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Climate change is affecting all regions of the world with different climates, and the scale of damage is increasing due to the occurrence of various natural disasters. In particular, maize production is highly affected by abnormal climate events such as heat waves and droughts. Increasing temperatures can accelerate growth and shorten the growing season, potentially reducing productivity. Additionally, enhanced temperatures during the ripening period can accelerate the process, reducing crop yields. In addition, drought stress due to water deficit can greatly affect seedling formation, early plant growth, photosynthesis, reproductive growth, and yield, so proper water management is critical to maize growth. Maize, in particular, is tall and broad-leaved, so extreme drought stress at planting can cause leaves to curl and stunt growth. It is important to understand that severe drought can have a detrimental effect on the growth and reproduction of maize. In addition, high temperatures caused by drought stress can inhibit the induction of flowering in male flowers and cause factors that interfere with pollen development. It is therefore important to increase the productivity of all food crops, including maize, while maintaining them in the face of persistent drought caused by climate change. This requires a strategy to develop genetically modified crops and drought-tolerant maize that can effectively respond to climate change. The aim of this paper is to investigate the effects of climate change and drought tolerance on maize growth. We also reviewed molecular breeding techniques to develop drought-tolerant maize varieties in response to climate change. [ABSTRACT FROM AUTHOR]

Agricultural practices of smallholder farming systems of Latin America can play an important role in reducing their exposure to the risks associated with climate extremes. To date, however, there is no systematic analysis of scientific evidence for the extent to which these practices can provide the multiple benefits needed for smallholders to adapt to climate extremes. In this paper, we searched scientific databases to review scientific evidence of the benefit provided by twenty-six practices in crops commonly farmed by smallholders in the region and highly relevant for their food and nutrition security; namely, coffee, maize and beans. We reviewed scientific documents (n = 304) published in the period 1953–2021 to register evidence of the practices' effects on fifty-five benefits. Our analysis of these documents found measurement records (n = 924) largely based on field experiments (85%). Our results show strong evidence of the multiple benefits that some ecosystem-based practices (e.g., tree-based practices for coffee and no tillage for maize) can provide to support the adaptation to climate extremes of smallholder farming systems and enhance a farm's natural assets (e.g., biodiversity, water, soil). We also found that the majority of research on practices in the region focused more on the socioeconomic dimension (54%) rather than on the capacity of practices to improve the natural assets of a smallholder farmers or reduce the impact of climate extremes. Given these knowledge gaps, we discuss the importance of a renovated investment in research to address existing knowledge gaps. Our concluding suggestions for future research include the need for systematizing existing knowledge from different sources (e.g., peer-reviewed, gray literature, farmers, extension agencies, etc.), and to assess the extent to which these practices can provide multiple benefits for smallholder farming systems by improving their wellbeing, reducing their vulnerability to different hydroclimatic extremes while also contributing to ecosystem services provision at the landscape level. [ABSTRACT FROM AUTHOR]

This article presents the results of research on the possibilities of fragmentation of cultural, and especially agricultural, landscapes in a selected locality in eastern Slovakia, which is currently characterized by a high proportion of large-scale soil units used for growing cereals and crops subsequently used as energy sources (maize and oilseed rape, among others). Slovakia, as the country with the largest average field area in the European Union (EU), is facing a process of fragmentation of these units to counter climate change and increase the resilience of the landscape to erosion, soil fertility, and biodiversity loss. This paper presents a fragmentation method based on the restoration of former dividing lines, mainly formed by dirt roads, based on the historical mapping. The results show that in this way it is possible to achieve denser landscape fragmentation, to create dividing green belts, to increase the resilience of the environment to water and wind erosion, and to create an environment for pollinator resources and a background for plants and animals in the landscape, while respecting the ergometric routing of the dividing lines and the ownership relations of the land. Last but not least, benefits have been quantified in the form of carbon capture, as well as in the construction of a network of recreational or hiking trails. [ABSTRACT FROM AUTHOR]

Extreme weather events have led to widespread yield losses and significant global economic damage in recent decades. African agriculture is particularly vulnerable due to its harsh environments and limited adaptation capacity. This systematic review analyzes 96 articles from Web of Science, Science Direct, and Google Scholar, focusing on biophysical studies related to maize in Africa and worldwide. We investigated the observed and projected extreme weather events in Africa, their impacts on maize production, and the approaches used to assess these effects. Our analysis reveals that drought, heatwaves, and floods are major threats to African maize production, impacting yields, suitable cultivation areas, and farmers' livelihoods. While studies have employed various methods, including field experiments, statistical models, and process-based modeling, African research is often limited by data gaps and technological constraints. We identify three main gaps: (i) lack of reliable long-term experimental and empirical data, (ii) limited access to advanced climate change adaptation technologies, and (iii) insufficient knowledge about specific extreme weather patterns and their interactions with management regimes. This review highlights the urgent need for targeted research in Africa to improve understanding of extreme weather impacts and formulate effective adaptation strategies. We advocate for focused research on data collection, technology transfer, and integration of local knowledge with new technologies to bolster maize resilience and food security in Africa. [ABSTRACT FROM AUTHOR]

Assessment of agricultural water requirements under future climate projections has received increasing attention in recent decades. The agriculture pattern of the semi-arid North China Plain is a maize–wheat rotation system in which sufficient irrigation is required to maintain production. In this study, the effects of future climate scenarios on the net irrigation requirement of the maize–wheat rotation system were assessed using the Food and Agriculture Organization crop growth model—AquaCrop. First, the baseline net irrigation requirement over the study region was obtained through AquaCrop simulation under ERA5-Land reanalysis from 2011 to 2020. In addition, the AquaCrop model was used to predict irrigation requirements in future scenarios (2021–2050) under the extreme-emission scenario of the Shared Socioeconomic Pathway SSP 5-8.5 (SSP 5-8.5). Finally, the predicted irrigation amount for maize and wheat during the period 2021–2050 under SSP 5-8.5 was compared with the baseline to assess the interannual change in irrigation water requirement. Results reveal significant agreement between the AquaCrop-derived daily soil moisture (SM) and a reference SM product with unbiased root mean square differences of 0.03 m3/m3 and 0.04 m3/m3 over maize and wheat, respectively. Furthermore, the median net irrigation requirement is expected to increase by approximately 107 mm (21%) to guarantee optimum yield. [ABSTRACT FROM AUTHOR]

