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Affected by global warming, the frequency of crop pests and diseases have increased, causing huge losses to agricultural production. To better grasp the development and trends of research on the effects of climate change on crop pests and diseases, the literature on the impact of climate change on crop pests and diseases published from 1990 to 2021 in the Web of Science (WOS) core collection database was used. This study explores the literature characteristics and hotspot evolution through the bibliometric visualization analysis software COOC, VOSviewer, and CiteSpace, with a view to identifying the changing characteristics and trends of research changes in this field. The results showed that the number of literature on the impact of climate change on crop pests and diseases increased rapidly. The main fields involved include environmental sciences, ecology, and agronomy. Papers in these fields mainly published in journals, such as PLos One, Forest Ecology and Management, and Frontiers in Plant Science. The country with the highest number of publications was the United States, followed by China and Australia. The most prolific authors in the top 20 are research scholars from China. The first author of the top 20 highly cited papers was from the United States. It was found that that current research on the impact of climate change on crop pests and diseases mainly focuses on agricultural production and food safety. Modelling and crop growth has maintained steady development. At present, research in this field mainly focuses on pest management strategies under the impact of climate change, the response of single species, and the complex ecological mechanisms behind the response. This study provides unique insights into the research field of the impact of climate change on crop pests and diseases and provides a reference direction for future research development in this field. [ABSTRACT FROM AUTHOR]

Based on the climate proxy data, several recent studies have concluded that the Ming dynasty's reign in China coincided with the Little Ice Age, a global crisis. In response, scholars have published several reports in recent years addressing this topic. This paper presents a comprehensive overview of the current research findings in English regarding this subject and identifies existing research gaps. The author proposes that the impact of climate on different regions during the late Ming period remains largely underexplored. Furthermore, scholars must exercise caution when assuming that adverse climatic conditions uniformly impacted the Ming empire during the Little Ice Age. This paper also highlights the use of simplistic models by scholars linking cold and dry climates to crop failure, floods, droughts, population decline, and other factors. However, any straightforward models that presume causal determination risk ignoring historical facts. [ABSTRACT FROM AUTHOR]

Crop quality is directly related to national food security and people's living standards, and it is also key to the improvement of agricultural quality and efficiency. According to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC), climate change has already exerted a negative impact on crop quality. To address climate change scientifically, this paper reviews the latest progress in studies on the impact of climate change on crop quality, and points out limitations of existing studies: (1) Climate factors affecting crop quality are not yet clearly identified; (2) The climate change influencing mechanism and disaster-inducing critical meteorological conditions for crop quality are not clearly established; and (3) No climatic suitability model for crop quality has been constructed to reflect the synergy of multiple climate factors. To ensure food quality and security, and to adjust and optimize the industrial planning of grain crops, promote a high crop quality and yield, and address climate change scientifically, this paper argues that subsequent studies should discuss the following topics, focusing on the climatic suitability of crop quality and resistance mechanisms: (1) changing laws involving the climate sensitivity of crop quality in the context of climate change; (2) response mechanisms of crop quality to climate change; (3) crop quality monitoring and assessment modelling; (4) climatic suitability zoning of crop quality; (5) spatiotemporal evolution trends of crop quality and its responses; and (6) crop quality and its legal measures in the world. [ABSTRACT FROM AUTHOR]

According to the climate change scenario, climate change in the Korean Peninsula is expected to worsen due to extreme temperatures, with effects such as rising average temperatures, heat waves, and droughts. In Republic of Korea, which relies on foreign countries for the supply of forage crops, a decrease in the productivity of forage crops is expected to cause increased damage to the domestic livestock industry. In this paper, to solve the issue of climate vulnerability for forage crops, we performed a study to predict the productivity of forage crops in relation to climate change. We surveyed and compiled not only forage crop production data from various regions, but also experimental cultivation production data over several years from reports of the Korea Institute of Animal Science and Technology. Then, we crawled related climate data from the Korea Meteorological Administration. Therefore, we were able to construct a basic database for forage crop production data and related climate data. Using the database, a production prediction model was implemented, applying a multivariate regression analysis and deep learning regression. The key factors were determined as a result of analyzing the changes in forage crop production due to climate change. Using the prediction model, it could be possible to forecast the shifting locations of suitable cultivation areas. As a result of our study, we were able to construct electromagnetic climate maps for forage crops in Republic of Korea. It can be used to present region-specific agricultural insights and guidelines for cultivation technology for forage crops against climate change. [ABSTRACT FROM AUTHOR]

