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Due to global climate change, droughts are likely to become more frequent and more severe in many regions such as in South Africa. In Limpopo, observed high climate variability and projected future climate change will likely increase future maize production risks. This paper evaluates drought patterns in Limpopo at two representative sites. We studied how drought patterns are projected to change under future climatic conditions as an important step in identifying adaptation measures (e.g., breeding maize ideotypes resilient to future conditions). Thirty-year time horizons were analyzed, considering three emission scenarios and five global climate models. We applied the WOFOST crop model to simulate maize crop growth and yield formation over South Africa's summer season. We considered three different crop emergence dates. Drought indices indicated that mainly in the scenario SSP5-8.5 (2051–2080), Univen and Syferkuil will experience worsened drought conditions (DC) in the future. Maize yield tends to decline and future changes in the emergence date seem to impact yield significantly. A possible alternative is to delay sowing date to November or December to reduce the potential yield losses. The grain filling period tends to decrease in the future, and a decrease in the duration of the growth cycle is very likely. Combinations of changed sowing time with more drought tolerant maize cultivars having a longer post-anthesis phase will likely reduce the potential negative impact of climate change on maize. [ABSTRACT FROM AUTHOR]

In the face of climate change scenarios, it is important to evaluate the possibility of an increase in the incidence of corn crop diseases and to promote studies aimed at creating mitigation measures. This paper aims to study the impacts that regional climate changes may have on the potential occurrence of corn common rust (Puccinia sorghi), in the region of Castro, Paraná (Brazil). The Eta climate model was driven by the global model CanESM2. We use the Historical simulation of the EtaCanESM2 model from 1981 to 2005, and future projections from 2046 to 2070 to simulate the occurrence of common rust. The criteria was adopted to simulate the common rust disease favored in environments with the minimum temperature lower than 8 °C, the maximum temperature higher than 32 °C, average temperature between 16 and 23 °C, and relative humidity higher than 95%. In Brazil, there are two different seasons for corn crop (Normaland Safrinha). Results show that relative humidity and minimum temperature simulated by the model presented good skills, approaching the observed data. Compared to the Historical simulation, the projections show a tendency to increase of maximum and minimum temperature in the future, and a tendency to decrease relative humidity. There is an increase in the number of days with the potential for the occurrence of the disease. The distribution of days with favorable conditions to rust disease tends to change in the future. In the Normaland Safrinhaseasons, there is a tendency to increase the number of days with favorable conditions to common rust occurrence. The influence of planting time is greater in Historical simulation when compared to future scenarios. The Safrinhaseason may present more days with the potential for the occurrence of common rust in the future than the Normalseason. [ABSTRACT FROM AUTHOR]

Heat stress in combination with drought has become the biggest concern and threat for maize yield production, especially in arid and hot regions. Accordingly, different optimal solutions should be considered in order to maintain maize production and reduce the risk of heat stress under the changing climate. In the current study, the risk of heat stress across Iranian maize agro-ecosystems was analyzed in terms of both intensity and frequency. The study areas comprised 16 provinces and 24 locations classified into five climate categories: arid and hot, arid and temperate, semi-arid and hot, semi-arid and temperate, and semi-arid and cold. The impact of heat stress on maize under a future climate was based on a 5‐multi‐model ensemble under two optimistic and pessimistic emission scenarios (RCP4.5 and RCP8.5, respectively) for 2040–2070 using the APSIM crop model. Simulation results illustrated that in the period of 2040–2070, intensity and the frequency of heat stress events increased by 2.37 °C and 79.7%, respectively, during maize flowering time compared to the baseline. The risk of heat stress would be almost 100% in hot regions in the future climate under current management practices, mostly because of the increasing high-risk window for heat stress which will result in a yield reduction of 0.83 t ha−1. However, under optimal management practices,farmers will economically obtain acceptable yields (6.6 t ha−1). The results also indicated that the high-risk windows in the future will be lengthening from 12 to 33 days in different climate types. Rising temperatures in cold regions as a result of global warming would provide better climate situations for maize growth, so that under optimistic emission scenarios and optimal management practices, farmers will be able to boost grain yield up to 9.2 t ha−1. Overall, it is concluded that farmers in hot and temperate regions need to be persuaded to choose optimal sowing dates and new maize cultivars which are well adapted to each climate to reduce heat stress risk and to shift maize production to cold regions. [ABSTRACT FROM AUTHOR]

