Rainfed Maize Yield Research Articles

Climate Change Impact on Rain-Fed Maize Yield Cultivated with Small-Scale Landowners in Wolaita Zone, Ethiopia

Ethiopia is a country that heavily relies on rainfall-aided cultivation which is carried out by small-scale landowners, leaving it very vulnerable to climate change and fluctuation. The primary goal of this research is to investigate how climate change affects maize yield in Wolaita zone of Ethiopia. The authors were employed a linear regression method to evaluate the relationship between climate parameters and maize yield. Sen's slope magnitude estimator and the Mann-Kendal trend test were used to assess the significance of climate change. The outcome demonstrated that the temperature extreme indices of warm days and the length of warm days were considerably higher by 37.5% and 3.7% of days per year, however, cold days and cold spells were significantly decreased. Over the 1981-2021 periods, there was a significant upward pattern in TXx and TNn at an average of 0.033°C and 0.034°C. There was a considerable decline of 2.3% in the simple daily precipitation intensity index and 33% decreased in extremely heavy precipitation, respectively. The correlation analysis's findings indicated that growing period precipitation and maize outputs were positively correlated, but negatively correlated with maximum and minimum temperatures. Extreme temperature and precipitation were more explained a maize yield than average climate patterns. 12.4%, 14.76%, 13.08%, and 7.95% of maize output variability was attributed by the growing season mean climate conditions, which include precipitation, mean, minimum, and maximum temperature. The variability of maize output was explained by combined impact of precipitation and temperature extremes were 67.7% and 45.0%, respectively. Therefore, livelihood diversification and relevant policy formulation are suggested to adapt inevitable climate change by implementing irrigation and resistant varieties to improve maize yield production.

Further adoption of conservation tillage can increase maize yields in the western US Corn Belt

Conservation tillage can reduce soil erosion, increase soil health, and decrease labor and fuel input costs. Despite these benefits, potential yield impacts remain an important concern for farmers considering adoption. Previous research suggests that conservation tillage is likely to have the largest yield benefits in more arid conditions, but a lack of field-level analyses across climatic, management and soil conditions limits confidence in such predictions. Satellite imagery provides the opportunity to monitor agricultural lands at sub-field resolution across large spatial scales and wide environmental gradients. Here we investigate the maize yield impacts of conservation tillage in the semi-arid western US Corn Belt, using sub-field resolution datasets on tillage practices and crop yields derived from satellite data spanning four states (Nebraska, Kansas, South Dakota, and North Dakota) between 2008 and 2020. On these datasets, we estimate heterogenous yield outcomes for several thousand maize fields across gradients in climate, soil quality and irrigation status by using a causal forests analysis, an adaptation of the random forests machine-learning algorithm for causal inference on observational data. We find that long-term adoption of conservation tillage increased rainfed maize yields by an average of 9.9% in the region. Impacts on irrigated yields were small and not statistically significant. These results, along with an analysis of variables related to greater than average yield benefits, indicate that improved water infiltration and retention are the primary reasons for conservation tillage benefits. Despite yield benefits, many fields estimated to see increased yields under long term low till have not adopted the practice. Therefore, we identify specific counties likely to benefit most from increased levels of adoption. Our results strengthen the understanding of the impacts of conservation agriculture on crop yields and help define environments and counties most likely to benefit from conservation tillage.

Suitable organic fertilizer substitution ration stabilizes rainfed maize yields and reduces gaseous nitrogen loss in the Loess Plateau, China