This review examines the 15-year presence of mycotoxins in food from Serbia and Croatia to provide a comprehensive overview of trends. Encompassing the timeframe from 2009 to 2023, this study integrates data from both countries and investigates climate change patterns. The results from Serbia focus primarily on maize and milk and show a strong dependence of contamination on weather conditions. However, there is limited data on mycotoxins in cereals other than maize, as well as in other food categories. Conversely, Croatia has a broader spectrum of studies, with significant attention given to milk and maize, along with more research on other cereals, meat, and meat products compared to Serbia. Over the investigated 15-year period, both Serbia and Croatia have experienced notable shifts in climate, including fluctuations in temperature, precipitation, and humidity levels. These changes have significantly influenced agriculture, consequently affecting the occurrence of mycotoxins in various food products. The results summarized in this 15-year review indicate the urgent need for further research and action to address mycotoxins contamination in Serbian and Croatian food supply chains. This urgency is further emphasized by the changing climatic conditions and their potential to exacerbate public health and food safety risks associated with mycotoxins. [ABSTRACT FROM AUTHOR]

Agricultural production across the African continent is subjected to various effects of climate variability. One of the main staple foods in Sub-Saharan Africa is maize. However, limited scientific research has recently focused on understanding the possible effects of hydro-climatic variability on maize production. The aim of the present work was to contribute to policy and climate adaptation, thus reducing the vulnerability of maize production to climate change over Equatorial Africa. This study firstly examined long-term trends of precipitation (PRE), soil moisture (SM), actual evapotranspiration (E), and potential evapotranspiration (Ep), as well as surface air temperatures, including the minimum (TMIN) and maximum (TMAX). Secondly, the relationship between maize production and these climate variables was quantified for 18 Equatorial African countries (EQCs) over 1980−2021. To assess the linear trends, Mann–Kendall and Sen's slope tests were used to quantify the magnitude of the hydro-climatic variable trends at the 5% significance level, and Pearson's correlation coefficient was used to evaluate the relation of these climate parameters with the maize production. The annual mean PRE declined at 0.03 mm day−110a−1. Other climate variables increased at different rates: SM at 0.02 mmday−110a−1, E at 0.03 mm day−110a−1, Ep at 0.02 mm day−1 10a−1, TMIN and TMAX at 0.01 °C day−110a−1. A regional analysis revealed heterogeneous significant wet–dry and warm–cool trends over the EQCs. While, spatially, dry and warm climates were observed in the central to eastern areas, wet and warm conditions dominated the western regions. Generally, the correlations of maize production with the E, Ep, TMAX, and TMIN were strong (r > 0.7) and positive, while moderate (r > 0.45) correlations of maize production with PRE and SM were obvious. These country-wide analyses highlight the significance of climate change policies and offer a scientific basis for designing tailored adaptation strategies in rainfed agricultural regions. [ABSTRACT FROM AUTHOR]

This study aims to analyze the drivers behind price changes in agricultural products in Türkiye from 2002 to 2021, considering the impacts of three crises of different causes which are the global food crisis, the Russia–Türkiye aircraft crisis, and the COVID-19 pandemic. The potential factors are categorized into four subgroups: governmental effects, agricultural inputs, macroeconomic indicators, and climatic conditions. The selected agricultural goods for price change measurement include wheat and maize representing subsistence goods, and olive oil and cotton as marketing goods. The autoregressive distributed lag (ARDL) model is applied to observe both the short- and long-term impacts of the variables on price developments. The results suggest that government effectiveness, regulatory quality, nitrogen use, water price, money supply, exchange rate, and GDP under the related categories are the most effective factors in price changes. Among the variables under the category of climatic conditions, significant values are obtained only in the analysis of the temperature impact on olive oil. The analysis also reveals the variable impact of crises on the prices of the chosen products, depending on the goods involved. The maize and wheat analyses yield particularly noteworthy results. In the long run, nitrogen use demonstrates a substantial positive impact, registering at 29% for wheat and 19.47% for maize, respectively. Conversely, GDP exhibits a significant negative impact, with 26.15% and 20.08%. Short-term observations reveal that a unit increase in the governmental effect leads to a reduction in inflation for these products by 17.01% and 21.42%. However, changes in regulatory quality result in an increase in inflation by 25.45% and 20.77% for these products, respectively. [ABSTRACT FROM AUTHOR]

Changes in land-use practices have been a central element of human adaptation to Holocene climate change. Many practices that result in the short-term stabilization of socio-natural systems, however, have longer-term, unanticipated consequences that present cascading challenges for human subsistence strategies and opportunities for subsequent adaptations. Investigating complex sequences of interaction between climate change and human land-use in the past—rather than short-term causes and effects—is therefore essential for understanding processes of adaptation and change, but this approach has been stymied by a lack of suitably-scaled paleoecological data. Through a high-resolution paleoecological analysis, we provide a 7000-year history of changing climate and land management around Lake Acopia in the Andes of southern Peru. We identify evidence of the onset of pastoralism, maize cultivation, and possibly cultivation of quinoa and potatoes to form a complex agrarian landscape by c. 4300 years ago. Cumulative interactive climate-cultivation effects resulting in erosion ended abruptly c. 2300 years ago. After this time, reduced sedimentation rates are attributed to the construction and use of agricultural terraces within the catchment of the lake. These results provide new insights into the role of humans in the manufacture of Andean landscapes and the incremental, adaptive processes through which land-use practices take shape. [ABSTRACT FROM AUTHOR]

Simple Summary: High salinity poses a threat to crop growth and yield. Increasing evidence suggests that environmentally friendly plant growth-promoting rhizobacteria (PGPRs) can mitigate the negative impacts of salt stress by modulating various molecular, biochemical, and physiological processes. In the present study, Microbacterium azadirachtae strain CNUC13 was isolated from maize rhizosphere soil. This strain tolerated up to 1000 mM NaCl and 30% PEG 6000 and showed growth-promoting traits like phosphate solubilization and siderophore and indole-acetic acid (IAA) production. The impacts of M. azadirachtae strain CNUC13 on maize (Zea mays L.) germination, growth, and development with salinity were further examined. The results showed that seed priming with M. azadirachtae CNUC13 strain could protect maize from salt stress by modulating plant growth parameters, photosynthetic efficiency, lipid peroxidation, reactive oxygen species, and antioxidant enzyme activities. This is the first study of M. azadirachtae on plant growth enhancement and salt stress tolerance in vivo, and the results indicated the vital contribution of M. azadirachtae CNUC13 in alleviating the adverse effects of salinity on maize seedlings. Soil salinization is one of the leading threats to global ecosystems, food security, and crop production. Plant growth-promoting rhizobacteria (PGPRs) are potential bioinoculants that offer an alternative eco-friendly agricultural approach to enhance crop productivity from salt-deteriorating lands. The current work presents bacterial strain CNUC13 from maize rhizosphere soil that exerted several PGPR traits and abiotic stress tolerance. The strain tolerated up to 1000 mM NaCl and 30% polyethylene glycol (PEG) 6000 and showed plant growth-promoting (PGP) traits, including the production of indole-3-acetic acid (IAA) and siderophore as well as phosphate solubilization. Phylogenetic analysis revealed that strain CNUC13 was Microbacterium azadirachtae. Maize plants exposed to high salinity exhibited osmotic and oxidative stresses, inhibition of seed germination, plant growth, and reduction in photosynthetic pigments. However, maize seedlings inoculated with strain CNUC13 resulted in significantly improved germination rates and seedling growth under the salt-stressed condition. Specifically, compared with the untreated control group, CNUC13-treated seedlings exhibited increased biomass, including fresh weight and root system proliferation. CNUC13 treatment also enhanced photosynthetic pigments (chlorophyll and carotenoids), reduced the accumulation of osmotic (proline) and oxidative (hydrogen peroxide and malondialdehyde) stress indicators, and positively influenced the activities of antioxidant enzymes (catalase, superoxide dismutase, and peroxidase). As a result, CNUC13 treatment alleviated oxidative stress and promoted salt tolerance in maize. Overall, this study demonstrates that M. azadirachtae CNUC13 significantly enhances the growth of salt-stressed maize seedlings by improving photosynthetic efficiency, osmotic regulators, oxidative stress resilience, and antioxidant enzyme activity. These findings emphasize the potential of utilizing M. azadirachtae CNUC13 as a bioinoculant to enhance salt stress tolerance in maize, providing an environmentally friendly approach to mitigate the negative effects of salinity and promote sustainable agriculture. [ABSTRACT FROM AUTHOR]