In recent years, the adverse effect of climate change on soil properties in the agricultural sector has become a dreadful reality worldwide. Climate change-induced abiotic stresses such as salinity, drought and temperature fluctuations are devastating crops' physiological responses, productivity and overall yield, which is ultimately posing a serious threat to global food security and agroecosystems. The applications of chemical fertilizers and pesticides contribute towards further deterioration and rapid changes in climate. Therefore, more careful, eco-friendly and sustainable strategies are required to mitigate the impact of climate-induced damage on the agricultural sector. This paper reviews the recently reported damaging impacts of abiotic stresses on various crops, along with two emerging mitigation strategies, biochar and biostimulants, in light of recent studies focusing on combating the worsening impact of the deteriorated environment and climate change on crops' physiological responses, yields, soil properties and environment. Here, we highlighted the impact of climate change on agriculture and soil properties along with recently emerging mitigation strategies applying biochar and biostimulants, with an aim to protecting the soil, agriculture and environment. [ABSTRACT FROM AUTHOR]

The paper presents the estimated changes in the soil water content, the total runoff, the sediment yield and the actual evapotranspiration for the small Bystra catchment in the east of Poland. The findings are based on the results of three simulations covering the years of 2041–2050. The simulations were based on a calibrated and validated SWAT model (2010–2017). The first variant covers just the climate change and the existing structure of soil cultivation for the three regional climate models supported by the EC-EARTH global climate model in the emission scenarios RCP4.5 and RCP8.5. Variants two and three are based on the first variant in terms of the changing climate. The second variant, however, involves placing a pond in each farm in the catchment, while the third variant involves designing huge reservoirs as a result of land consolidation. Variants two and three occur in five adaptation scenarios each. The first adaptation scenario (V2.1 and V3.1) involves only increasing the number of ponds on the farm or increasing the number of reservoirs for non-irrigated arable land crops, i.e., WWHT (winter cereals), BARL (spring cereals), CANP (rapeseed) and CRDY (other crops). The second adaptation scenario (V2.2 and V3.2) involves growing vegetables without irrigation (instead of cereals). The third adaptation scenario (V2.3 and V3.3) involves growing vegetables with irrigation (instead of cereals). The fourth adaptation scenario (V2.4 and V3.4) involves partial cultivation of vegetables and cereals. The fifth adaptation scenario (V2.5 and V3.5) involves partial cultivation of orchards and cereals. The adaptation scenarios of the irrigation of vegetables from deep water-bearing layers (second variant) or reservoirs (third variant) contribute to the increase in water content in the soil, especially in summer, in comparison with the adaptation scenarios for vegetable cultivation without irrigation. What is more, the actual evapotranspiration was higher in the adaptation scenarios involving irrigation than in scenarios without irrigation. It is known that the changes in water content in soil and the intensification of water erosion are gravely affected by modifications in crops and soil cultivation. A change from cereal cultivation to irrigated vegetable cultivation or orchards increased the water content in the soil in most climatic projections. However, the increase in the number of ponds in the second variant had little impact on the soil water content, actual evapotranspiration and overall runoff, while the erosion loss decreased. With the lower precipitation levels in the years 2041–2050 relative to 2010–2017, as presented in the emissive scenario RCP 4.5, the soil water content decreases by up to 14% for most variants. Total runoff for most variants will also be lower by 4–35%. The percentage change in sediment yield will fluctuate between −86% and 116%. On the other hand, the actual evapotranspiration for most variants will be higher. With higher precipitation levels in the years 2041–2050 relative to 2010–2017, as presented in the emissive scenario RCP 8.5, the soil water content changes slightly from −7% to +3%. Total runoff for most variants will also be higher by as much as 43%. Sediment yield for most scenarios may increase by 226%. The actual evapotranspiration for most variants will also be higher. Irrigation variants tend to increase soil available water while increasing evapotranspiration and total outflow in the catchment as compared to non-irrigated LULC. The largest increase in the soil water content is observed in most irrigation variants for RCP 4.5 (annual average 316–319 mm) (V2.3-V2.5, V3.2, and V3.3) and RCP 8.5 (annual average 326–327 mm) (V2.3-V2.5 and V3.3) as compared to V1 (BaU) (315 mm–RCP 4.5 and 324 mm–RCP 8.5) for the years 2041–2050. On the other hand, the lowest increase in soil water content is observed in the V3.5 variant, with an annual average of 292 mm for RCP 4.5 and an annual average of 311 mm for RCP 8.5. Thus, for future climate change scenarios, irrigation with water reservoirs (ponds and storage reservoirs) should be considered. The study proves the rationale behind building ponds in small catchments in order to increase water resources in a landscape and also to counteract adverse effects of climate changes, i.e., sediment outflow and surface water erosion. [ABSTRACT FROM AUTHOR]

