technological factors for the cultivation of corn. The research was carried out in the years 2017-2021 within the SC Micul Agricultor SRL Company from Osmancea, Constanța County. To achieve the objectives of the research, a trifactorial experience of the 3 x 3 x 5 type was established. It was organized according to the method of subdivided plots, in three repetitions. Within it, the following factors were tested: Factor A = soil works, with graduations (a1 = plough, a2 = tiger, a3 = disk); Factor B = the hybrid, with the graduations (b1 = Mas 40 F, b2 = Dartona, b3 = P9911); Factor C = year of experimentation, with graduations (c1 = 2017 F, c2 = 2018, c3 = 2019, c4 = 2020, c5 = 2021). The best results in terms of seed germination and yield were recorded for the variant in which the basic tillage was carried out with tiger. Using the disc for basic tillage had negative effects on the percentage of plants that emerged, but also reduced seed yield, while weed infestation was higher compared to the other types of tillage. Results show that tillage was the main factor influencing production, followed by hybrid selection. Knowledge of the effects of tillage types, combined with hybrid selection is important in developing crop management practices adapted to the condition of a particular crop area, which will ensure a balance between farmers' need to increase productivity and conserve natural soil resources. [ABSTRACT FROM AUTHOR]

Some stress factors (excess temperature and lack of moisture) have a negative effect on the corn yield in the existence of climate change. This article deals with the corn growing by using adaptive technology that increases crop’s tolerance to extreme climate conditions and has a positive effect on crop yield during global warming. In order to reduce the effect of temperature and moisture stress on the corn yield, field experiments were conducted in the conditions of gray-brown soils in Samukh district. The results showed that it is possible to sow corn 10 days earlier rather than usual sowing time and this causes the temperature-sensitive flowering-fertilization stages of the plant to be less exposed to the excessive mid-summer heat and drought. The grain yield of corn ripened 15 days earlier on the raised beds rather than ordinary planting. The highest grain yield (86,1 quintals per ha) was obtained in the raised bed planting method. Straw mulching of the corn inter-rows saves water in the soil by preventing surface evaporation. [ABSTRACT FROM AUTHOR]

Purpose: More information is needed on the comparative evaluation of C sequestration and soil fertility conservation between straw and biochar application. Particularly, the effect of the co-application of straw and biochar on the quantity and quality of soil organic matter (SOM) remains unknown. Methods: A 3-year field experiment was conducted in a Mollisol, and included the following treatments: no application (CK), straw (CS) and biochar application (BC), and mixing straw with biochar (BS). C groups were identified by solid-state 13C NMR. Results: Applying straw and biochar significantly increased the contents of SOM (10.02–20.99%), labile and humic C, and corn yield (11.01–22.78%), compared to CK. BC had a more significant potential to increase SOM, C pool index, and corn yield than CS, while CS had the highest C lability index and C management index. BC improved the hydrophobicity and aromaticity, whereas CS increased the aliphatic and hydrophilic properties in SOM chemical composition. BS greatly reduced the ratios of alkyl C/O-alkyl C and aliphatic C/aromatic C. Conclusions: BC is more conducive to the stability and accumulation of SOM, while CS is beneficial to exerting soil fertility attributed to the improvement in the bioavailability and reactivity of SOM. BS could synergistically improve the biological activity and stability of SOM to some degree. Considering biochar production cost, we recommend introducing a small amount of biochar into straw returning practice as a booster to promote the stability and activity of SOM and consequent crop production, synergistically realizing a low C strategy and fertility conservation. [ABSTRACT FROM AUTHOR]

In order to explore the effect of reconstructing soil quality change after adding Pisha sandstone rich in clay mineral materials to improve sandy soil in the Mu Us Sandy Land. Long-term field monitoring experiments were conducted to study the characteristic changes of the reconstructed soil carbon and nitrogen content and corn yield with different proportions of Pisha sandstone and sand. The results showed that after 9 years of experiment, compared with the original sandy soil, in T1, T2, and T3 treatments the reconstructed soil organic matter content increased by 10, 12, and 11 times, total nitrogen content increased by 5.5, 5.4, and 3.9 times, and corn yield increased by 43.9, 105.9, and 58.5%. Especially, the corn yield of T2 and T3 treatment is greater than or equal to the corn yield of local high-yield fields. In summary, the reconstructed soil quality in different proportions has developed toward a good trend after long-term planting. T2 and T3 treatments have the best effects on reconstructing soil carbon and nitrogen accumulation reconstruction and corn yield increase. T2 and T3 treatments are recommended as the best scientific ratio for improving sandy soil with Pisha sandstone in Mu Us Sandy Land. This method has important reference and guidance for ecological remediation of desertification and degraded land.