The influence of climate conditions in the agricultural environment is important in evapotranspiration, water availability for plants and roots, and other processes. This research focuses on two aspects: (1) the effects of climate change on the occurrence of extreme events that may affect agricultural processes in a region in Illinois (USA), and (2) the effects of climate change on the soil water dynamics in a corn crop. Different climate scenarios developed by the Institut Pierre Simon Laplace, using a climate model with medium resolution—IPSL(CM5MR), provided input to simulate soil water dynamics in two fields with different drainage system layouts. The Hydrus model simulated surface flux and runoff. Results indicate that the variation of precipitation and temperature in the future may increase extreme events, representing a risk for agriculture. Hydrus simulations indicate different results accordingly to the drainage layout, suggesting that it may be necessary to make adjustments in drainage systems in the future. In general, surface flux and runoff will increase over time, and these changes are more related to extreme events than average values. Extreme event indices show vulnerability in agriculture and will be reflected in changes in the soil water dynamics, and may increase the climatic risk of corn production. [ABSTRACT FROM AUTHOR]

Weather conditions regulate the growth and yield of crops, especially in rain-fed agricultural systems. This study evaluated the use and relative importance of readily available weather data to develop yield estimation models for maize and soybean in the US central Corn Belt. Total rainfall (Rain), average air temperature (Tavg), and the difference between maximum and minimum air temperature (Tdiff) at weekly, biweekly, and monthly timescales from May to August were used to estimate county-level maize and soybean grain yields for Iowa, Illinois, Indiana, and Minnesota. Step-wise multiple linear regression (MLR), general additive (GAM), and support vector machine (SVM) models were trained with Rain, Tavg, and with/without Tdiff. For the total study area and at individual state level, SVM outperformed other models at all temporal levels for both maize and soybean. For maize, Tavg and Tdiff during July and August, and Rain during June and July, were relatively more important whereas for soybean, Tavg in June and Tdiff and Rain during August were more important. The SVM model with weekly Rain and Tavg estimated the overall maize yield with a root mean square error (RMSE) of 591 kg ha−1 (4.9% nRMSE) and soybean yield with a RMSE of 205 kg ha−1 (5.5% nRMSE). Inclusion of Tdiff in the model considerably improved yield estimation for both crops; however, the magnitude of improvement varied with the model and temporal level of weather data. This study shows the relative importance of weather variables and reliable yield estimation of maize and soybean from readily available weather data to develop a decision support tool in the US central Corn Belt. [ABSTRACT FROM AUTHOR]

The stability of maize production is essential to global food security. Climate factors, such as temperature, precipitation, and solar radiation, directly affect the development of maize plants and hence the final grain yield. In this study, we investigated the spatial distributions and temporal trends of agro-climatic indices and severe weather indicators during the actual growing season for summer maize in Huanghuaihai region of China. The results showed that during the growing season, accumulated effective thermal time had significantly increased. From R3 to R6, accumulated effective thermal time, effective precipitation, and photosynthesis active radiation all showed an increasing trend, with the rate of 20.3 °C day, 1.1 mm, and 7.3 MJ m−2 per decade, respectively. From VE to R3, most of the study years showed a > 50% ratio of high-temperature days to subtotal days and > 7 consecutive days without available precipitation. During most of the study years, there were at least 0.5 thunderstorm events from V6 to VT stage in the locations of study; days with strong winds accounted for more than half the subtotal days during the V6-VT stage. And potential risk of lodging may be reduced by the decrease in days with strong wind. The results of this study could be used in optimizing agricultural management in summer maize production in order to take advantage of beneficial climatic elements while combating adverse climatic elements. [ABSTRACT FROM AUTHOR]