Miscanthus is a perennial wild plant that is vital for the production of paper and roofing, as well as horticulture and the development of new high-yielding crops in temperate climates. Chromosome-level assembly of the ancient tetraploid genome of miscanthus chromosomes is reported to provide resources that can link its chromosomes to related diploid sorghum and complex polyploid sugarcane. Analysis of Miscanthus sinensis and Miscanthus sacchariflorus showed intense mixing and interspecific hybridization and documented the origin of a high-yielding triploid bioenergetic plant, Miscanthus × giganteus. The Miscanthus genome expands comparative genomics functions to better understand the main abilities of Andropogoneae herbs. Miscanthus × giganteus is widely regarded as a promising lignocellulosic biomass crop due to its high-biomass yield, which does not emit toxic compounds into the environment, and ability to grow in depleted lands. The high production cost of lignocellulosic bioethanol limits its commercialization. The main components that inhibit the enzymatic reactions of fermentation and saccharification are lignin in the cell wall and its by-products released during the pre-treatment stage. One approach to overcoming this barrier could be to genetically modify the genes involved in lignin biosynthesis, manipulating the lignin content and composition of miscanthus. [ABSTRACT FROM AUTHOR]

The world’s food and agricultural programs have gradually declined into an unsustainable situation due to challenges such as increase in world population, varied agro-climatic regions, increase temperature, extreme sole-culture growing techniques, and water shortage. A considerable emphasis has been put on few staple food crops coupled with repeated dieting, food scarcity, and essential mineral deficits, frequently inducing dietary disorders. Because relying on staple crops may lead to serious food shortages in the future, we must adjust our dietary habits to include a diverse range of non-staple foods and maximize their use in order to achieve food security and reduce the nutritional gap. To assure healthy meals around the world, an authentic and reasonable strategy is presented to draw additional awareness towards variations in agricultural production techniques and dietary preferences. The EAT-Lancet declaration highlighted the importance of increasing agri-based foods to achieve sustainable health. Expanding overlooked crops with abundant genetic stocks and possibly beneficial characteristics is an approach that might meet food and nutritional security challenges. Although undervalued, pumpkin is a valuable vegetable herbaceous plant that contributes to global food and nutritional security. This crop has already been identified as a revolutionary age crop, balanced food, and more adapted to low soil and atmospheric circumstances than other major crops. This review paper focuses on the potential uses of pumpkin as an underutilized crop; diversification and development of hybrids, particularly hybridization breeding through diallel mating design; and how implementation of this “modern” technology would contribute to the breeding of the neglected pumpkin vegetable and stimulate productivity and nourish the world’s largest malnourished, deprived, and starved populations. [ABSTRACT FROM AUTHOR]

The adaptation measures of agricultural crops to current climate change are also reflected at the level of land-use planning for species with resistance to rainfall shortages and periods of prolonged droughts. The present paper aimed at the spatial modeling of land favorability for alfalfa (Medicago sativa L.) within Bihor county, which is located in Northwest Romania. This was performed by using GIS spatial analysis techniques, particularly the technique of rating agricultural plots by using as a modeling basis the synthetic climate indicators, soil indices, as well as topographic characteristics, which are considered relevant for the studied species. As a result of the modeling process, agricultural plots that are favorable for the alfalfa culture were identified. A comparative analysis of the profit was also carried out both for the green and dry masses of eight types of alfalfa, which are suitable for the national environmental conditions. Land favorability modeling for alfalfa cultivation will be carried out by using GIS spatial analysis techniques, which allow the use of large databases while maintaining the necessary degree of detail, and they make possible the correlations between factors and production estimated per hectare, which are correlations that are characteristic for the environmental factors. Thus, for the studied territory, the best green alfalfa production was identified as being obtained from the Carinca and Daniela varieties, whereas the Mihaela and Teodora varieties were noticed to provide the best dry alfalfa production. [ABSTRACT FROM AUTHOR]