Sustainable use of croplands is facing a challenge to maintain organic carbon (C) in soil. Pyrolyzed coal or coal char (CC) is a porous C material produced from the pyrolysis of coal containing high organic C, large surface area, and low bulk density like biochar (BC). This study evaluates corn (Zea mays L.) grain yield and selected soil properties in soil amended with CC and BC at two rates (22 and 44 Mg ha−1) with farmyard manure (FM) (66 Mg ha−1) and without FM addition. This field experiment was performed in sandy loam soil at the University of Wyoming’s Sustainable Agricultural Research and Extension Center (SAREC), Lingle, WY, USA. Two years of field study results indicated CC and BC applied at 22 Mg ha−1 with FM resulted in significantly greater average corn grain yields (13.04–13.57 Mg ha−1) compared to the no char’s treatment (11.42 Mg ha−1). Soil organic matter (SOM) content was significantly greater in the higher application rates of CC and BC than in treatments without chars. Overall, soil nitrate nitrogen (NO3-N), phosphorous (P), and potassium (K) were found significantly greater in CC and BC co-applied with FM treatments. Soil water-holding capacity (WHC) significantly improved in sandy loam soil (up to 27.6% more than the no-char treatment) at a greater concentration of char materials. This study suggests that char materials applied at a moderate rate (22 Mg ha−1) with FM can improve soil properties and crop yield.

Soil organic matter (SOM) serves as an important indicator of soil health. Soils with high SOM are associated with high crop yield under drought conditions. However, a critical question remains unanswered: is the yield-stabilizing effect of SOM attributable to inherent soil properties, such as soil texture and taxonomy? Or is it driven by dynamic soil properties that reflect the overall health of the soil? Following the Soil Health Assessment Protocol and Evaluation, we derived a soil health score (SHS; range: 0–1) from the SOM concentration by accounting for site-specific variables, including climate, texture, and soil suborder. Using county-level data of rainfed corn across the U.S. from 2000 to 2016, we found that higher SHS were associated with higher yields. During the most severe drought events, an increase of 0.5 in SHS was associated with a 1.15 ​± ​0.18 ​Mg ​ha−1 increment in corn yield, suggesting that high SHS helps to stabilize yield in drought. Interestingly, smaller but statistically significant effects of SHS on yield were found during less intensive droughts. The SOM concentration was a slightly better predictor of corn yield than the SHS. We also found similar effects of SHS on corn yield across different soil types, i.e., different textures or soil suborders, under severe drought conditions. Our results suggest that soil health is a main factor in explaining the yield benefits of SOM, while the effects of soil health were not driven by differences in soil texture or suborder. We argue that the resilience of corn yield against drought can be potentially increased by adopting agronomic practices aimed at augmenting SOM and improving overall soil health across a broad spectrum of geographical locations and site characteristics.

Sustainable management of agricultural resources is needed to meet people's increasing demands for food, fiber and energy while maintaining the quality of the environment and protecting natural resources. With the rapid growth of agriculture and the mechanization of farming, the agricultural sector has become one of the main contributors to the increase in CO2 emissions and other greenhouse gases in the world. Therefore, the aim of this study was to determine the effect, dependence and correlations of CO2 in soil with native vegetation (presence/absence, corn yield) and climatic conditions (soil temperature and moisture) during three years of measurements under different management practices in a classical conventional agroecosystem. This research contains four different treatments: control treatment (CT), dolomite/organic fertilization (DOL/OF), mineral fertilization (MF) and black fallow (BF). During the investigated period, the average overall C-CO2 flux ranged from 7.98 kg ha−1 day−1 on bare soil to 16.26 kg ha−1 day−1 on soil treated with mineral fertilization. No statistically significant difference was observed among different fertilization treatments, except in 2013 and 2015 when comparing different fertilization treatments to bare soil. In all three years, there was a positive correlation between average C-CO2 fluxes and soil temperature. Additionally, in 2013 and 2017, there was a positive correlation between average C-CO2 fluxes and soil moisture, while a negative correlation was observed in 2015. Obtained values of crop yield ranged from 0.89 t ha−1 in the control treatment (in 2015) to 14.81 t ha−1 in the treatment with mineral fertilization (in 2017). Growing global concern about the effects of climate change calls for intensive research on the carbon cycle, and these results will contribute to the understanding of carbon transformation in different crops and soil management practices. [ABSTRACT FROM AUTHOR]