The application of organic fertilizers has become an increasingly popular substitution in maize production to reduce gaseous nitrogen (N) loss and soil degradation caused by inorganic fertilizers. Organic fertilizer plays a key role in improving soil quality and stabilizing maize yields, but studies that refine different substitution rates remain poorly documented. A field study was carried out in 2021 and 2022 based on a long-term trial initiated in 2016. The experiment included five organic fertilizer N substitution rates with equal input of 200 kg N ha–1: 0% organic fertilizer (T1, 100% inorganic fertilizer), 50.0% organic+50.0% inorganic fertilizer (T2), 37.5% organic+62.5% inorganic fertilizer (T3), 25.0% organic+75.0% inorganic fertilizer (T4), 12.5% organic+87.5% inorganic fertilizer (T5), and no fertilizer control (T6). The average result of two years showed that T3 and T1 had the highest grain yield and biomass, respectively, and there was no significant difference between T1 and T3. Compared with T1, 12.5, 25.0, 37.5, and 50.0% substitution rates (T5, T4, T3, and T2) significantly reduced total nitrogen loss (NH3、N2O) by 8.3, 16.1, 18.7, and 27.0%, respectively. Nitrogen use efficiency (NUE) was higher in T5, T3, and T1, and there was no significant difference among them. The organic fertilizer substitution directly reduced NH3 volatilization and N2O emission from farmland by lowering ammonium nitrogen and alkali-dissolved N content and by increasing soil moisture. These substitution treatments reduced N2O emissions indirectly by regulating the abundance of AOB and nirK-harboring genes by promoting soil moisture. The 37.5% of organic fertilizer substitution reduces NH3 volatilization and N2O emission from farmland by decreasing ammonium nitrogen and alkali-dissolved N content and increasing moisture which negatively regulate the abundance of AOB and nirK-harboring genes to reduce N2O emissions indirectly in rainfed maize fields on the Loess Plateau of China.

Strip-Till Farming: Combining Controlled-Release Blended Fertilizer to Enhance Rainfed Maize Yield While Reducing Greenhouse Gas Emissions

The two major concerns of sustainable agriculture are safeguarding food security and reducing greenhouse gas emissions. Studies on the performance of strip-till with controlled-release blended fertilizer on rainfed maize grain yield, greenhouse gas emissions, and net ecosystem economic budget are scarce in the hilly region of northeast China. In this study, the differences between strip-till (RST) and conventional ridge cropping (CP), straw off-field no-tillage (NT), and no-tillage with straw mulching (RNT) were comparatively investigated in the conventional fertilizer (Sd) mode. And meanwhile, four fertilization modes were also set up under strip-till (RST): conventional fertilization (Sd), controlled-release nitrogen fertilizer blended with normal urea 3:7 (30%Cr), controlled-release nitrogen fertilizer blended with normal urea 5:5 (50%Cr), and no-nitrogen fertilization. We analyzed maize yield, greenhouse gas emissions (GHG), greenhouse gas intensity (GHGI), net income and net ecosystem economic budget (NEEB) for different treatments. The results showed that, under conventional fertilizer (Sd) mode, the maize yield of RST increased by 4.2%, 6.0% and 7.2% compared with NT, CP and RNT and the net income increased by 7.0%, 9.7% and 10.0%, respectively. Compared with CP and NT, although RST increased CO2 and N2O emissions, the GHGI of RST was not significantly different from CP and NT, and was 8.0% lower than that of RNT. The NEEB of RST increased by 6.8%, 9.7% and 11.0%, respectively, compared with NT, CP and RNT. Under strip-till, compared with 30%Cr and Sd, the yield of 50%Cr increased by 4.0% and 9.2% and the net income increased by 3.5% and 6.9%, respectively. There was no significant difference in GHGI between 50%Cr and 30%Cr, and 50%Cr decreased by 10.4% compared with Sd. The NEEB of 50%Cr increased by 3.8% and 7.4% compared to 30%Cr and Sd. Strip-till combines controlled-release nitrogen fertilizer blended with normal urea 5:5 (50%Cr) and can be applied as a sustainable strategy to improve the economic efficiency of maize and reduce environmental costs in the hilly region of northeast China.

Nitrogen application and soil mulching improve grain yield of rainfed maize by optimizing source-sink relationship and grain filling process on the Loess Plateau of China