Colombia has positioned itself as a significant actor in Hass avocado production, capitalizing on the rising global demand and its suitable climate for the crop. These conditions have led to considerable investments from farmers. In this business environment, this research presents a systematic simulation and methodological approach for the evaluation of crops focusing on the Hass avocado and its extension to small-scale producers in Colombia. The initial phase involved a comprehensive analysis of key variables in the Hass avocado production chain, assessing productivity and viability. Subsequently, a dynamic model was developed to explore four scenarios spanning 13 years. The first scenario evaluated the production chain's current behavior, while the second scrutinized the impact of credit accessibility. The third scenario analyzed the associativity among producers' effects, and the fourth assessed the impact of government support. The results underscore that the implementation of each strategy improves the economic returns. Integrating all three strategies is the most effective method. These scenarios serve as proactive tools for investors, equipping them valuable insights and enabling informed decisions. Moreover, the study advocates for the promotion of rural economic development through strategic agricultural interventions. [ABSTRACT FROM AUTHOR]

Simple Summary: Tuta absoluta (Meyrick) is an invasive insect pest that poses a threat to solanaceous crops. In recent years, the occurrences of extremely high temperature have been increasing due to climate change. Therefore, it is important to study the effect of high temperature on the growth and development of T. absoluta. In this study, when the eggs, pupae, and adults of T. absoluta were exposed to high-temperature stress, the pupal stage exhibited the highest sensitivity. This was demonstrated by a significant decrease in emergence rate, longevity, and fecundity. High-temperature stress during the egg stage resulted in a cascading effect, leading to a reduction in the adult longevity. This study provides a new insight for the integrated management of T. absoluta under high temperature. Insect life processes and reproductive behaviors are significantly affected by extremely high temperatures. This study focused on Tuta absoluta, which poses a severe threat to tomato cultivars. The effects of intense heat stress on the growth, development, oviposition, and longevity of T. absoluta were investigated. This investigation encompassed various developmental stages, including eggs, pupae, and adults. This study revealed that egg hatching and pupa emergence rates were significantly reduced at a temperature of 44 °C maintained for 6 h. The longevity of adults that emerged after the egg and pupal stages were exposed to 44 °C for 6 h was significantly reduced compared to the control. Notably, there was no significant variation in adult fecundity after egg-stage exposure to high temperatures. However, all treatments exhibited significantly reduced fecundity compared to the control after exposure to high temperatures during the pupal stage. Adult survival rates after exposure to 40 °C and 44 °C for 3 h were 74.29% and 22.40%, respectively, dramatically less than that of the control, which was 100%. However, no significant differences were noted in terms of longevity and egg production. These results offer a better understanding of the complex interactions between extreme temperatures and the life history traits of T. absoluta, thereby offering valuable insights for implementing management strategies to alleviate its impact on tomato crops in response to climate change. [ABSTRACT FROM AUTHOR]

The variety of natural indicators, associated with weather forecasting and climate prediction, as used by farmers in the South-Western Free State province of South Africa, is described. Most farmers in this area were not familiar with the application of weather forecasts/climate predictions for agricultural production, or with other science-based agrometeorological products. They relied almost fully on their experience and traditional knowledge for farming decision making. The indicators for traditional knowledge are demonstrated here in broad terms, relying on the stories and indications from observations and years of experience of their use by the farmers. These means of engagement with the natural environment, are skills not well understood by most scientists, but useful to the farmers. They range from the constellation of stars, animal behavior, cloud cover and type, blossoming of certain indigenous trees, appearance and disappearance of reptiles, to migration of bird species and many others. It is suggested that some short-term traditional forecasts/predictions may be successfully merged with science-based climate predictions. The traditional knowledge and its use, reported on in this paper, is what scientists learned from farmers. Berkes was right that scholars have wasted too much time and effort on a science versus traditional knowledge debate; we should reframe it instead as a science and traditional knowledge dialogue and partnership. The complications of a changing climate make this even more necessary. [ABSTRACT FROM AUTHOR]