Purpose Due to the urgent need for sustainable agro-industrial waste management, a field experiment was conducted to evaluate the application of biosolids as organic fertilizer in a corn cultivation crop. In addition, to achieve food security, the study aimed to assess metals concentrations in soil and maize plants and enrichment factors (EF) for soils and plants.Method Four sites with a biosolids application were studied and compared against a control. Physicochemical properties of soils and heavy metal contents were evaluated after one year of application of biosolids. Metal concentrations, average kernel yield and biomass were measured in corn plants.Results The results demonstrated that the biosolids increased the content of organic matter, nitrogen, phosphorus, and exchangeable bases in the soil. In addition, the concentration of heavy metals in soils with biosolids was higher than in soils without treatment, and the concentration of heavy metals in the corn kernels did not exceed the maximum recommended limits. However, EF values showed a considerable contamination grade due to the accumulation of metals.Conclusion Some of the physical and chemical characteristics of soil were improved by incorporating biosolids, but the metal content in the soil increased. Also, the application of biosolids increased the plant height and corn yield. Therefore, biosolids can be used as organic fertilizer sources; however, it is necessary to carry out periodic evaluations to ensure low levels of enrichment in crops and soil, thus guaranteeing the safety of biosolids as soil fertilizers.

Brackish water has been increasingly used worldwide for irrigation to relieve crop water stress. However, crop yield reductions inevitably occur under uncontrolled irrigation with saline waters, especially in areas with shallow and saline groundwater. It is essential to quantify the movement of soil water and salts in a soil-plant system and to optimize irrigation patterns with brackish water to alleviate the harm of salt stress on crop growth. Therefore, a two-year cornfield experiment was carried out during 2020–2021 to evaluate differences in soil water and salt movement under different irrigation regimes: a) brackish water irrigation with high (HB), medium (MB), and low (LB) irrigation depths, and b) freshwater irrigation with medium irrigation depths (MF). Moreover, the HYDRUS (2D/3D) model was used to evaluate soil water contents (SWC), electrical conductivities of the saturation paste extract (ECe), and fluxes, distributions, and mass balances of soil water and salts for the HB, MB, LB, and MF regimes. Meanwhile, oxygen isotope (18O) was used to calibrate and verify the simulation accuracy of the HYDRUS (2D/3D) model by determining the proportion of water and salt sources in a soil-plant system.The results showed that HYDRUS (2D/3D) could precisely capture SWC and ECe under different irrigation treatments, with the root mean square error (RMSE) of 0.004–0.017 cm3 cm−3 and 0.023–0.372 dS m−1 for SWC and ECe, respectively. The highest differences in SWCs and ECe in plots under brackish water and freshwater irrigations occurred in the 0–20 cm soil layer. The stress areas in the soil profile due to water and salt stresses under MB decreased and increased by 1.8 cm2 and 2010.0 cm2, respectively, compared with MF, accounting for 0.04% and 40.2% of the root zone. However, average root water uptake (RWU) in both years under MB decreased by 1.9% compared to MF. Additionally, RWU showed a nonlinear relationship with irrigation depth when brackish water was used for irrigation. The highest RWU occurred under MB, where the average RWU in both years increased by 7.7% and 12.4% compared with HB and LB, respectively. Therefore, the MB treatment could be recommended to increase crop yield and alleviate the freshwater shortage in agricultural production. Moreover, the findings of this study improve our understanding of the mechanisms of soil water and salt movement and groundwater contributions in a system under brackish water irrigation with different irrigation depths.

The object of the study is to investigate the suitability of some maize hybrids (Zea mays) from Seed Origin: Croatia (Hybrids Institute of Zagreb BC), Standard (NS 640 and NS 640 Hybrids). There were investigated six maize hybrids: BC 288, BC 354, BC 394, BC 408, BC 418, BC 5982, while the comparative hybrids (Standard) are NS 444, Standard NS 640. The research was conducted in two agro-climatic regions of Kosovo (in Arbnesh, on the research farm of the Agriculture Institute of Kosovo, Peja -- Dukagjini's Plain, and in Pestovo -- Kosovo's Plain, the private property of the company called "Pestova". There were investigated these parameters; the height of the stump placement on the stalk, the height of the plant, the number of trams per plant, the length of the tram, the weight of the tram, the weight of grains on the tram, grain weight, humidity, the weight of 1000 grains (Absolute P.), seed protein content (%), the content of seed fat (%). The agro-climatic and pedological data of Kosovo, compared to the yields obtained in maize culture indicate that the genetic potential of hybrids cultivated here is not exploited. The obtained results showed that there were statistically significant differences at different levels for traits investigated across the hybrids included in the plots relative to the standard (NS 444, NS 640.) and between localities. [ABSTRACT FROM AUTHOR]