The kernel weight of maize (Zea mays L.) is largely regulated by the source-sink relationship during the grain-filling period. The source-sink coordination is the key to high grain yield, which is affected by many management practices, such as nitrogen application and soil mulching. Previous studies have mainly focused on qualitative descriptions of maize source-sink relationships, but the quantitative analysis of maize source-sink relationships under various nitrogen application rates and soil mulching practices have been poorly explored. A three-season (2020–2022) experiment was conducted on rainfed maize on the Loess Plateau of China, with two nitrogen rates (N0, 0 kg N ha–1; N180, 180 kg N ha–1) and three mulching practices (NM, flat cultivation with no mulching; SM, flat cultivation with full straw mulching; RF, ridge-furrow cultivation with transparent film mulching on the ridge). The results showed that compared with N0, N180 increased the maximum leaf area index (LAImax) by 29.6%, leaf area duration (LAD) by 31.4%, maximum 100-kernel weight (HGWmax) by 12.5%, source growth (SG) by 34.2%, sink capacity (SC) by 49.8%, source supply rate (SUR) by 23.4%, sink growth rate (SGR) by 50.7%, and finally increased grain yield by 37.2%. Compared with NM, SM and RF increased LAImax by 8.5% and 25.6%, LAD by 10.6% and 28.0%, HGWmax by 5.5% and 10.3%, SG by 13.6% and 41.6%, SC by 16.4% and by 35.5%, SUR by 8.7% and 35.5%, SGR by 16.3% and 37.1%, and finally increased grain yield by 8.2% and 26.7%, respectively. The structural equation modeling indicated that LAD mainly affected SG, and SG significantly affected source-sink relationships and grain-filling parameters, which mainly affected 100-kernel weight and the number of grains per spike, respectively. The number of grains per spike had a greater impact on the sink capacity than 100-kernel weight. In conclusion, nitrogen application and soil mulching enhanced grain yield of rainfed maize by increasing leaf source size, promoting source growth and grain filling, improving kernel number and optimizing source-sink relationships on the Loess Plateau of China. This study provides a better understanding of source-sink relationships for optimizing maize management practices and identifying key processes in modeling maize yield.

Optimized Farmland Mulching Improves Rainfed Maize Productivity by Regulating Soil Temperature and Phenology on the Loess Plateau in China

Owing to global warming, continuously increasing the grain yield of rainfed maize is challenging on the Loess Plateau in China. Plastic film mulching has been extensively utilized in dryland agriculture on the Loess Plateau. However, higher topsoil temperatures under film mulch caused rainfed-maize premature senescence and yield loss. Here, we aimed to explore the influence of topsoil temperature driven by novel double mulching patterns on rainfed maize productivity based on the excellent moisture conservation function of plastic film. A maize field experiment was conducted in two different areas, namely Changwu, a typical semi-arid area, and Yangling, a dry semi-humid area. The experiment followed a randomized block design with three replications. Five flat-planting practices were examined in 2021 and 2022: (1) bare land (CK), (2) transparent film mulching (PFM), (3) black film mulching (BFM), (4) double mulching of PFM with a black polyethylene net (PFM + BN), and (5) double mulching of PFM with whole maize stalks (PFM + ST). Soil hydrothermal conditions, maize growth dynamics, grain yield, water use efficiency (WUE), and economic returns were quantified under different mulching practices. Under double mulching treatments, topsoil temperatures were lower than PFM by 1.7–2.0 °C at the two sites (p < 0.05), whereas BFM was slightly lower than that of PFM by 0.6–0.7 °C at Yangling (p > 0.05). The average growth period for maize under double mulching was longer than that under PFM by 8–11 days at the two sites. Double mulching treatments significantly improved the leaf area index (LAI), chlorophyll relative content (SPAD), and aboveground biomass compared to CK and PFM during the late growth stage. Compared with PFM, average grain yield increased by 14.93%, 18.46%, and 16.45% in Changwu (p < 0.05) under BFM, PFM + BN, and PFM + ST, respectively, and by 2.71%, 24.55%, and 20.38% in Yangling. The corresponding WUEs also increased. Additionally, net income under BFM was higher than that under other treatments, and there were no significant (p > 0.05) differences between PFM + ST and BFM in Changwu. However, PFM + ST in net income averaged 10.72–52.22% higher than other treatments, and its output value was 19.51% higher in Yangling. In summary, smallholder farmers can adopt PFM + ST to improve rainfed-maize productivity in the Loess Plateau in China.

Effects of conservation practices on rainfed maize yield, furrow water infiltration, and soil moisture for surface sealing loam soils in the Yazoo‐Mississippi Delta

AbstractDecades of intense tillage have created the problem of surface sealing in loam soils across the Mid‐South United States and beyond. These soils exhibit low organic matter, poor aggregate stability, and ultimately low infiltration rates that decrease rainfed crop productivity and increase irrigation water demand. This research quantified the effects of soil management practices on rainfed maize (Zea mays L.) yield, furrow water infiltration, and soil moisture in Commerce very fine sandy loam and silt loam near Stoneville, MS. The six treatments included conventional tillage (CT), cereal rye (CR; Secale cereale L.), furrow diking (FD), no‐till (NT), polyacrylamide (PAM), and subsoiling (SS). No other treatment achieved a significantly higher maize grain yield than the CT control treatment in both years consistently. Single‐ring infiltrometer results indicated no significant differences among CT, CR, PAM, and SS in 2022 and between CT and NT in 2021. Neutron attenuation found that total soil water within the top 1 m was not significantly different among CT, FD, and SS on any of the eight measurement dates throughout the 2022 maize reproductive period. However, soil moisture was numerically lower for FD in the late reproductive stages. These findings suggest that environmental factors and other agronomic operations may counteract conservation practices, limiting their effectiveness at reducing irrigation requirements to mitigate groundwater depletion in the Mississippi River Valley Alluvial Aquifer.