Extension agrometeorology is applied in agrometeorological extension work to advice and serve farmers. In agrometeorology, response farming has been developed decades ago. Climate change complicates response farming, but does not alter it. This paper reports on new operationalization of that response farming in new educational commitments in agroclimatology. It is explained how "Science Field Shops" are an example in Indonesia. This was based on a thorough analysis of what climate change means for farmers in Asia. For Africa, we report on eying the training of agrometeorological extension trainers ("product intermediaries") in West Africa, based on a thorough analysis of what climate change means for farmers in Africa. We also compare experience with reaching farmers in South Africa and farmer communities in Zambia, as new forms of supporting response farming, all under conditions of a changing climate. The paper, for the first time, connects results from four different programs the senior author is taking part in. There is first and foremost the need for training material to make it possible for the product intermediaries to participate in training extension intermediaries. This should, particularly, bring new knowledge to farmers. With what is presently available and with new approaches, climate extension should be developed and tested with farmers in ways that improve farmer preparedness and decision making. [ABSTRACT FROM AUTHOR]

Northeast China (NEC) is one of the most important national agricultural production bases, and its agricultural water dynamics are essential for food security and sustainable agricultural development. However, the dynamics of long-term annual crop-specific agricultural water and its crop type and climate impacts remain largely unknown, compromising water-saving practices and water-efficiency agricultural management in this vital area. Thus, this study used multi-source data of the crop type, climate factors, and the digital elevation model (DEM), and multiple digital agriculture technologies of remote sensing (RS), the geographic information system (GIS), the Soil Conservation Service of the United States Department of Agriculture (USDA-SCS) model, the Food and Agriculture Organization of the United Nations Penman–Monteith (FAO P-M) model, and the water supply–demand index (M) to map the annual spatiotemporal distribution of effective precipitation (Pe), crop water requirement (ETc), irrigation water requirement (IWR), and the supply–demand situation in the NEC from 2000 to 2020. The study further analyzed the impacts of the crop type and climate changes on agricultural water dynamics and revealed the reasons and policy implications for their spatiotemporal heterogeneity. The results indicated that the annual average Pe, ETc, IWR, and M increased by 1.56%/a, 0.74%/a, 0.42%/a, and 0.83%/a in the NEC, respectively. Crop-specifically, the annual average Pe increased by 1.15%/a, 2.04%/a, and 2.09%/a, ETc decreased by 0.46%/a, 0.79%/a, and 0.89%/a, IWR decreased by 1.03%/a, 1.32%/a, and 3.42%/a, and M increased by 1.48%/a, 2.67%/a, and 2.87%/a for maize, rice, and soybean, respectively. Although the ETc and IWR for all crops decreased, regional averages still increased due to the expansion of water-intensive maize and rice. The crop type and climate changes jointly influenced agricultural water dynamics. Crop type transfer contributed 39.28% and 41.25% of the total IWR increase, and the remaining 60.72% and 58.75% were caused by cropland expansion in the NEC from 2000 to 2010 and 2010 to 2020, respectively. ETc and IWR increased with increasing temperature and solar radiation, and increasing precipitation led to decreasing IWR in the NEC. The adjustment of crop planting structure and the implementation of water-saving practices need to comprehensively consider the spatiotemporally heterogeneous impacts of crop and climate changes on agricultural water dynamics. The findings of this study can aid RS-GIS-based agricultural water simulations and applications and support the scientific basis for agricultural water management and sustainable agricultural development. [ABSTRACT FROM AUTHOR]

The possible influence of global climate changes on agricultural production is becoming increasingly significant, necessitating greater attention to improving agricultural production in response to temperature rises and precipitation variability. As one of the main winter wheat-producing areas in China, the temporal and spatial distribution characteristics of precipitation, accumulated temperature, and actual yield and climatic yield of winter wheat during the growing period in Shanxi Province were analysed in detail. With the utilisation of daily meteorological data collected from 12 meteorological stations in Shanxi Province in 1964–2018, our study analysed the change in winter wheat yield with climate change using GIS combined with wavelet analysis. The results show the following: (1) Accumulated temperature and precipitation are the two most important limiting factors among the main physical factors that impact yield. Based on the analysis of the ArcGIS geographical detector, the correlation between the actual yield of winter wheat and the precipitation during the growth period was the highest, reaching 0.469, and the meteorological yield and accumulated temperature during this period also reached its peak value of 0.376. (2) The regions with more suitable precipitation and accumulated temperature during the growth period of winter wheat in the study area had relatively high actual winter wheat yields. Overall, the average actual yield of the entire region showed a significant increasing trend over time, with an upward trend of 47.827 kg ha−1 yr−1. (3) The variation coefficient of winter wheat climatic yield was relatively stable in 2008–2018. In particular, there were many years of continuous reduction in winter wheat yields prior to 2006. Thereafter, the impact of climate change on winter wheat yields became smaller. This study expands our understanding of the complex interactions between climate variables and crop yield but also provides practical recommendations for enhancing agricultural practices in this region [ABSTRACT FROM AUTHOR]