The research was carried out to study the effect of basic tillage methods, means of chemicalization, and biologization on the yield of corn grain and the content of mobile phosphorus in the arable (0–25 cm) layer of typical heavy loamy medium-thick low-humus chernozem. The work was carried out in 2021–2022 in the Chechen Republic. The content of humus (according to Tyurin) in the soil of the experimental plot was 3.6%, the content of mobile phosphorus and potassium (according to Machigin) was 15 and 300 mg/kg, respectively, and the reaction of the medium was neutral (pHKCl = 7.1). In the experiment, a Pioneer 9678 corn hybrid was grown, and the predecessor was winter wheat. The scheme of the experiment included the following options: reception of the main tillage (factor A): plowing to a depth of 25–30 cm; disking by 10–15 cm; chiseling by 30–40 cm; fertilizers, biological product and green manure aftereffect (factor B): without fertilizers, biological product and green manure; N120P60K60 + green manure; biological product V417 + green manure; N120P60K60 + V417 + green manure. Disking, which ensured the formation of corn grain yield at the level of 4.75 t/ha, was the most effective in the experiment against 3.65 t/ha for plowing and 4.35 t/ha after chiselling. The content of mobile phosphorus in the soil was 21, 15, and 16 mg/kg, respectively. The use of the V417 biological product in combination with the aftereffect of green manure against the background of disking provided the highest corn yield on average for 2 years: 5.10 t/ha. The highest content of mobile phosphorus, 26 mg/kg at a balance of 60 kg/ha with an intensity of 236%, was found in the variant with disking and the use of fertilizers and a biological product in combination with the aftereffect of green manure, which was 1.5–2.0 times higher than the values of these indicators with plowing and chiselling. [ABSTRACT FROM AUTHOR]

A 3-year field experiment was conducted to determine the impact of corn residue-derived biochar on soil organic matter (SOM), soil nutrients, corn yield and partial factor productivity of synthetic fertilizer in Hetao Irrigation District, Inner Mongolia of China. Three rates of biochar, 15 (B15), 30 (B30) and 45 (B45) t ha−1, and a non-biochar control (B0) were applied to a corn field one time at the first crop growing season under film-mulched with drip-irrigation. Relative to B0, the B30 led to a significant increase in SOM at top 30 cm soil layer (15.3%) and partial factor productivity of fertilizers (12.8%) as averaged across 3 years. Amendment in B30 also increased the available nutrients in the soil (nitrogen, phosphorus and potassium), corn yield and economic benefit. In contrast, the first year showed the largest improvements for corn yield and economic benefit for B30, followed by the second year and the third year. The corn grain yield has potentially increased when the SOM and the available phosphorus were increased when compared to the available nitrogen and potassium. A single biochar amendment at the rate of 30 t ha−1 can be adequate for the corn production in 3 years under dry climatic conditions. [ABSTRACT FROM AUTHOR]

Regulating the plastic film mulching duration was a good strategy to decrease plastic residues and to avoid the stress from low soil nitrate concentration (SNC). However, few studies focused on soil nitrogen dynamic under different mulching durations, especially for the impacts of soil nitrogen loss on crop yield and comprehensive benefits have not been revealed. In this study, HYDRUS (2D/3D) model was used to evaluate the differences of SNC and NO3-N leaching (NL) under no mulching (NM), mulching for the seedling stage (PMS), mulching for the elongation stage (PME), mulching for the tasseling stage (PMT), and mulching for the entire corn growth season (PMW). Additionally, a two-year (2019–2020) field experiment was carried out to measure SNC, NL, N2O, and NH3 emissions and to calibrate and validate the model accuracy. The effect of soil nitrogen loss on the comprehensive benefits under different mulching durations was further analyzed using a comprehensive multi-objective model. The results showed that HYDRUS (2D/3D) could well capture SNC dynamic under different mulching treatments, with average the normalized root mean square error of 16.5% in the validation period. There was no apparent difference in SNC, N2O emission, NH3 emission, and NL under different mulching durations in the seedling stage. However, the corresponding difference markedly increased with corn growth and development, especially in 2019. The average SNC (0–20 cm soil depth) under NM was higher by 9.2%, 25.0%, 21.2%, and 19.4% than PMS, PME, PMT, and PMW, respectively. Nitrogen emission (N2O and NH3) showed an increase trend with the shortening of mulching duration, i.e., NM>PMS>PME >PMT >PMW, while an opposite trend was found for NL. In general, PME was found to be the optimal mulching duration with the highest comprehensive evaluation score of 1782.7. Therefore, PME can be recommended to apply in this region to promote the developments of sustainable agriculture.