Ridge-furrow planting with black film mulching increases rainfed summer maize production by improving resources utilization on the Loess Plateau of China

Soil mulching has been widely used to improve crop productivity around the world, but how various mulching practices affect soil hydrothermal conditions, water-temperature-radiation utilization and finally grain yield of rainfed maize has been poorly understood. A two-season field experiment was conducted on rainfed summer maize in 2021 and 2022 on the Loess Plateau of China, with six soil mulching practices: flat planting with non-mulching (FPNM), flat planting with full straw mulching (FPSM), flat planting with full black film mulching (FPBF), flat planting with full transparent film mulching (FPTF), ridge-furrow planting with black film mulching on the ridge (RFBF) and ridge-furrow planting with transparent film mulching on the ridge (RFTF). The results showed that compared with the traditional FPNM, the five mulching treatments (FPSM, FPBF, FPTF, RFBF and RFTF) greatly regulated root-zone soil hydrothermal conditions and resulted in obvious soil drying-wetting alternation, which significantly changed the daytime average root-zone soil temperature in the 0 – 25 cm soil layer (by − 1.1 ℃, − 1.9 ℃, + 2.7 ℃, − 1.6℃ and + 0.8 ℃, respectively) and significantly reduced crop evapotranspiration. The five mulching treatments promoted the root growth, leaf area index and canopy light interception rate due to the improved soil water and/or temperature conditions. The structural equation modeling indicated that soil hydrothermal condition and water-temperature-radiation use efficiency could directly or indirectly explain 98% of the grain yield variation under various soil mulching practices; radiation use efficiency (RUE) determined maize production in the water-sufficient year (2021), whereas maize production was mainly determined by crop water productivity (WP) in the water-limited year (2022). The RFBF increased maize production most, followed by RFTF. Compared with FPNM, RFBF increased leaf area index by 45.4%, canopy light interception rate by 19.1%, aboveground biomass by 68.8%, 1000-grain weight by 15.1%, grain yield by 58.6%, WP by 71.8%, thermal time use efficiency by 64.6% and RUE by 30.5%. In conclusion, RFBF optimized the root-zone soil hydrothermal conditions for root growth, which in turn promoted aboveground growth and water-temperature-radiation use efficiency, and finally improved the gain yield of rainfed summer maize on the Loess Plateau of China. Therefore, RFBF was considered as a promising agricultural practice to improve rain-fed summer maize production and resource utilization efficiency on the Loess Plateau of China.

Climate Change Impacts on Rainfed Maize Yields in Kansas: Statistical vs. Process-Based Models

The changing climate and the projected increase in the variability and frequency of extreme events make accurate predictions of crop yield critically important for addressing emerging challenges to food security. Accurate and timely crop yield predictions offer invaluable insights to agronomists, producers, and decision-makers. Even without considering climate change, several factors including the environment, management, genetics, and their complex interactions make such predictions formidably challenging. This study introduced a statistical-based multiple linear regression (MLR) model for the forecasting of rainfed maize yields in Kansas. The model’s performance is assessed by comparing its predictions with those generated using the Decision Support System for Agrotechnology Transfer (DSSAT), a process-based model. This evaluated the impact of synthetic climate change scenarios of 1 and 2 °C temperature rises on maize yield predictions. For analysis, 40 years of historic weather, soil, and crop management data were collected and converted to model-compatible formats to simulate and compare maize yield using both models. The MLR model’s predicted yields (r = 0.93) had a stronger association with observed yields than the DSSAT’s simulated yields (r = 0.70). A climate change impact analysis showed that the DSSAT predicted an 8.7% reduction in rainfed maize yield for a 1 °C temperature rise and an 18.3% reduction for a 2 °C rise. The MLR model predicted a nearly 6% reduction in both scenarios. Due to the extreme heat effect, the predicted impacts under uniform climate change scenarios were considerably more severe for the process-based model than for the statistical-based model.