The low availability of high-quality meteorological data resulted in the development of synthetic meteorological data generated by satellite or data interpolation, which are available in grids with varying spatio-temporal resolution. Among these different data sources, NASA/POWER and DailyGridded databases have been applied for crop yield simulations. The objective of this study was to evaluate the performance of these two datasets, in different time scales (daily, 10-day, monthly, and annual), as input data for estimating potential (YP) and attainable (YA) maize yields, using the FAO Agroecological Zone crop simulation model (FAO-AEZ), properly calibrated and validated. For that, daily weather data from ten Brazilian locations were collected and compared to the data extracted from NASA/POWER and DailyGridded systems and later applied to estimate the potential and attainable maize yields. DailyGridded data showed a better performance than NASA/POWER for all weather variables and time scales, with confidence index (C) ranging from 0.52 to 0.99 for the former and from 0.09 and 0.99 for the latter. As a consequence of that, DailyGridded data was better than NASA/POWER to estimate maize yields with estimates close to those obtained with observed data, with a lower mean absolute errors (< 30 kg ha−1) and a higher confidence index (C = 0.99). [ABSTRACT FROM AUTHOR]

Low light is a type of abiotic stress that seriously affects plant growth and production efficiency. We investigated the response mechanisms of summer maize to low light by measuring the changes in endogenous hormones in the grains and during grain filling in summer maize at different light intensities to provide a theoretical basis for the production and management of summer maize under light stress. We applied different light treatments in a field experiment as follows: S, shading from tassel stage (VT) to maturity stage (R6); CK, natural lighting in the field; and L, increasing light from VT to R6. The shading level was 60%, and the maximum illumination intensity of the increasing light treatment on cloudy days was 1600-1800 μmol m−2 s−1. Compared with the control, shading significantly increased the grain abscisic acid (ABA) content at 5-20 days after pollination and decreased the indole acetic acid (IAA), zeatin riboside (ZR), and gibberellin (GA) contents (P < 0.05). The grain-filling rate decreased under shading conditions. Meanwhile, the grain volume, grain weight, and yield all decreased; the yields in 2013 and 2014 decreased by 61 and 60%, respectively. The grain IAA, ZR, and GA contents were increased by increasing light. The grain ABA content at 5-20 days after pollination did not significantly differ from that of CK (P < 0.05). After 20 days after pollination, the ABA content decreased, the grain-filling rate and the filling duration increased, and the yield increased. However, shading after anthesis increased the grain ABA content and reduced the IAA, ZR, and GA contents. Grain growth and development were inhibited, and the yield decreased. The grain ABA content decreased; the IAA, ZR, and GA contents increased; and the yield increased after increasing light. The results indicate that different light intensities regulated the levels of grains endogenous hormones, which influenced the grain-filling rate and duration, and consequently, regulated grain weight and yield. [ABSTRACT FROM AUTHOR]

Rainfed maize production in the hilly ecosystem of Northeastern Himalayas often suffers from moisture and soil acidity induced abiotic stresses. The present study measured evapotranspiration loss (ET) of maize crop under controlled condition (pot experiment) of water deficit (W-25 % and W-50 % of field capacity soil moistures) and well watered (W = 100 % of field capacity (FC)) regimes in strong acid soils (pH = 4.3) of the Northeastern Himalayan Region of India. The response of soil ameliorants (lime) and phosphorus (P) nutrition under differential water regimes on ET losses and water use efficiency was also studied. The measured seasonal ET loss varied from 124.3 to 270.9 mm across treatment combinations. Imposition of water deficit stress resulted in significant ( p < 0.05) reduction (by 33-50 %) of seasonal ET losses but was at the cost of delay in tasseling to silking, 47-65 % reduction in dry matter accumulation (DMA), 12-22 days shortening of grain formation period, and complete kernel abortion. Liming @ 4 t ha significantly ( p < 0.05) increased ET losses and DMA across water regimes but the magnitude of increase was higher in severely water deficit (W) regime. Unlike lime, P nutrition improved DMA only in well-watered regimes (W) while seasonal ET loss was unaffected. Vegetative stage (tillering to tasseling) contributed the maximum ET losses while weekly crop ET loss was estimated highest during 11th-14th week after sowing (coincided with blistering stage) and then declined. Water use efficiency estimated from dry matter produced per unit ET losses and irrigation water used varied from 4.33 to 9.43 g dry matter kg water and 4.21 to 8.56 g dry matter kg, respectively. Among the input factors (water, P, and lime), water regime most strongly influenced the ET loss, growth duration, grain formation, and water use efficiency of maize. [ABSTRACT FROM AUTHOR]

