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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]

Maize crop (Zea mays) is one of the staple foods in the East African (EA) region. However, the suitability of its production area is threatened by projected climate change. The Multimodel Ensemble (MME) from eight Coupled Model Intercomparison Project 5 (CMIP5) models was used in this paper to show climate change between the recent past (1970–2000) and the future (2041–2060), i.e., the mid-twenty-first century. The climatic suitability of maize crop production areas is evaluated based on these climate datasets and the current maize crop presence points using Maximum entropy models (MaxEnt). The MME projection showed a slight increase in precipitation under both RCP4.5 and RCP8.5 in certain places and a reduction in most of southern Tanzania. The temperature projection showed that the minimum temperature would increase by 0.3 to 2.95 °C and 0.3 to 3.2 °C under RCP4.5 and 8.5, respectively. Moreover, the maximum temperature would increase by 1.0 to 3.0 °C and 1.2 to 3.6 °C under RCP4.5 and 8.5 respectively. The impacts of these projected changes in climate on maize production areas are the reduction in the suitability of the crop, especially around central and western Tanzania, mid-northern and western Uganda, and parts of western Kenya by 20–40%, and patches of EA will experience a reduction of as high as 40–60%, especially in northern Uganda, and western Kenya. The projected changes in temperature and precipitation present a significant negative change in maize crop suitability. Thus, food security and the efforts towards the elimination of hunger in EA by the mid-twenty-first century will be hampered significantly. We recommend crop diversification to suit the new future environments, modernizing maize farming programs through the adoption of new technologies including irrigation, and climate-smart agricultural practices, etc. [ABSTRACT FROM AUTHOR]

This study analyzed smallholder maize farmers' perceptions of climate change vulnerability and adaptation strategies in the eastern Democratic Republic of the Congo. The study used a cross-sectional quantitative approach, with smallholder farmers selected based on farm size (less than 10 hectares). Using simple random sampling techniques, 210 smallholder farmers in South Kivu Province was selected from October and November 2021. The data were analyzed using frequency analysis, non-parametric Mann–Whitney U-tests, Tobit regression model and structural equations modeling, which demonstrated that demographic and socioeconomic factors influenced smallholder farmers' perceptions and adaptation strategies to climate change. The findings revealed that the level of education, size of the field, and activities of smallholder farmers had significant effects on climate change perception and adaptation strategies. Smallholder farmers' perceptions had a negative (p < 1%) influence on maize smallholder farmers' adaptation to climate change. Common efforts should be made to encourage smallholder farmers to feel committed enough to implement climate change adaptation measures that are effective in mitigating or preventing climate change risk. The results of this study would have implications for policies to support maize smallholder farmers in their efforts to mitigate and resilient to climate change in sub-Saharan Africa. Firstly, the promotion of climate literacy must be sufficient to provide farmers with information on climate and forecasting. Secondly, to empower smallholder farmers with means and resources to prevent and reduce the effects of climate change. Lastly, enhancing the current environment for the agriculture sector will advance community inclusivity and food security. [ABSTRACT FROM AUTHOR]

In this study, we assessed responses of adaptation options to possible climate change scenarios on maize growth and yield by using projections of 20 coupled ensemble climate models under two representative concentration pathways (RCPs) 4.5 and 8.5 by means of a DSSAT model. Growth and yield simulations were made across present and future climate conditions using the hybrid maize variety (Shone). Subsequently, simulated yields were compared with farmer' average and on-farm trial yields. Results showed that on-farm trial yield (5.1–7.3 t ha−1) lay in between farmers' average yield (2.9–5 t ha−1) and water-limited potential yield (6.3–10.6 t ha−1). Maize yields achieved in farmers' fields are projected to decline towards mid-century and further towards the end of the century regardless of the adaptation options compared with baseline in low potential clusters. Results of a combination of adaptation options including February planting, use of 64 kg ha−1 N and conservation tillage provided yield advantage of 5.8% over the 30 cm till under medium GHGs emission scenario during mid-century period at Shamana. Mulching with 5 t ha−1 was projected to produce a 4–5% yield advantage in the Hawassa cluster during the mid-century period regardless of changes in tillage or planting window. Under a high GHGs emission scenario, over 13.4% yield advantage was projected in the Bilate cluster due to conservation tillage and June planting during the mid-century period. In the Dilla cluster, the use of 10 t ha−1 mulch, conservation tillage and early planting (February) would result in a 1.8% yield advantage compared with the control either in medium or high GHGs emission scenarios. Thus, the most promising and least risky practices among simulated strategies were the use of nitrogen and mulching in combination with tillage or planting date adjustment. However, adaptation options remained least promising and highly risky if not integrated with mulching or nitrogen use. Hence, the negative impacts of future climate change and subsequent yield gaps would be reduced by optimizing the application of nitrogen, mulch and their interaction with planting date and tillage in high and low potential areas of maize production. [ABSTRACT FROM AUTHOR]