Yield loss due to natural disasters, such as storms with high-speed winds and rainfall, can significantly damage standing corn (Zea mays L.) plants and yield. Using a geospatial approach, the study aimed to estimate green snap wind damage to corn and assess potential yield and economic loss in the Mississippi Delta. Midseason corn (V12–V14) snapping occurred on 8 June 2022. We recorded green snap damage in 13 fields [1.0 to 2.0 hectares (ha−1)] with low (224 kg ha−1) and high (336 kg ha−1) N rates and two different row orientations (north–south and east–west) after the damage. The results indicated no nitrogen rates or row orientation effect on green snap damage. The average yield loss could be ~29.25 kg ha−1, with every 1% increase in green snap wind damage causing significant economic loss to producers. Research methods can help scientists to estimate potential green snap yield loss due to severe winds in the larger fields. Research results can also help estimate potential yield and economic loss to assist producers and other stakeholders in decision-making to prepare for changing weather patterns and unprecedented severe windstorms in the future.

Winter cover crops can provide multiple ecosystem services but can reduce succeeding maize (Zea mays L.) yield and water-use efficiency (WUE) by depleting soil water compared with no cover crop in arid and semi-arid regions. We examined the impacts of winter cover crops (lentil [ Lens culinaris L.], oat [ Avena sativa L.], lentil/oat mixture, and no cover crop) and nitrogen fertilization rates (0, 165, and 220 kg N ha1) to succeeding maize on soil water storage at planting (SWP) and harvest (SWH) at the 0–2 m depth, evapotranspiration (ET), maize yield, and water use efficiency (WUE) from 2017 to 2022 in the Loess Plateau of China. We measured cover crop biomass and maize yield at harvest, SWP and SWH using a soil probe, and ET and WUE based on growing season precipitation and water use. Cover crop biomass yield was 59–134 % greater for oat with 220 kg N ha−1 than lentil with other N fertilization rates. The SWP was 5–22 % greater for no cover crop with 0 kg N ha−1 than other cover crops with N fertilization rates. The SWH and ET varied with cover crops, N fertilization rates, and years. Maize yield and WUE were 12–42 % greater for lentil with 220 kg N ha−1 than oat and no cover crop with other N fertilization rates. Although cover crops depleted soil water at maize planting, lentil cover crop with 220 kg N ha−1 can enhance maize yield and WUE compared with other cover crops and N fertilization rates in the Loess Plateau of China. [Display omitted] • Winter cover cropping decreased soil water content at maize planting, regardless of N rates. • Soil water content at maize harvest and ET varied with cover crops, N rates, and years. • Lentil cover crop with 220 kg N ha−1 can enhance maize yield and WUE. [ABSTRACT FROM AUTHOR]

Crop growth and yield monitoring are essential for food security and agricultural economic return prediction. Remote sensing is an efficient technique for measuring growing season crop canopies and providing information on the spatial variability of crop yields. In this study, ten vegetation indices (VIs) derived from time series PlanetScope and Sentinel-2 images were used to investigate the potential to estimate corn grain yield with different regression methods. A field-scale spatial crop yield prediction model was developed and used to produce yield maps depicting spatial variability in the field. Results from this study clearly showed that high-resolution PlanetScope satellite data could be used to detect the corn yield variability at field level, which could explain 15% more variability than Sentinel-2A data at the same spatial resolution of 10 m. Comparison of the model performance and variable importance measure between models illustrated satisfactory results for assessing corn productivity with VIs. The green chlorophyll vegetation index (GCVI) values consistently produced the highest correlations with corn yield, accounting for 72% of the observed spatial variation in corn yield. More reliable quantitative yield estimation could be made using a multi-linear stepwise regression (MSR) method with multiple VIs. Good agreement between observed and predicted yield was achieved with the coefficient of determination value being 0.81 at 86 days after seeding. The results would help farmers and decision-makers generate predicted yield maps, identify crop yield variability, and make further crop management practices timely. [ABSTRACT FROM AUTHOR]

