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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]

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]

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]

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]

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 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]

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]

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]

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]