Agro-climatic indicators (AgcIs) provide a suitable tool to evaluate the implications of climate change on agriculture by simplifying plant–climate interactions. However, developing reliable AgcIs requires high-quality historical climate datasets. Consequently, reanalysis products (RPs) are frequently used as a potential reference dataset for observed climate in agricultural studies. This study aims to compare five RPs (ERA5, ERA5-Land, SCOPE Climate, FYRE Climate, and RFHR) at reproducing observed AgcIs over France. The RPs are evaluated against the SYNOP meteorological data over the 1996–2012 period, focusing on six AgcIs specific to apple, maize, and vine crops. The findings show that RPs perform well in reproducing temperature-based AgcIs, with some slight discrepancies in areas with complex topography. However, all RPs tend to overestimate precipitation amounts and to underestimate dry days, leading to a poor performance in reproducing precipitation-based AgcIs. This study emphasizes the need for a thorough evaluation of the RPs in developing both temperature-based and precipitation-based AgcIs, especially if findings are intended to support operational agricultural decision-making. [ABSTRACT FROM AUTHOR]

The synchronicity of rain and heat in the summer of China's monsoon region provides sufficient water and heat resources for maize growth. However, the intra-annual distribution of precipitation and the probability of extreme precipitation have been inevitably altered by the ongoing climate change, thus affecting the matching degree between precipitation and crop water requirements (MDPCWR). Evaluating the extent to which the MDPCWR will change in the future is of great importance for food security and the sustainable management of water resources. In this study, considering that different growth stages of crops have different sensitivities to water stress, the AquaCrop model was used to calculate the MDPCWR more accurately. In addition, a cumulative distribution function-transform (CDF-t) method was used to remove the bias of 11 global climate models (GCMs) under two typical emission scenarios (SSP2-4.5 and SSP5-8.5) from phase six of the Coupled Model Intercomparison Project (CMIP6). A comprehensive investigation was conducted on how maize growth, water consumption, and the MDPCWR will respond to future climate change with CO2 concentration enrichment in the Huang–Huai–Hai (3H) region in China by driving a well-tested AquaCrop model with the bias-corrected GCMs outputs. The results indicate the following: (1) The CDF-t method can effectively remove seasonal bias, and it also performs well in eliminating the bias of extreme climate events. (2) Under the SSP2-4.5 scenario, the average maximum temperature will increase by 1.31 °C and 2.44 °C in 2021–2050 and 2051–2080, respectively. The average annual precipitation will increase up to 96.8 mm/year, but it will mainly occur in the form of heavy rain. (3) The increased maize evapotranspiration rate does not compensate for the decreased crop water requirement (up to −32 mm/year), due to a shorter growth cycle. (4) The farmland cultivation layer is not able to hold a significant amount of precipitation, due to the increased frequency of heavy rains, resulting in increased irrigation water requirements for maize over the next two periods, with the maximum value of 12 mm/year. (5) Under different scenarios, the projected future MDPCWR will decrease by 9.3–11.6% due to changes in precipitation patterns and crop water requirements, indicating that it will be more difficult for precipitation to meet the water demand of maize growing in the 3H region. The results can provide comprehensive information to understand the impact of climate change on the agricultural water balance and improve the regional strategy for water resource utilization in the 3H region. [ABSTRACT FROM AUTHOR]

Global climate change is a serious threat to food and energy security. Crop growth modelling is an important tool for simulating crop food production and assisting in decision making. Planting date is one of the important model parameters. Larger-scale spatial distribution with high accuracy for planting dates is essential for the widespread application of crop growth models. In this study, a planting date prediction method based on environmental similarity was developed in accordance with the third law of geography. Spring maize planting date observations from 124 agricultural meteorological experiment stations in China over the years 1992–2010 were used as the data source. Samples spanning from 1992 to 2009 were allocated as training data, while samples from 2010 constituted the independent validation set. The results indicated that the root mean square error (RMSE) for spring maize planting date based on environmental similarity was 10 days, which is better than that of multiple regression analysis (RMSE = 13 days) in 2010. Additionally, when applied at varying scales, the accuracy of national-scale prediction was better than that of regional-scale prediction in areas with large differences in planting dates. Consequently, the method based on environmental similarity can effectively and accurately estimate planting date parameters at multiple scales and provide reasonable parameter support for large-scale crop growth modelling. [ABSTRACT FROM AUTHOR]

This study delves into the critical issue of climate change and its impact on maize cultivation, focusing on irrigation water requirements (IWR) and crop evapotranspiration (ETc) values over three distinct time periods: 1971–2000 (RF), 2025–2054 (P1), and 2069–2098 (P2), under the climate scenarios of RCP4.5 and RCP8.5 in the AR5 of the IPCC via the CROPWAT model. The research reveals significant increases in mean temperatures, particularly during summers, in both scenarios, signifying the substantial influence of climate change on the Cukurova Region's climate. Daily average evapotranspiration (ETo) values for the study periods demonstrate noteworthy increases, with the most pronounced rise observed in July for P2 under RCP8.5, emphasizing the seasonality and magnitude of the change. Moreover, the study underscores a consistent escalation in irrigation water requirements from RF to P2 periods for both scenarios, highlighting the pressing need for water resource management strategies in agriculture. Under RCP4.5, the study found that average simulated ETc increased by 9.2% for P1 and 11.7% for P2 compared to the RF period. In the harsher RCP8.5 scenario, ETc values displayed a substantial 20.0% increase for P2 and exhibited a wide range of variation across the study periods. In the light of these escalating climate change impacts, this study underscores the imperative of understanding and addressing the challenges encountered in maize cultivation. The findings emphasize the consistent rise in temperature and irrigation demands, underscoring the necessity for proactive adaptive strategies to ensure the sustainability of agricultural practices and long-term food security. As climate change continues to exert its influence, this research serves as a call to action for policymakers, agricultural stakeholders, and researchers to prioritize adaptation efforts to safeguard the future of maize production and the global food supply. [ABSTRACT FROM AUTHOR]