Corn straw incorporation in soil has been regarded as an environment-friendly approach for straw utilization. However, straw incorporation has been a challenge under a cold and dry climate due to slow decomposition. This field study was to use a novel approach to incorporate corn straw into the soil during the fall season with a plastic film cover in an effort to enhance the straw degradation, soil water use efficiency, and corn growth and yield. Two-year field experiments were conducted in northeast China to investigate the effects of four treatments on soil properties and corn growth: (1) straw incorporation with film cover, (2) straw incorporation only, (3) film cover only, and (4) control. Soils and corn plants were collected during the growing season and analyzed for soil temperature and moisture, straw degradation, corn biomass, grain yield, and water use efficiency. Results indicated that straw incorporation with film cover increased grain yield by 53% as compared to straw incorporation only and by 102% to control. The straw decomposition under film cover was 20% faster, significantly higher than that of the straw incorporation treatment. In all cases, soil water content before planting, corn water uptake, and corn water use efficiency under straw incorporation with film cover were significantly higher than straw incorporation and control. Surface film cover resulted in 10-day earlier corn tasseling in compared to treatments without film cover. This field study demonstrated that straw incorporation with film cover would enhance straw degradation in soil, improve soil properties, and increase corn yield and water use efficiency, which could be potentially used as a sustainable soil management practice in northeast China. [ABSTRACT FROM AUTHOR]

【Objective】 Evapotranspiration is important not only as a component of the hydrological cycle but also for its role in modulating crop growth. The purpose of this paper is to measure the evapotranspiration of spring maize using weighing lysimeters and analyze its relationship with the yield and water use efficiency of the crop. 【Method】 A two-year experiment was conducted in Shanxi province from 2019 to 2020, and the evapotranspiration of spring maize under different water supplies was measured using weighing lysimeters. We compared four irrigation schedules: irrigating 5 times (T1), 6 times (T2), 4 times (T3) and 2 times (T4), with irrigation amount in all them being kept at 60cm. The irrigations differed only in the criteria set to resume irrigation, judged by a critical soil moisture measured in situ. Hourly changes in soil water content in all lysimeters were recorded automatically, and daily evapotranspiration was calculated using the water balance method, from which we further analyzed the relationship between yield and evapotranspiration. 【Result】 The evapotranspiration rate peaked in the middle of growing season in all treatments, and the daily evapotranspiration rate in all growing stages increased with the irrigation amount. In T2, the maximum evapotranspiration rate was 0.44 mm/h occurring at 13:00 pm, while in T4 it was reduced to 0.175 mm/h occurring at 09:00 am. The legacy of the effect of irrigation scheduling on evapotranspiration lasted a few days following the irrigation. The more frequently the crop was irrigation, the more the water would be evaporated or transpired. Most soil water was lost via evapotranspiration in the middle growth stage, i.e., 52 to 120 days after drilling the seeds; the maximum daily evapotranspiration during this period was 10.68 mm/d in 2019 and 7.27 mm/d in 2020, accounting for 75.7% and 72.9% of the total evapotranspiration in each of the two years, respectively. Model using relative evapotranspiration to predict the crop yield gave a good fitting with a correlation coefficient R2 > 0.99. Further verification of the model against data measured from 2018 to 2020 from a spring maize field in Wenyu River Basin proved the robustness of the model with a correlation coefficient R2 >0.94. 【Conclusion】 Evapotranspiration measured from the weighting lysimeter was accurate and can be used to predict yield and estimate soil water change.

Sustainable management of agricultural resources is needed to meet people’s increasing demands for food, fiber and energy while maintaining the quality of the environment and protecting natural resources. With the rapid growth of agriculture and the mechanization of farming, the agricultural sector has become one of the main contributors to the increase in CO2 emissions and other greenhouse gases in the world. Therefore, the aim of this study was to determine the effect, dependence and correlations of CO2 in soil with native vegetation (presence/absence, corn yield) and climatic conditions (soil temperature and moisture) during three years of measurements under different management practices in a classical conventional agroecosystem. This research contains four different treatments: control treatment (CT), dolomite/organic fertilization (DOL/OF), mineral fertilization (MF) and black fallow (BF). During the investigated period, the average overall C-CO2 flux ranged from 7.98 kg ha−1 day−1 on bare soil to 16.26 kg ha−1 day−1 on soil treated with mineral fertilization. No statistically significant difference was observed among different fertilization treatments, except in 2013 and 2015 when comparing different fertilization treatments to bare soil. In all three years, there was a positive correlation between average C-CO2 fluxes and soil temperature. Additionally, in 2013 and 2017, there was a positive correlation between average C-CO2 fluxes and soil moisture, while a negative correlation was observed in 2015. Obtained values of crop yield ranged from 0.89 t ha−1 in the control treatment (in 2015) to 14.81 t ha−1 in the treatment with mineral fertilization (in 2017). Growing global concern about the effects of climate change calls for intensive research on the carbon cycle, and these results will contribute to the understanding of carbon transformation in different crops and soil management practices.