This paper examines the effects of climatic and non-climatic factors on cassava yields in Togo using an Autoregressive Distributed Lag (ARDL) modelling approach and pairwise Granger Causality tests. Secondary data on production statistics, rural population, climate variables, prices and nominal exchange rate for the period 1978--2009 are used. Results for estimated short- and long-run models indicate that cassava yield is affected by both 'normal' climate variables and within-season rainfall variability. An inverse relationship is found between area harvested and yield of cassava, but a significant positive and elastic effect of labour availability on yield in the long run. Increasing within-lean-season rainfall variability and high lean-season mean temperature are detrimental to cassava yields, while increasing main-season rainfall and mean-temperature enhance cassava yields. Through Granger Causality tests, a bilateral causality is found between area harvested and yield of cassava, and four unidirectional causalities from labour availability, real producer price ratio between yam and cassava, main-season rainfall and lean-season mean temperature to cassava yields. Based on the findings from this study, investment in low-cost irrigation facilities and water harvesting is recommended to enhance the practice of supplemental irrigation. Research efforts should as well be made to breed for drought, heat and flood tolerance in cassava. In addition, coupling area expansion with increasing availability of labour is advised, through the implementation of measures to minimize rural--urban migration. [ABSTRACT FROM AUTHOR]

The crop coefficient (Kc) is widely used for operational estimation of actual evapotranspiration (ETa) and crop water requirements. The standard method for obtaining Kc is via a lookup table from FAO-56 (Food and Agriculture Organization of the United Nations Irrigation and Drainage Paper No. 56), which broadly treats Kc as a function of four crop-growing stages. However, the distinctive physiological characteristics of overwintering crops, such as winter wheat (Triticum aestivum L.), which is extensively planted in the North China Plain (NCP), are not addressed in this method. In this study, we propose a stage-wise method that accounts for Kc variations for winter wheat at each critical phenological stage, thereby estimating Kc at finer temporal scales. Compared with the conventional FAO method, the proposed stage-wise method successfully captures the bimodal pattern in Kc time series for winter wheat, which is shown at both ten-day and phenological time scales. In addition, the accuracies of the proposed stage-wise Kc method and the FAO method were evaluated using micro-meteorological measurements of ETa collected at the Gucheng agro-meteorological experimental station in the NCP. Using a leave-one-out strategy, the evaluation revealed that the stage-wise method significantly outperformed the FAO method at both daily and critical phenological time scales, with root-mean-square errors in ETa for the stage-wise method and the FAO method being 0.07 mm·day-1 and 0.16 mm·day-1, respectively, at the daily time scale, and 0.01 mm·day-1 and 0.27 mm·day-1 at the critical phenological time scale. Generally, the FAO method underestimates ETa during the initial stage and overestimates ETa during both the development and mid-season stages. It is shown that the proposed stage-wise method is important for the water-stressed NCP where precision irrigation is highly desirable, especially during the critical phenological stages. Results from this study provide insight into accurate estimation of water requirements for winter wheat at phenological time scales. [ABSTRACT FROM AUTHOR]

The potential of optical remote sensing data to identify, map and monitor croplands is well recognized. However, clouds strongly limit the usefulness of optical imagery for these applications. This paper aims at assessing cloud cover conditions over four states in the tropical and sub-tropical Center-South region of Brazil to guide the development of an appropriate agricultural monitoring system based on Landsat-like imagery. Cloudiness was assessed during overlapping four months periods to match the typical length of crop cycles in the study area. The percentage of clear sky occurrence was computed from the 1 km resolution MODIS Cloud Mask product (MOD35) considering 14 years of data between July 2000 and June 2014. Results showed high seasonality of cloud occurrence within the crop year with strong variations across the study area. The maximum seasonality was observed for the two states in the northern part of the study area (i.e., the ones closer to the Equator line), which also presented the lowest averaged values (15%) of clear sky occurrence during the main (summer) cropping period (November to February). In these locations, optical data faces severe constraints for mapping summer crops. On the other hand, relatively favorable conditions were found in the southern part of the study region. In the South, clear sky values of around 45% were found and no significant clear sky seasonality was observed. Results underpin the challenges to implement an operational crop monitoring system based solely on optical remote sensing imagery in tropical and sub-tropical regions, in particular if short-cycle crops have to be monitored during the cloudy summer months. To cope with cloudiness issues, we recommend the use of new systems with higher repetition rates such as Sentinel-2. For local studies, Unmanned Aircraft Vehicles (UAVs) might be used to augment the observing capability. Multi-sensor approaches combining optical and microwave data can be another option. In cases where wall-to-wall maps are not mandatory, statistical sampling approaches might also be a suitable alternative for obtaining useful crop area information. [ABSTRACT FROM AUTHOR]