Long-term effects of plastic mulching on soil structure, organic carbon and yield of rainfed maize

Long-term effects of plastic mulching on soil structure, organic carbon and yield of rainfed maize

Assessment of Climate Change Impact and Adaptation Strategies for Rainfed Maize (Zea mays L.)

The study was performed to assess the impact of climate change on spatiotemporal changes in rainfed maize yield. Climate projections data of MIROC-ESM-CHEM model from CMIP6 was used for future climatic scenarios in the maize growing areas of Dindigul and Perambalur districts of Tamil Nadu. The DSSAT model was used to simulate maize yield and evaluate adaptation strategies for base period (1991-2020), the mid (2040-2069) and end centuries (2070-2099) under SSP245 and SSP585 scenarios. The simulation finding shows that, in all scenarios maize yield declined in both Dindigul (7 to 9% and 11 to 12%) and Perambalur (6 to 9% and 11 to 13%) during mid and end centuries respectively from the base period (1991-2020). Following the adaptation strategies such as delayed sowing, the yield was increased in both Dindigul (5 to 6% and 4 to 5%) and Perambalur (4 to 5% and 5 to 6%) with respect to normal sowing date. The results of this study would help in developing adaptation strategies for minimizing the adverse effects of the projected climate in maize-growing districts of Tamil Nadu.

Effect of tillage practices, mulching and intercropping on rainfed maize (Zea mays) in foothill of Shivaliks, Jammu, Jammu and Kashmir

A field experiment was conducted during the rainy (kharif) season of 2017 and 2018 at Advanced Centre for Rainfed Agriculture, Sher-e-Kashmir University of Agricultural Sciences and Technology, Jammu, Dhianasr, Jammu and Kashmir to evaluate the effect of tillage, residue mulching and intercropping on nutrients, growth and yield of rainfed maize (Zea mays L.). The experiment was laid out in a randomized block design with 3 replications. The treatments included conventional tillage (CT), CT+ mulching (CTm), CT + intercropping with mash [Vigna mungo (L.) Hepper] (CTi), minimum tillage (MT), MT + mulching (MTm), MT + intercropping with mash (MTi), MT + residue (MTr), zero tillage (ZT), ZT + mulching (ZTm) and ZT + residue (ZTr). The highest grain yield (3.01 t/ha) and yield attributes were recorded with minimum tillage + residue incorporation (MTr). However, the grain yield recorded in all the treatments were at par when equivalent yield of intercrop was taken. The intercropping of mash in maize sown by conventional tillage resulted in 34.3% reduction in grain yield of maize as compared to conventional tillage. The stover yield ranged from 5.65 to 7.93 t/ha and harvest index ranged from 23.8 to 32.5% in all the treatments was at par.

Response of Grain Yield to Planting Density and Maize Hybrid Selection in High Latitude China—A Multisource Data Analysis

Identifying the relationships between the yield of rainfed maize and planting densities as well as the hybrids used is crucial for ensuring the sustainable development of the grain industry in high latitude China. In this study, we collected 108 grain yield date points from our multiyear (2017–2020) field experiments and combined 213 data points collected from 21 published papers to appraise the impact of planting density and hybrids on maize yield. It was found that grain yield forms a curvilinear relationship with plant density as it increased from 22,500 to 112,500 plants ha−1. The optimum plant density (OPD) was determined to be 72500 plants ha−1, with a maximum maize grain yield of 10.56 Mg ha−1. The interannual variability in grain yields among hybrids with different planting densities was mainly due to the differences in dry matter (DM), especially post-silking. Grain yields increased significantly with a rise in the proportion of post-silking DM to DM at maturity. In addition, both the collected literature and our field experiments showed that the OPD was positively correlated with solar radiation accumulated during the maize growth period and with each hybrid’s year of release. This study suggests that increasing plant density and selecting new hybrids with suitable growth periods are effective approaches for increasing grain yield in high latitude China.