Purpose Due to the urgent need for sustainable agro-industrial waste management, a field experiment was conducted to evaluate the application of biosolids as organic fertilizer in a corn cultivation crop. The study aimed to measure metals concentrations and assess enrichment factor (EF) in soil and corn plants as they are important factors to consider in order to achieve food security. Method Four sites where biosolids are applied were studied and compared against a control. Physicochemical properties of soils and heavy metal contents were evaluated after one year of application of biosolids. Metal concentrations, average kernel yield and biomass were measured in corn plants. Results The results demonstrated that the application of biosolids increased the content of organic matter, nitrogen, phosphorus, and exchangeable bases in the soil. Additionally, the concentration of heavy metals in soils with biosolids was higher than in soils without treatment, and the concentration of heavy metals in the corn kernels did not exceed the maximum recommended limits. However, EF values showed a considerable contamination level due to the accumulation of metals. Conclusion Some of the soil physical and chemical characteristics were improved by incorporating biosolids, but the metal content in the soil increased as well. Also, the application of biosolids increased the plant height and corn yield. Therefore, biosolids can be used as organic fertilizer sources; however, it is necessary to carry out periodic evaluations to ensure low levels of enrichment in crops and soil, thus guaranteeing the safety of biosolids as soil fertilizers. [ABSTRACT FROM AUTHOR]

Our objective was to assess maize fields in two growing seasons to determine the factors that affect the yield and nutritive value of maize silage produced in Brazil. Seventy‐four commercial maize fields, 49 in the first growing season (FGS) and 25 in the second (SGS), were sampled over two crop years. In each field, 12 linear meters of plants were cut by hand at 25 cm above ground. Characteristics of the field, plants, and their components (stalk, leaves, husk, cob, and grains) were evaluated. Farmers were interviewed regarding the crop management practices applied. Chopped maize forage was dried to assess its chemical composition, in vitro dry matter digestibility, and in vitro fibre digestibility. Descriptive statistics was carried out for agronomic and nutritional variables. To determine the factors that affected yield and nutritive value in maize fields, artificial neural networks were used. The dry matter yield (DMY), NDF concentration, starch concentration, NDF digestibility, and DM digestibility were chosen as response variables. Then, the top 10 main parameters were used to explain the results. Overall, the association between grain and stover yield maximized DMY. Plant population (plants/ha) and plant maturity were also important to explain yield. Grain depth and number of grains per row were the two most important parameters linked to genetic traits. Plant maturity was decisive in altering the nutritive value of forage maize. Maize grown in the FGS had both greater yield and nutritive value than maize in the SGS. [ABSTRACT FROM AUTHOR]

Food security has been one of the greatest global concerns facing the current complicated situation. Among these, the impact of climate change on agricultural production is dynamic over time and space, making it a major challenge to food security. Taking the U.S. Corn Belt as an example, we introduce a geographically and temporally weighted regression (GTWR) model that can handle both temporal and spatial non-stationarity in the relationship between corn yield and meteorological variables. With a high fitting performance (adjusted R2 at 0.79), the GTWR model generates spatiotemporally varying coefficients to effectively capture the spatiotemporal heterogeneity without requiring completion of the unbalanced data. This model makes it possible to retain original data to the maximum possible extent and to estimate the results more reliably and realistically. Our regression results showed that climate change had a positive effect on corn yield over the past 40 years, from 1981 to 2020, with temperature having a stronger effect than precipitation. Furthermore, a fuzzy c-means algorithm was used to cluster regions based on spatiotemporally changing trends. We found that the production potential of regions at high latitudes was higher than that of regions at low latitudes, suggesting that the center of productive regions may migrate northward in the future. [ABSTRACT FROM AUTHOR]