Drought is the main meteorological disaster that affects the yield and quality of spring maize on the Loess Plateau. This study used data of the spring maize growth period, relative soil humidity, and yield at 18 agricultural meteorological observation stations on the Loess Plateau from 1997 to 2013 to determine the drought category based on the yield reduction rate. Through the drought index according to the conformity rate of category standard and individual case verification, a refined suitability drought index of spring maize on the Loess Plateau was constructed, and the spatial distribution characteristics of drought in different growth stages of spring maize were analyzed. The results showed the following: (1) The number of days in the whole growth period of spring maize in all regions of the Loess Plateau has been extended. The average sowing date of spring maize in the northwest region of the Loess Plateau was 9 April, and that in the east and central regions was 26 April. In terms of spatial distribution, each growth period was gradually delayed from west to east. (2) The correlation between relative soil humidity and yield of spring maize at the jointing stage and heading stage was the best, followed by the milky stage and mature stage, and the relative soil humidity at the sowing stage and emergence stage had little effect on the yield. (3) According to the national drought category standard "Drought Category of Spring Maize in the North", based on the data of yield reduction rate, the drought index of spring maize on the Loess Plateau was refined by region and growth stage. The drought category index values of spring maize in different growth stages and regions changed according to the revised drought category standard, with 71.4% of the sites in the sowing seedling stage and 85.7% of the sites in the seedling jointing stage, and the revised drought category was more severe than the national drought category standard, while at 57.1% of the sites in the jointing and tasseling stages and 71.4% in the tasseling and milking stages, the revised drought category was less severe than the national drought category standard. (4) Based on the revised refined drought index for spring maize on the Loess Plateau, the spatial distribution of drought occurrence frequency across different growth stages of spring maize on the Loess Plateau was analyzed. The frequency of drought occurrence during the seeding and emergence stages was 25–75%. With the change in growth stages, the high-value area of drought occurrence frequency gradually moved northward, and the overall frequency of drought occurrence decreased. For the milky mature stage, the frequency of drought occurrence in a few regions was around 42%, and the drought frequency in most regions was between 8% and 33%. [ABSTRACT FROM AUTHOR]

The climate is changing in Europe: average temperatures are increasing, and so is the frequency of extreme weather events. Climate change has a severe impact on areas suitable for growing certain crops and on food safety, for example, affecting the occurrence of the aflatoxin contamination of maize. The aim of this study was to obtain insights into the impact of climate change on possible changes in land use in Europe, particularly in areas suitable for maize cultivation, and on the probability of the mycotoxin contamination of maize in order to give directions for long-term adaptation to climate change. By combining a land use model and a mycotoxin prediction model, the suitability of land for maize cultivation and the probability of aflatoxin contamination were estimated for suitable areas in Europe, comparing the current climate with the 2050 scenario. In 2050, the occurrence of aflatoxin contamination in Europe is predicted to severely increase, especially in Central and Southern Europe. More northern regions, presently unsuitable for maize cultivation, will become suitable for maize cultivation in 2050. In the baseline scenario, most regions suitable for maize cultivation have a low probability of aflatoxin contamination, whereas in 2050, about half of the regions suitable for maize cultivation have a medium to high probability of aflatoxin contamination. Regions for safely growing maize for human consumption will shift from the southern to the northern half of Europe. [ABSTRACT FROM AUTHOR]

Suitable sowing dates are crucial in plant production to cope with climate change and ensure high-quality crop production. We hypothesize that the analysis of the effect of sowing date and climatic resources on maize kernel nutritional quality (KNQ) (crude fiber, starch, crude fat, and crude protein) might contribute to selecting appropriate sowing dates according to different production requirements and meteorological conditions. The study was based on five main local varieties in three experimental stations (early-maturing variety: Zengyu1317, Hongshuo298, Keyu15; medium-maturing variety: Xianyu335; late-maturing variety: Danyu405) in Northeast China from 2018 to 2021. The results showed that: (1) the average starch content (67.7%) and crude protein content (9.1%) of early-maturing variety maize and the crude fiber content (3.3%) and crude fat content (3.6%) of late-maturing variety maize were the highest in Northeast China; (2) the sowing date had no significant effect on the starch content, but significantly affected the crude protein and crude fiber contents, the kernel protein content of early-maturing variety maize was the highest when the sowing date was delayed for 5 days (9.8%), and the crude fiber content of medium-maturing and late-maturing variety maize (4.3% and 5.39%, respectively) was the highest when the sowing date was advanced by 10 days; (3) during the reproductive growth stage, the more light and heat resources, the less starch content and crude protein content and the more crude fat content; when the diurnal temperature range increased by 1 °C, the crude fat content decreased by 0.28%, and the crude protein content increased by 0.77%; for every 100 mm more precipitation, crude fiber and crude protein content decreased by 0.68% and 0.73%, respectively, and fat content increased by 0.15%. Our results provide a meaningful reference for maize production to cope with climate change and improve kernel quality. [ABSTRACT FROM AUTHOR]

Co-occurring extreme heat, drought, and moisture events are increasing under global warming and pose serious threats to ecosystem and food security. However, how to effectively link compound agrometeorological disasters (CADs) with climate change has not been well assessed. In this study, we focus on the comprehensive influence of large-scale climate factors on CADs rather than extreme meteorological elements. The results indicate that there are two main CADs of spring maize in Shenyang, Northeast China (NEC), including concurrent drought and cold damage (DC) and drought in multiple growth periods (MD). The related circulation anomalies at mid–high latitudes are identified as four patterns, namely, the Northeast Asia Low (NEAL) and Ural High (UH) patterns affecting DC, the Baikal High and Okhotsk Low (BHOL), and the Northeast Asia High (NEAH) patterns leading to MD. The vertical profile and water vapor transport anomalies further demonstrate the influence mechanism of large-scale circulation on compound heat–moisture stresses. This study highlights the role of atmospheric circulation, which can provide effective predictors for these synergistic agrometeorological disasters. [ABSTRACT FROM AUTHOR]