Climate Indices and Their Impact on Maize Yield in Veracruz, Mexico

The State of Veracruz (Mexico) is highly vulnerable to climate change. Therefore, it is necessary to identify and analyze local climate extreme trends and explore potential relationships between climate indices and maize. The objectives of this research were (1) to describe recent trends of climate indices (1979–2018) and (2) to compare these climate indices with maize yields produced in Veracruz, Mexico, under rainfed conditions. The methodology calculated and analyzed the sector-specific climate indices (Rx5day, PRCPTOT, SPI6, R20mm, TXx, TNn, TXgt50p, and TXge35) in 18 observation sites using Climpact. Climate indices were calculated over the spring-summer agricultural cycle and correlated with rainfed maize yields. Results show increasing trends for Rx5day, TXx, TXgt50p, and TXge35 indices in 65%, 56%, 89%, and 67% of the analyzed sites, respectively, whereas decreasing trends in PRCPTOT and R20mm indices were detected in 59% and 47% of the sites. Significant correlations (p < 0.05) between climate indices and maize yield were found in eight municipalities, of which 62% were positive. In conclusion, extreme temperature and precipitation local events are increasing in frequency, duration, and intensity, and depending on the site’s local climate, these might positively or negatively impact maize yields.

Impact of Spatial Soil Variability on Rainfed Maize Yield in Kansas under a Changing Climate

As the climate changes, a growing demand exists to identify and manage spatial variation in crop yield to ensure global food security. This study assesses spatial soil variability and its impact on maize yield under a future climate in eastern Kansas’ top ten maize-producing counties. A cropping system model, CERES-Maize of Decision Support System for Agrotechnology Transfer (DSSAT) was calibrated using observed maize yield. To account for the spatial variability of soils, the gSSURGO soil database was used. The model was run for a baseline and future climate change scenarios under two Representative Concentration Pathways (RCP4.5 and RCP8.5) to assess the impact of future climate change on rainfed maize yield. The simulation results showed that maize yield was impacted by spatial soil variability, and that using spatially distributed soils produces a better simulation of yield as compared to using the most dominant soil in a county. The projected increased temperature and lower precipitation patterns during the maize growing season resulted in a higher yield loss. Climate change scenarios projected 28% and 45% higher yield loss under RCP4.5 and RCP8.5 at the end of the century, respectively. The results indicate the uncertainties of growing maize in our study region under the changing climate, emphasizing the need for developing strategies to sustain maize production in the region.

Long-term agro-hydrological simulations of soil water dynamic and maize yield in a tillage chronosequence under subtropical climate conditions

Process-based modeling addressing soil tillage effect on soil hydraulic properties is scarce since most assessments focus on static parameters (e.g., bulk density, penetration resistance, total porosity, etc.). Our goals were to (i) simulate the long-term soil water balance and the yield of rainfed maize under a tillage chronosequence, (ii) analyze the duration of the positive impacts of chiseling tillage effects on soil hydraulic properties, and (iii) compare the results produced by the agro-hydrological modeling with the static soil physical properties from earlier studies. A chisel tillage chronosequence was established in an Oxisol, i.e., at the sampling time the soil was under no-till (NT) for 0, 6, 12, 18, and 24 months after chiseling, and under 12 years continuous NT (control). Maize root length density (RLD) and soil hydraulic properties were determined for each treatment (four replications and three soil depths). Soil tillage effect on soil-water regime and maize yield were evaluated using the SWAP model integrated with the crop growth module WOFOST. The simulated scenarios included long-term (30 years) rainfed maize growth in each treatment. The simulation detected significant (P < 0.05) soil tillage effects on crop yield and soil water balance components. Actual crop transpiration (Tact) was promoted in the first crop season after chiseling, increasing crop yield by 14%, but this positive effect of chiseling lasted only one cropping season. Fresh chiseled soil increased Tact, while the 24-month chiseling interval generated larger water loss through runoff. RLD and soil hydraulic properties stratification within soil profile generated different patterns of soil drought stress response during the crop season. Both agro-hydrological modeling (dynamic approach) and individual soil physical properties assessment (static approach) from earlier studies found similar ephemeral positive effects of chiseling on soil physical properties. Nevertheless, agro-hydrological simulations were more effective in detecting soil functioning changes due to agricultural practices. Thus, it is crucial to integrate dynamic and static soil physical assessment when analyzing tillage effects on soil physical properties related to mass and energy transfer in cropped soils.

Impact of conservation agriculture practices on soil physical properties and yield of rainfed maize

Impact of conservation agriculture practices on soil physical properties and yield of rainfed maize

Plant Population and Row Spacing Affects Growth and Yield of Rainfed Maize in Semi-arid Environments.