Climate change and its impact on agriculture productivity vary among crops and regions. The southeastern United States (SE-US) is agro-ecologically diversified, economically dependent on agriculture, and mostly overlooked by agroclimatic researchers. The objective of this study was to compute the effect of climatic variables; daily maximum temperature (Tmax), daily minimum temperature (Tmin), and rainfall on the yield of major cereal crops i.e., corn (Zea mays L.), rice (Oryza sativa L.), and wheat (Triticum aestivum L.) in SE-US. A fixed-effect model (panel data approach) was used by applying the production function on panel data from 1980 to 2020 from 11 SE-US states. An asymmetrical warming pattern was observed, where nocturnal warming was 105.90%, 106.30%, and 32.14%, higher than the diurnal warming during corn, rice, and wheat growing seasons, respectively. Additionally, a shift in rainfall was noticed ranging from 19.2 to 37.2 mm over different growing seasons. Rainfall significantly reduced wheat yield, while, it had no effect on corn and rice yields. The Tmax and Tmin had no significant effect on wheat yield. A 1 °C rise in Tmax significantly decreased corn (− 34%) and rice (− 8.30%) yield which was offset by a 1 °C increase in Tmin increasing corn (47%) and rice (22.40%) yield. Conclusively, overall temperature change of 1 °C in the SE-US significantly improved corn yield by 13%, rice yield by 14.10%, and had no effect on wheat yield. [ABSTRACT FROM AUTHOR]

Bt maize is being increasingly cultivated worldwide as the effects of climate change are increasing globally. Bt maize IE09S034 and its near-isogenic non-Bt maize Zong 31 were used to investigate whether climate change alters the effects of Bt maize on soil Collembola. Warming and drought conditions were simulated using open-top chambers (OTC), and their effects on soil Collembola were evaluated. We found that the maize type had no significant effect on Collembola; however, the abundance and diversity of Collembola were significantly higher in the OTC than outside at the seedling stage; they were significantly lower in the OTC at the heading and mature stages. The interactions of the maize type with the OTC had no effect on these parameters. Therefore, Bt maize had no significant effect on soil Collembola, and the effects of climate warming and drought on soil Collembola depended on the ambient climatic conditions. When the temperature was low, collembolan abundance and diversity were promoted by warming; however, when the temperature was high and the humidity was low, collembolan abundance and diversity were inhibited by warming and drought. The climate changes simulated by the OTC did not alter the effects of Bt maize on soil Collembola. [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]

Combined phenomic and genomic approaches are required to evaluate the margin of progress of breeding strategies. Here, we analyze 65 years of genetic progress in maize yield, which was similar (101 kg ha−1 year−1) across most frequent environmental scenarios in the European growing area. Yield gains were linked to physiologically simple traits (plant phenology and architecture) which indirectly affected reproductive development and light interception in all studied environments, marked by significant genomic signatures of selection. Conversely, studied physiological processes involved in stress adaptation remained phenotypically unchanged (e.g. stomatal conductance and growth sensitivity to drought) and showed no signatures of selection. By selecting for yield, breeders indirectly selected traits with stable effects on yield, but not physiological traits whose effects on yield can be positive or negative depending on environmental conditions. Because yield stability under climate change is desirable, novel breeding strategies may be needed for exploiting alleles governing physiological adaptive traits. Phenomic and genomic approaches are required to evaluate the progress of breeding strategies. Here, the authors analyse 65 years of genetic progress in maize, showing that breeders have selected traits with stable effects on yield whereas not for adaptive traits key for climate change adaptation. [ABSTRACT FROM AUTHOR]

Global climate change leads to the concurrence of a number of abiotic stresses including moisture stress (drought, waterlogging), temperature stress (heat, cold), and salinity stress, which are the major factors affecting maize production. To develop abiotic stress tolerance in maize, many quantitative trait loci (QTL) have been identified, but very few of them have been utilized successfully in breeding programs. In this context, the meta-QTL analysis of the reported QTL will enable the identification of stable/real QTL which will pave a reliable way to introgress these QTL into elite cultivars through marker-assisted selection. In this study, a total of 542 QTL were summarized from 33 published studies for tolerance to different abiotic stresses in maize to conduct meta-QTL analysis using BiomercatorV4.2.3. Among those, only 244 major QTL with more than 10% phenotypic variance were preferably utilised to carry out meta-QTL analysis. In total, 32 meta-QTL possessing 1907 candidate genes were detected for different abiotic stresses over diverse genetic and environmental backgrounds. The MQTL2.1, 5.1, 5.2, 5.6, 7.1, 9.1, and 9.2 control different stress-related traits for combined abiotic stress tolerance. The candidate genes for important transcription factor families such as ERF, MYB, bZIP, bHLH, NAC, LRR, ZF, MAPK, HSP, peroxidase, and WRKY have been detected for different stress tolerances. The identified meta-QTL are valuable for future climate-resilient maize breeding programs and functional validation of candidate genes studies, which will help to deepen our understanding of the complexity of these abiotic stresses. [ABSTRACT FROM AUTHOR]

This study investigates the main drivers of uncertainties in simulated irrigated maize yield under historical conditions as well as scenarios of increased temperatures and altered irrigation water availability. Using APSIM, MONICA, and SIMPLACE crop models, we quantified the relative contributions of three irrigation water allocation strategies, three sowing dates, and three maize cultivars to the uncertainty in simulated yields. The water allocation strategies were derived from historical records of farmer's allocation patterns in drip-irrigation scheme of the Genil-Cabra region, Spain (2014–2017). By considering combinations of allocation strategies, the adjusted R2 values (showing the degree of agreement between simulated and observed yields) increased by 29% compared to unrealistic assumptions of considering only near optimal or deficit irrigation scheduling. The factor decomposition analysis based on historic climate showed that irrigation strategies was the main driver of uncertainty in simulated yields (66%). However, under temperature increase scenarios, the contribution of crop model and cultivar choice to uncertainty in simulated yields were as important as irrigation strategy. This was partially due to different model structure in processes related to the temperature responses. Our study calls for including information on irrigation strategies conducted by farmers to reduce the uncertainty in simulated yields at field scale. [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]