Maize is a crop of significant economic importance. In the northeast region of Brazil, it serves as the foundation of family support for the majority of farmers. However, achieving high levels of productivity requires an adequate water supply throughout its growth cycle. The northeast semi-arid region experiences low rainfall and high potential evapotranspiration, directly affecting maize development and leading to severe declines in productivity. In this study, genetic selection and proteomic analysis are proposed as a strategy to identify the tolerance of maize cultivars against water stress. The experiments were conducted under two water regimes using randomized block designs with three replicates. Development and productivity traits were evaluated, and genetic parameters were estimated using mixed linear models. Selection for water stress tolerance was based on the harmonic mean of the relative performance of genotypic values. Total protein extraction from maize leaves followed the protocol established by the phenol method, and peptides were analyzed through mass spectrometry. The AG8677P cultivar demonstrated remarkable productivity under drought stress conditions, and proteins related to various fundamentally important biological processes for the tolerance mechanism were identified. The combination of genetic selection with proteomic analysis proves to be an efficient strategy, even in the face of limited resources and a small number of treatments. [ABSTRACT FROM AUTHOR]

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]

The influence of global climate change on agricultural productivity is an essential issue of ongoing concern. The growth and development of wheat, maize, and rice are influenced by elevated atmospheric CO2 concentrations, increased temperatures, and seasonal rainfall patterns. However, due to differences in research methodologies (e.g., crop models, climate models, and climate scenarios), there is uncertainty in the existing studies regarding the magnitude and direction of future climate change impacts on crop yields. In order to completely assess the possible consequences of climate change and adaptation measures on crop production and to analyze the associated uncertainties, a database of future crop yield changes was developed using 68 published studies (including 1842 samples). A local polynomial approach was used with the full dataset to investigate the response of crop yield changes to variations in maximum and minimum temperatures, mean temperature, precipitation, and CO2 concentrations. Then, a linear mixed-effects regression model was utilized with the limited dataset to explore the quantitative relationships between them. It was found that maximum temperature, precipitation, adaptation measure, study area, and climate model had significant effects on changes in crop yield. Crop yield will decline by 4.21% for each 1 °C rise in maximum temperature and increase by 0.43% for each 1% rise in precipitation. While higher CO2 concentrations and suitable management strategies could mitigate the negative effects of warming temperatures, crop yield with adaptation measures increased by 64.09% compared to crop yield without adaptation measures. Moreover, the uncertainty of simulations can be decreased by using numerous climate models. The results may be utilized to guide policy regarding the influence of climate change and to promote the creation of adaptation plans that will increase crop systems' resilience in the future. [ABSTRACT FROM AUTHOR]

The increased frequency of climate extremes associated with ongoing climate change has the potential for significant impacts on maize grain yield in maize-producing regions worldwide. In this study, we used a modeling approach to investigate the effects of different types of climatic extremes on maize grain yield in Northeast China. We combined annual mean air temperature and accumulated precipitation data and divided the climate years into 9 categories, using the 10th and 90th percentiles as extreme thresholds. The climate data were represented by 1 normal climate type, 4 individual climate extremes, and 4 combined climate extremes. Changes in the frequencies of climate extremes and their impacts on maize grain yields were analyzed for two 30-year periods (period I: 1960–1989; period II: 1990–2019) using the Agricultural Production Systems sIMulator (APSIM-Maize). Compared with period I, the occurrences of the normal climate and all 3 cold-related climate extremes (i.e., cold-normal, cold-humid, and cold-dry) decreased during period II, while occurrences of the other climate extremes increased. Moreover, according to the APSIM-Maize model, the estimated yield in the years with a normal climate decreased by 4.01%; the 3 cold-related climate extremes increased yields by 26.56%, 12.10%, and 6.68%, respectively; the 2 warm-related climate extremes (warm-normal and warm-dry) and normal-humid years decreased estimated yields by 6.39%, 24.12%, and 5.10%, respectively. The increase in the occurrence of warm-humid years increased the estimated yield by 11.69%. This work confirms the adverse effects of warmer temperatures in the absence of excess rainfall on grain yield and highlights the importance of extremely dry or wet conditions under normal temperature conditions. [ABSTRACT FROM AUTHOR]

Inappropriate agricultural practices consume more input energy and emit higher greenhouse gases (GHGs) which cause global warming and climate change, thereby threatening environmental sustainability. To identify energy and carbon-efficient varieties and nutrient management practices, the present study was undertaken during the kharif season of 2018 and 2019 in a split-plot design with three varieties of fodder maize (African Tall, J-1006 and P-3396) and four nutrient management practices such as N0: Absolute control, N1: 100% recommended dose of fertilizers (RDF), N2: 75% RDF + plant growth promoting rhizobacteria (PGPR) + Panchagavya spray and N3: 50% RDF + 25% farmyard manure (FYM) + PGPR + Panchagavya spray). Results indicated that variety J-1006 and applying 75% RDF + PGPR + Panchagavya spray produced significantly higher dry fodder yield. Among the varieties, J-1006 recorded the highest total energy output (224,123 MJ ha−1), net energy (211,280 MJ ha−1), energy use efficiency (17.64), energy productivity (0.98 kg MJ−1), energy profitability (16.64), and lowest specific energy (1.03 MJ ha−1). Regarding nutrient management, 75% RDF + PGPR + Panchagavya spray fetched the highest total energy output (229,470 MJ ha−1) and net energy (215,482 MJ ha−1). However, energy use efficiency, energy productivity, and energy profitability were significantly higher with integrated nutrient management (N2 and N3) over 100% RDF. Concerning the carbon estimation, J-1006 resulted in a significantly higher carbon output (5479 kg CE ha−1), net carbon gain (5029 kg CE ha−1), carbon efficiency (12.46), carbon sustainability index (11.46), and significantly lower carbon footprint per unit yield (CFy) (131.3 kg CO2-e Mg−1). For nutrient management, the application of 75% RDF + PGPR + Panchagavya spray showed significantly higher carbon output (5609 kg CE ha−1) and net carbon gain (5112 kg CE ha−1). However, significantly higher carbon efficiency, carbon sustainability index, and lower CFy were reported with integrated nutrient management over 100% RDF. Overall, selecting the J-1006 variety and applying 75% RDF + PGPR + Panchagavya spray for fodder maize cultivation could be the most productive in terms of dry fodder production, energy, and carbon efficiency approach. [ABSTRACT FROM AUTHOR]