Increased tolerance to competition for soil resources of modern maize (Zea mays L.) hybrids increases soil resource use efficiency and yield. Yet little information is available on the relationship between maize population density and yield under no-tillage in semi-arid environments. A 2-year field trial was conducted in South Africa during the 2017/2018 (Season 1) and 2018/2019 (Season 2) production seasons to evaluate growth and water use productivity of rainfed maize established at seven diverse plant population (20,000–60,000 plants ha−1) and row spacing (0.52 and 0.76 m) configurations. In Season 1, light interception was 6.8% greater at 0.76 m row spacing compared to 0.52 m row spacing (p < 0.05). In Season 2, despite dry and hot growing conditions, a well-developed leaf canopy cover was present at 0.52 m row spacing indicating a 10.4% greater intercepted photosynthetically active radiation (IPAR) compared to 0.76 m row spacing. In Season 1, with more uniform rainfall distribution, no biomass or yield benefits were found with increased plant population, except at 50,000 plants ha−1 at 0.76 m row spacing. In Season 2, plant populations at 0.76 m row spacing out-yielded any given plant population at 0.52 m row spacing. The optimal plant population and row spacing will ultimately be a compromise between obtaining high maize grain yield and minimizing the potential for crop failure in semi-arid environments.

Assessment of Maize Drought Risk in Midwestern Jilin Province: A Comparative Analysis of TOPSIS and VIKOR Models

Drought is a major natural disaster that causes a reduction in rain-fed maize yield. Agricultural drought risk assessment is conducive to improving regional disaster management ability, thereby reducing food security risks and economic losses. Considering the complexity of risk assessment research, an increasing number of researchers are focusing on the multiple-criteria decision-making (MCDM) method. However, the applicability of the MCDM method to agro-meteorological disaster risk assessments is not clear. Therefore, this study comprehensively evaluated hazard, exposure, vulnerability, and emergency response and recovery capability using the TOPSIS and VIKOR models to generate a maize drought risk map in mid-western Jilin Province and ranked the drought risk of each county. The results showed that: (1) maize drought risk in the middle and west of Jilin province showed an increasing trend. Spatially, the risk diminished from west to east. The drought risks faced by Tongyu, Changchun, and Dehui were more severe; (2) the evaluation results of the two models were verified using the yield reduction rate. The VIKOR model was found to be more suitable for agrometeorological drought risk assessments; (3) according to the damage degree of drought disaster to maize, the cluster analysis method was used to divide the study area into three sub-regions: safe, moderate drought, and severe drought. Combined with the characteristics of different regions, suggestions on disaster prevention and mitigation are proposed. The results of this study can provide a basis for formulating strategies to alleviate drought, reduce losses, and ensure the sustainable development of agriculture.

Dominant sources of uncertainty in simulating maize adaptation under future climate scenarios in China

CONTEXTThe potential of climate adaptation has been widely investigated with a climate-crop modeling approach. Although different sources of uncertainty in projected crop yields have been quantified in climate change impact assessments, uncertainty in simulating the crop adaptation to future climate has not been fully assessed. OBJECTIVEThe objective of this study was to determine the uncertainty in simulating maize adaptation to future climate change with two adaptation options (adjusting planting date and shifting cultivars) at four contrasting sites across China's Maize Belt. METHODSMaize yield with adaptation was simulated using three crop models (APSIM, DSSAT-CERES, and STICS) driven by 22 global climate models (GCMs) under four emission scenarios of future societal development pathway (SSP126, SSP245, SSP370, and SSP585) during two periods (2040–2069 and 2070–2099). RESULTS AND CONCLUSIONSWe found that late planting had a greater potential to cope with climate change at most study sites. However, all sites required new cultivars with increased thermal time requirements. Under optimum management options at the four study sites, rainfed maize yields were likely to increase by 1.9%–68.3% compared with yields obtained without adaptation. For the adaptation simulation using adjusted planting date alone, GCM was the major source of uncertainty, accounting for 22.9%–36.7% of the total uncertainty at all sites except a high-altitude site where changing planting time was the major source of uncertainty (32.4%). For the adaptation simulation using shifting cultivar alone, crop model was the dominant source of uncertainty, accounting for 24.0%–38.0% of the total uncertainty at all sites except a high-latitude site where shifting cultivar was the major source of uncertainty (34.0%). These findings demonstrated that adaptation options have great potential for increasing maize yields, and the major source of uncertainty depends on study sites and adaptation type used. SIGNIFICANCEThe results of this study advance the understanding of the dominant sources of uncertainty in crop yield under different climate adaptations, thereby improving our confidence in assessments of future climate impact on maize yields determined by different adaptation strategies.