This study seeks to quantify the roles of soybean and corn plants and the cropland ecosystem in the regional NO budget of the Upper Midwest, USA. The NO flux was measured at three scales (plant, the soil-plant ecosystem, and region) using newly designed steady-state flow-through plant chambers, a flux-gradient micrometeorological tower, and continuous tall-tower observatories. Results indicate that the following. (1) NO fluxes from unfertilized soybean (0.03 ± 0.05 nmol m s) and fertilized corn plants (−0.01 ± 0.04 nmol m s) were about one magnitude lower than NO emissions from the soil-plant ecosystem (0.26 nmol m s for soybean and 0.95 nmol m s for corn), confirming that cropland NO emissions were mainly from the soil. (2) Fertilization increased the corn plant flux for a short period (about 20 days), and late-season fertilization dramatically increased the soybean plant emissions. (3) The direct NO emission from cropland accounted for less than 20 % of the regional flux, suggesting a significant influence by other sources and indirect emissions, in the regional NO budget. [ABSTRACT FROM AUTHOR]

The primary objective of this study was to clarify the influence of crop plants on atmospheric methane (CH) in an agriculture-dominated landscape in the Upper Midwest of the United States. Measurements were carried out at two contrasting scales. At the plant scale, CH fluxes from soybean and corn plants were measured with a laser-based plant chamber system. At the landscape scale, the land surface flux was estimated with a modified Bowen ratio technique using measurements made on a tall tower. The chamber data revealed a diurnal pattern for the plant CH flux: it was positive (an emission rate of 0.4 ± 0.1 nmol m s, average of soybean and corn, in reference to the unit ground area) during the day, and negative (an uptake rate of −0.8 ± 0.8 nmol m s) during the night. At the landscape scale, the flux was estimated to be 14.8 nmol m s at night and highly uncertain during the day, but the available references and the flux estimates from the equilibrium methods suggested that the CH flux during the entire observation period was similar to the estimated nighttime flux. Thus, soybean and corn plants have a negligible role in the landscape-scale CH budget. [ABSTRACT FROM AUTHOR]

Abstract  The development of maize (Zea mays L.) varieties as factories of pharmaceutical and industrial compounds has renewed interest in controlling pollen dispersal. The objective of this study was to compare gene flow into maize fields of different local pollen densities under the same environmental conditions. Two fields of approximately 36 ha were planted with a nontransgenic, white hybrid, in Ankeny, Iowa, USA. In the center of both fields, a 1-ha plot of a yellow-seeded stacked RR/Bt transgenic hybrid was planted as a pollen source. Before flowering, the white receiver maize of one field was detasseled in a 4:1 ratio to reduce the local pollen density (RPD). The percentage of outcross in the field with RPD was 42.2%, 6.3%, and 1.3% at 1, 10, and 35 m from the central plot, respectively. The percentage of outcross in the white maize with normal pollen density (NPD) was 30.1%, 2.7%, and 0.4%, respectively, at these distances. At distances greater than 100 m, the outcross frequency decreased below 0.1 and 0.03% in the field with RPD and NPD, respectively. A statistical model was used to compare pollen dispersal based on observed outcross percentages. The likelihood ratio test confirmed that the models of outcrossing in the two fields were significantly different (P is practically 0). Results indicated that when local pollen is low, the incoming pollen has a competitive advantage and the level of outcross is significantly greater than when the local pollen is abundant. [ABSTRACT FROM AUTHOR]