Drought is a major environmental threat that limits crop growth, development, and productivity worldwide. Improving drought resistance with genetic engineering methods is necessary to tackle global climate change. It is well known that NAC (NAM, ATAF and CUC) transcription factors play a critical role in coping with drought stress in plants. In this study, we identified an NAC transcription factor ZmNAC20, which regulates drought stress response in maize. ZmNAC20 expression was rapidly upregulated by drought and abscisic acid (ABA). Under drought conditions, the ZmNAC20-overexpressing plants had higher relative water content and survival rate than the wild-type maize inbred B104, suggesting that overexpression of ZmNAC20 improved drought resistance in maize. The detached leaves of ZmNAC20-overexpressing plants lost less water than those of wild-type B104 after dehydration. Overexpression of ZmNAC20 promoted stomatal closure in response to ABA. ZmNAC20 was localized in the nucleus and regulated the expression of many genes involved in drought stress response using RNA-Seq analysis. The study indicated that ZmNAC20 improved drought resistance by promoting stomatal closure and activating the expression of stress-responsible genes in maize. Our findings provide a valuable gene and new clues on improving crop drought resistance. [ABSTRACT FROM AUTHOR]

Projections of climate patterns through the end of the 21st century indicate varying impacts across the U.S. However, a common thread of these projections calls for increasing atmospheric temperatures in every region, some more pronounced than others. The significance of these projections for corn and soybean production cannot be overestimated. This study contributes to our understanding of climate change impacts on production and farm revenues by projecting their impacts on corn and soybean yields in Buchanan County, Iowa, a county in the center of the Corn Belt. Projections indicate that as atmospheric temperatures rise and precipitation levels vary markedly, the result is a significant decline in corn and soybean yields, the latter to a lesser extent, as compared to long-term yield trends. Depending upon the climate change scenario that will materialize, corn yields are projected to decline by up to 29%, while soybean yields are projected to decline by up to 24% from their normal upward trends by the year 2100. Due to the long-term upward trends in yields, corn and soybean yields will increase in absolute terms by the end of the century. Depending upon the climate change scenario, actual corn and soybean yields will increase by 30 to 57% and 30 to 66%, respectively, by the end of the 21st century, significantly less than they would have in the absence of these climate projections. [ABSTRACT FROM AUTHOR]

Warmer temperatures predicted as a result of climate change will have an impact on milpa. An experiment was carried out with induced passive heat with the objective of simulating the increase in temperature on the physiological, morphological, and yield parameters of milpa from different climates of San Luis Potosí, Mexico. Two different environments, Open-top chambers (OTC) and control, and three milpas, from warm–dry, temperate, and hot and humid climates, were studied. A total of 12 experimental units of 13.13 m2 were used in the random design, with a factorial arrangement of 2 × 3 and two replications. Abiotic variables (minimum, maximum, and mean daily temperatures and accumulated heat units) were determined and compared between the two environments and confirmed that the OTC increased the abiotic variables. The growth and development parameters increased under the warming effect. Furthermore, the milpa from hot and humid climate was the least affected. In contrast, the warming considerably delayed yield parameters. The squash suffered the most, while the bean benefited the most. The warming affected the chlorophyll fluorescence and gas exchange differently for each crop. However, at an early stage, the maximum photochemical efficiency (Fv/Fm) and non-photochemical quenching (qN) for bean and maize were reduced, while at a late stage, they were Fv/Fm, photochemical quenching (qP), and qN for maize; stomatal conductance and transpiration rate of the squash were improved under the warming treatments. In conclusion, the warming delayed the yield and photosynthetic parameters, while growth and development benefited. The milpa systems were differently affected by warming. [ABSTRACT FROM AUTHOR]

Water stress is one of the most important yield constraints on crop productivity for many crops, and especially for maize, worldwide. In addition, climate change creates new challenges for crop adaptation as water stress appears even in areas where, until recently, there was an adequate water supply. The objective of the present study was to determine the effect of water availability on the morphological and physiological characteristics of maize, and also on the environmental cost under field conditions. The lowest water treatment (ET50) reduced leaf area index, plant height, chlorophyll content, assimilation rate and gas exchange parameters, photosynthetic efficiency, and silage yield. Furthermore, mild water stress (ΕΤ70) affected the characteristics that were studied but maintained a high crop yield. Moreover, the outputs/inputs ratio and energy efficiency showed similar trends, with the highest values under ΕΤ100 treatment and the lowest under ΕΤ50 treatment in two consecutive years. Therefore, the results of this study can be used by farmers in the Mediterranean area, who can maintain or improve their crop yield using a lower amount of water when the water supply is limited, thereby contributing to reducing the impact of global climate change and maintaining crop productivity. [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]

The dangers of population-level mycotoxin exposure have been well documented. Climate-sensitive aflatoxins (AFs) are important food hazards. The continual effects of climate change are projected to impact primary agricultural systems, and consequently food security. This will be due to a reduction in yield with a negative influence on food safety. The African climate and subsistence farming techniques favour the growth of AF-producing fungal genera particularly in maize, which is a food staple commonly associated with mycotoxin contamination. Predictive models are useful tools in the management of mycotoxin risk. Mycotoxin climate risk predictive models have been successfully developed in Australia, the USA, and Europe, but are still in their infancy in Africa. This review aims to investigate whether AFs' occurrence in African maize can be effectively mitigated in the face of increasing climate change and food insecurity using climate risk predictive studies. A systematic search is conducted using Google Scholar. The complexities associated with the development of these prediction models vary from statistical tools such as simple regression equations to complex systems such as artificial intelligence models. Africa's inability to simulate a climate mycotoxin risk model in the past has been attributed to insufficient climate or AF contamination data. Recently, however, advancement in technologies including artificial intelligence modelling has bridged this gap, as climate risk scenarios can now be correctly predicted from missing and unbalanced data. [ABSTRACT FROM AUTHOR]

In this article we connect theoretically the concepts of structural vulnerabilities, recursive crises, and disasters through the linking-up of the COVID-19 pandemic with extreme hydrometeorological events in three municipalities in southern Yucatan, Mexico. The main research goal was to show the effects in productive and commercial systems in beekeeper and farmer households and their coping strategies to highlight the inter-relationships between historical vulnerabilities, crises, and disasters. The methodological approach included ethnographic fieldwork, 101 semi-structured interviews, and five focal groups. In the results, we reconstruct the agro-productive and commercial vulnerabilities built up since 1960 and contextualize the health and hydrometeorological crisis to show how some 87% of households suffered severe consequences to their incomes. The prices of main products (maize, fruit, honey) reached historically low levels as a result of conditions within local markets during the crisis. Half of the households surveyed had to make use of savings and more than 60% received no support from government or from development agencies. We conclude by pointing out the need for accompanying the design and implementation of community mitigation plans, which should take as a starting point the recovery of knowledge and local organization in order to demand from government co-managed, preventive programs, and capacities that would enable communities to confront increasing negative consequences in situations of global climate change and market instabilities in local peasant contexts. Our study aims to reach policy-makers, social organizations, and communities in order to highlight the importance of developing joint capabilities to respond to growing environmental, economic, and health vulnerabilities. [ABSTRACT FROM AUTHOR]