Nitrogen (N) fertilizer recommendations based on yield goals are common and do not consider variability in soil N supply between fields. Nitrogen transformations in soils are dynamic and may vary widely among different soils, climates, cropping systems, and management practices, making it difficult to provide general N recommendation rates for a region, state, or even a county. To optimize N fertilization rates for corn (Zea mays L.), eight field trials were conducted on different fields at the Edisto Research and Education Center of Clemson University in 2018–2021. The soils varied in pH, inorganic N, management practices (irrigate, dryland, cover, and no-cover crop), and climatic conditions (temperature and precipitation). Six nitrogen fertilizer rate treatments were used during 2018 and 2019, eight in 2020, and five in 2021 trials. Test sites were different in each year except in 2021 in which trials were conducted on the same site but were differentiated by multi-species and no-cover crop treatments. Nitrogen fertilizer was applied as a complete one-time dose in all trials in 2018 and 2021 and in several splits in 2019 and 2020. The corn yields generally increased with N fertilization rates; however, a strong variation of up to 4–11 Mg ha−1 existed at each N level among different fields. Based on yield responses, the eight field trials were divided into two groups: low-yielding and high-yielding sites. The low-yielding sites on average produced 3.8 Mg ha−1 of corn, which was 137% less than the corn harvested from high-yielding sites (9.0 Mg ha−1). The agronomic N use efficiency (AgNUE) in high-yielding sites was almost double (32.68 kg kg−1 N) compared to low-yielding sites (17.16 kg kg−1 N), and the differences were even wider for partial factor productivity of N (PFPN). The economic optimum N rate (EONR) remained below 300 kg N ha−1 for all sites with no marked difference among sites. However, relative yield (ratio of corn yield in unfertilized control to the N level giving the highest yield) was comparatively lower in low-yielding sites (29.45%). Baseline inorganic N, pH, and precipitation were identified as the major factors controlling corn yield responses to N fertilization. The yield variations driven by several factors make N management challenging, indicating the need for site-specific N management for corn in the southeast United States.

Crop yield prediction before the harvest is crucial for food security, grain trade, and policy making. Previously, several machine learning methods have been applied to predict crop yield using different types of variables. In this study, we propose using the Geographically Weighted Random Forest Regression (GWRFR) approach to improve crop yield prediction at the county level in the US Corn Belt. We trained the GWRFR and five other popular machine learning algorithms (Multiple Linear Regression (MLR), Partial Least Square Regression (PLSR), Support Vector Regression (SVR), Decision Tree Regression (DTR), and Random Forest Regression (RFR)) with the following different sets of features: (1) full length features; (2) vegetation indices; (3) gross primary production (GPP); (4) climate data; and (5) soil data. We compared the results of the GWRFR with those of the other five models. The results show that the GWRFR with full length features (R2 = 0.90 and RMSE = 0.764 MT/ha) outperforms other machine learning algorithms. For individual categories of features such as GPP, vegetation indices, climate, and soil features, the GWRFR also outperforms other models. The Moran's I value of the residuals generated by GWRFR is smaller than that of other models, which shows that GWRFR can better address the spatial non-stationarity issue. The proposed method in this article can also be potentially used to improve yield prediction for other types of crops in other regions. [ABSTRACT FROM AUTHOR]

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White clover (Trifolium repens L.) and ryegrass (Lolium multiflorum L.) are widely used cover crops. This experiment investigated the potential of white clover (WC), ryegrass (RG), and fallow (FL) to inhibit the growth of weeds and the effect of their residue return to the field on subsequent crops in a cover crop-corn rotation system. Furthermore, we designed pot experiments to guide the scientific application of WC and RG. The results showed that the FL treatment had the highest mean weed biomass in two years (11.99 t ha−1) and the RG treatment recorded the lowest mean weed biomass in two years (2.04 t ha−1) as its early growth rate and aerial root cover. The combination of rotary tillage (RT) and WC recorded the highest total corn yield in two years (20.20 t ha−1) and an increase of 2.84% in the two-year average biomass of weeds compared to RT-FL. Compared to RT-FL, RT-RG treatments inhibited weed invasion by an average of 73%, but corn yield was reduced by 3.25%. Straw and soil ratios above 6:100 for RG resulted in stunted corn growth, including a reduction in fresh weight and chlorophyll content, and impaired photosynthesis, but this effect was not evident in WC treatment. From an ecological point of view, this study recommends RT-RG as a pre-crop for corn to reduce herbicide use. [ABSTRACT FROM AUTHOR]

During our soil-specific drought sensitivity research, an aim of ours was to ascertain how drought, a stress factor caused by the lack of precipitation, affects soil fertility. We used the five-year-long (1985–1989) soil and corn yield data of the National Pedological and Crop Production Database (NPCPD). We assigned the annual Pálfai Drought Index (PaDI) to the annual corn yield data of the NPCPD in order to identify drought-free corn yields and production areas. We determined the drought sensitivity of soils by comparing drought-free and annual yields. Based on the results of our statistical analyses, we created a seven-point drought sensitivity scale of soil types, based on which we produced a national soil-specific drought sensitivity index map. Our results may provide a good starting point for constructing large-scale (1: 10,000) climate sensitivity soil maps of agricultural lands, which can assist with soil-specific crop production that also adapts to climate change.