Simple Summary: Plodia interpunctella (Hübner) is an important grain storage pest in China that is distributed in almost every province and that has caused huge economic losses. In this study, we adjusted the biological parameters of the Indian grain borer and then used the CLIMEX model to predict the detailed potential distribution of P. interpunctella in China under current and future conditions. Under historical climatic conditions, the central, northeastern, and southern regions of China are highly suitable habitats for it. Because of temperature change in the future climate, suitable habitats will increase in the eastern part of Qinghai and will decrease in the mid-eastern, northeastern, and southeastern parts of China. This study provides important information for controlling the further spread of the Indian corn borer in China. The Indian meal moth Plodia interpunctella (Hübner) (Lepidoptera: Pyralidae) is a notorious stored-grain pest that can be found in most parts of China. The corpses, excretions, and other secretions of P. interpunctella larvae cause serious grain pollution, seriously affecting the nutritional and economic value of stored grain in China. To elucidate the potential distribution of P. interpunctella in China, we used the CLIMEX 4.0 model to project the potential distribution of the pest using historical climate data (1960–1990) and estimated future climate data (2030, 2050, and 2070). Under the historical climate situation, P. interpunctella was distributed in most areas of China, and its highly favorable habitats account for 48.14% of its total potential distribution. Because of temperature change in the future climate, suitable habitats will increase in the eastern part of Qinghai and will decrease in the mid-eastern, northeastern, and southeastern parts of China. Under these scenarios, the area of this pest's highly favorable habitat will be reduced by 1.24 million km2, and its proportion will decrease to about 28.48%. These predicted outcomes will help to distinguish the impact of climate change on the potential distribution of P. interpunctella, thereby providing important information to design early forecasting and strategies to prevent pest harm to stored grain. [ABSTRACT FROM AUTHOR]

Under a changing environment, the effect of climate change and human activities on maize yield is vital for ensuring food security and efficient socio-economic development. The time series of maize yield is generally non-stationary and contains different frequency components, such as long- and short-term oscillations. Nevertheless, there is no adequate understanding of the relative importance of climate change. In addition, human activities on maize yield at multiple timescales remain unclear, which help in further improving maize yield prediction. Based on the ensemble empirical mode decomposition method (EEMD), the method of dependent variable variance decomposition (DVVD) and the Sen-slope method, the effect of climate change including growing-season precipitation and temperature (i.e., GSP, GEP, CDD, GST, GSMAT, and GSMT) and human activities including effective irrigation area (EIA) and the consumption of chemical fertilizers (CCF) on maize yield were explored at multiple timescales during 1979–2015. The Heilongjiang Province, a highly important maize production area in China, was selected as a case study. The results of this work indicate the following: (1) The original maize yield series was divided into 3.1-, 7.4-, 18.5-, and 37-year timescale oscillations and a residual series with an increasing trend, where the 3.1-year timescale (IMF1), the 18.5-year timescale (IMF3), and the increasing trend (R) were dominant; (2) the original sequence was mainly affected by human activities; (3) climate change and human activities had different effects on maize yield at different timescales: The short-term oscillation (IMF1) of maize yield was primarily affected by climate change. However, human activities dominated the mid- and long-term oscillations (IMF3 and R) of maize yield. This study sheds new insight into multiple timescale analysis of the role of climate and human activities on maize yield dynamics. [ABSTRACT FROM AUTHOR]

Cultivar and sowing date selection are major factors in determining the yield potential of any crop and in any region. To explore how climate change affects these choices, this study performed a regional scale analysis using the well-validated APSIM-maize model for the Northeast China Plain (NEC) which is the leading maize (Zea mays L.) producing area in China. Results indicated that high temperature had a significantly negative effect on grain yield, while effective accumulated temperature and solar radiation had significant positive effects on grain yield and kernel number. Cloudy and rainy weather in flowering stage had significant negative effects on kernel number. Delayed sowing led to less cloudy and rainy weather during flowering and reduced the negative effect on kernel number. Higher diurnal thermal range and less precipitation during the grain-filling stage also increased the 1000-kernel weight. Delayed sowing, however, also significantly increased the risk of early senescence and frost (>80%) in middle and high latitude areas. In the middle and high latitude areas of the NEC, the grain yield of a long-season cultivar (LS) under early sowing (I) (6.2–19.9%) was significantly higher than under medium sowing (II) or late sowing (III), and higher than that of an early sown (I) short-season (SS) and medium-season cultivar (MS). In the low latitude area of the NEC, the grain yield of MS under medium sowing date (II) was higher than that under I and III, meanwhile, this was also higher than that of SS and LS. Therefore, under climate warming, LS sown earlier in high and medium latitudes and MS sown medium in low latitude were the appropriate cultivar and sowing date choices, which could mitigate the stress of high temperatures and reduce the risk of early senescence and frost. Cultivar and sowing date selection are effective measures to alleviate negative effects of climate change on maize production in the NEC, and provides valuable advice for breeders on cultivar selection, and the choice of varieties and sowing dates for farmers in actual production. [ABSTRACT FROM AUTHOR]

Maize is a crucial global commodity, which is used not only for food, but also as an alternative crop in biogas production and as a major energy-supply ingredient in animal diets. However, climate change is jeopardizing current maize production due to its direct impact on weather instability and water availability or its indirect effects on regional climate suitability loss. Hence, new areas for sweet maize cultivation should be considered in the future. Therefore, this study focuses on the possibility of producing maize in a challenging environment in Southern Italy considering rainfed cultivation and two irrigation regimes (full and deficit). The experiment was conducted during two subsequent growing seasons under semi-arid Mediterranean climate conditions. The overall results indicated a significant difference in biomass and yield between irrigated and non-irrigated treatments, and between full and deficit irrigation. Sweet maize cultivated under deficit irrigation gained less biomass than under full irrigation and its development and fruit maturation were delayed. Under deficit irrigation, the plants gave lower yields and a higher percentage of the panicle weight consisted of kernels. Irrigation water productivity was higher for deficit than for full irrigated treatment. These findings indicate the feasibility of sweet maize production in semi-arid areas of Southern Italy using adaptive agricultural strategies including deficit irrigation and controlled water stress. Given the importance of maize production, understanding of maize growth and productivity in a challenging environment may support future agricultural programming and thereby contribute e to mitigation of the direct and indirect effects of climate change. [ABSTRACT FROM AUTHOR]

Agriculture is one of the sectors most susceptible to changes in climatic conditions. The impact is even stronger in Africa, where rain-fed agriculture is vital for daily subsistence, but where adaptive capacity is low. It is therefore crucial to increase the understanding of the actual climate change dynamics on agricultural productivity. This study examined the effects of changes in climatic variables such as rainfall and temperature on maize production in the Ejura-Sekyedumase Municipality, Ghana. Regression, chi-square and trend analyses were used to establish the relationship between climate variables (rainfall and temperature) and maize yield in the study area. This was supplemented with participatory household interviews with 120 farmers to understand the perception of farmers on rainfall and temperature patterns. The results from the study respondents and trend analysis show that rainfall is shorter in terms of duration and less predictable, whilst temperature has increased. The findings suggest that the general relationship between rainfall, temperature and maize yield is such that maize yield increased with increasing rainfall of the right amount and distribution pattern and decreased with increasing temperature. The study concludes that climate variability and/or change is evident in the study area and its effect on maize yield is severe. [ABSTRACT FROM AUTHOR]

Climate change will increase the co-occurrence of Fusarium verticillioides and Aspergillus flavus, along with their mycotoxins, in European maize. In this study, the expression profiles of two pathogenesis-related (PR) genes and four mycotoxin biosynthetic genes, FUM1 and FUM13, fumonisin pathway, and aflR and aflD, aflatoxin pathway, as well as mycotoxin production, were examined in kernels and in artificial medium after a single inoculation with F. verticillioides or A. flavus or with the two fungi in combination. Different temperature regimes (20, 25 and 30 °C) over a time-course of 21 days were also considered. In maize kernels, PR genes showed the strongest induction at 25 °C in the earlier days post inoculation (dpi)with both fungi inoculated singularly. A similar behaviour was maintained with fungi co-occurrence, but with enhanced defence response at 9 dpi under 20 °C. Regarding FUM genes, in the kernels inoculated with F. verticillioides the maximal transcript levels occurred at 6 dpi at 25 °C. At this temperature regime, expression values decreased with the co-occurrence of A. flavus, where the highest gene induction was detected at 20 °C. Similar results were observed in fungi grown in vitro, whilst A. flavus presence determined lower levels of expression along the entire time-course. As concerns afl genes, considering both A. flavus alone and in combination, the most elevated transcript accumulation occurred at 30 °C during all time-course both in infected kernels and in fungi grown in vitro. Regarding mycotoxin production, no significant differences were found among temperatures for kernel contamination, whereas in vitro the highest production was registered at 25 °C for aflatoxin B1 and at 20 °C for fumonisins in the case of single inoculation. In fungal co-occurrence, both mycotoxins resulted reduced at all the temperatures considered compared to the amount produced with single inoculation. [ABSTRACT FROM AUTHOR]

Biochar is being considered a climate change mitigation tool by increasing soil organic carbon contents (SOC), however, questions remain concerning its longevity in soil. We applied 30,000 kg ha−1 of biochars to plots containing a Goldsboro sandy loam (Fine-loamy, siliceous, sub-active, thermic Aquic Paleudults) and then physically disked all plots. Thereafter, the plots were agronomically managed under 4 years (Y) of continuous corn (Zea Mays, L.) planting. Annually, incremental soil along with corresponding bulk density samples were collected and SOC concentrations were measured in topsoil (down to 23-cm). The biochars were produced from Lodgepole pine (Pinus contorta) chip (PC) and Poultry litter (PL) feedstocks. An untreated Goldsboro soil (0 biochar) served as a control. After four years, SOC contents in the biochar treated plots were highest in the top 0–5 and 5–10 cm depth suggesting minimal deeper movement. Declines in SOC contents varied with depth and biochar type. After correction for SOC declines in controls, PL biochar treated soil had a similar decline in SOC (7.9 to 10.3%) contents. In contrast, the largest % SOC content decline (20.2%) occurred in 0–5 cm deep topsoil treated with PC biochar. Our results suggest that PC biochar had less stability in the Goldsboro soil than PL biochar after 4 years of corn grain production. [ABSTRACT FROM AUTHOR]

Drought stress causes heavy damages to crop growth and productivity under global climatic changes. Transcription factors have been extensively studied in many crops to play important roles in plant growth and defense. However, there is a scarcity of studies regarding WRKY transcription factors regulating drought responses in maize crops. Previously, ZmWRKY79 was identified as the regulator of maize phytoalexin biosynthesis with inducible expression under different elicitation. Here, we elucidated the function of ZmWRKY79 in drought stress through regulating ABA biosynthesis. The overexpression of ZmWRKY79 in Arabidopsis improved the survival rate under drought stress, which was accompanied by more lateral roots, lower stomatal aperture, and water loss. ROS scavenging was also boosted by ZmWRKY79 to result in less H2O2 and MDA accumulation and increased antioxidant enzyme activities. Further analysis detected more ABA production in ZmWRKY79 overexpression lines under drought stress, which was consistent with up-regulated ABA biosynthetic gene expression by RNA-seq analysis. ZmWRKY79 was observed to target ZmAAO3 genes in maize protoplast through acting on the specific W-boxes of the corresponding gene promoters. Virus-induced gene silencing of ZmWRKY79 in maize resulted in compromised drought tolerance with more H2O2 accumulation and weaker root system architecture. Together, this study substantiates the role of ZmWRKY79 in the drought-tolerance mechanism through regulating ABA biosynthesis, suggesting its broad functions not only as the regulator in phytoalexin biosynthesis against pathogen infection but also playing the positive role in abiotic stress response, which provides a WRKY candidate gene to improve drought tolerance for maize and other crop plants. [ABSTRACT FROM AUTHOR]

We used the APSIM-Maize model to simulate maize potential yield (Yp) and rain-fed yield (Yw) when adaptation options of sowing date and planting density were adopted under Representative Concentration Pathway (RCP) 4.5 and 8.5 in the Guanzhong Plain of China. The results showed that Yp would decrease by 10.6–14.9% and 15.0–31.4% under RCP4.5 and RCP8.5 for summer maize, and 13.9–19.7% and 18.5–36.3% for spring maize, respectively. The Yw would decrease by 17.1–19.0% and 23.6–41.1% under RCP4.5 and RCP8.5 for summer maize, and 20.9–24.5% and 27.8–45.5% for spring maize, respectively. The loss of Yp and Yw could be reduced by 2.6–9.7% and 0–9.9%, respectively, under future climate for summer maize through countermeasures. For spring maize, the loss of Yp was mitigated by 14.0–25.0% and 2.0–21.8% for Yw. The contribution of changing sowing date and plant density on spring maize yield was more than summer maize, and the optimal adaptation options were more effective for spring maize. Additionally, the influences of changing sowing date and planting density on yields become weak as climate changes become more severe. Therefore, it is important to investigate the potential of other adaptation measures to cope with climate change in the Guanzhong Plain of China. [ABSTRACT FROM AUTHOR]