Agriculture is highly dependent on climate change, and Cyprus especially is experiencing its impacts on agricultural production to a greater extent, mainly due to its geographical location. The adaptation of farming to the effects of global climate change may lead to the maximization of agricultural production, which is an important and desirable improvement. The main aim of this paper is to rank and quantify the impacts of climate change on the agricultural sector of Cyprus, through a multi-round Delphi survey seeking a consensus agreement in a group of experts. A multidisciplinary group of 20 experts stated their willingness-to-pay for various impacts of climate change. By applying this method, the individual impacts of climate change on crop production and water resources were brought into the modeling effort on equal footing with cost values. The final cost impact estimate represents the total estimated cost of climate change in the agricultural sector. According to the results, this cost reaches EUR 25.08 million annually for the agricultural sector, and EUR 366.48 million for the whole country. Therefore, it is expected that in the seven-year programming period 2014–2020 the total cost of climate change on agriculture ranges from EUR 176 to EUR 2565 million. The most significant impacts are due to the increasing level of CO2 in the atmosphere and the burden of biodiversity and ecosystems. [ABSTRACT FROM AUTHOR]

This paper describes the combination of terrestrial vegetation observations from two sensors, providing a historical dataset used for an in-depth analysis of the corresponding spatio-temporal patterns. The Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) is an important variable suitable for regional to large-scale monitoring of climate impacts on vegetation. In this work, we create an extensive dataset of FAPAR using a 10-day product at ∼1 km resolution from September, 1997, to April, 2012, combining information from two sensors: the NASA/Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and the European Space Agency (ESA)/Medium Resolution Imaging Spectrometer Instrument (MERIS). The proposed methodology reduces the noise, fills the gaps and corrects for the spurious trends in the data, providing a time-consistent coverage of FAPAR. We develop a fast merging method and evaluate its performance over Europe and the Horn of Africa. [ABSTRACT FROM AUTHOR]

Data-driven technologies are employed in agriculture to optimize the use of limited resources. Crop evapotranspiration (ET) estimates the actual amount of water that crops require at different growth stages, thereby proving to be the essential information needed for precision irrigation. Crop ET is essential in areas like the US High Plains, where farmers rely on groundwater for irrigation. The sustainability of irrigated agriculture in the region is threatened by diminishing groundwater levels, and the increasing frequency of extreme events caused by climate change further exacerbates the situation. These conditions can significantly affect crop ET rates, leading to water stress, which adversely affects crop yields. In this study, we analyze historical climate data using a machine learning model to determine which of the climate extreme indices most influences crop ET. Crop ET is estimated using reference ET derived from the FAO Penman–Monteith equation, which is multiplied with the crop coefficient data estimated from the remotely sensed normalized difference vegetation index (NDVI). We found that the climate extreme indices of consecutive dry days and the mean weekly maximum temperatures most influenced crop ET. It was found that temperature-derived indices influenced crop ET more than precipitation-derived indices. Under the future climate scenarios, we predict that crop ET will increase by 0.4% and 1.7% in the near term, by 3.1% and 5.9% in the middle term, and by 3.8% and 9.6% at the end of the century under low greenhouse gas emission and high greenhouse gas emission scenarios, respectively. These predicted changes in seasonal crop ET can help agricultural producers to make well-informed decisions to optimize groundwater resources. [ABSTRACT FROM AUTHOR]

The demand for soybeans in Europe motivates breeders, researchers, and growers to find suitable cultivars to adapt and extend the soybean crop to improper climate areas. Weed control is a crucial aspect of crop technology in organic agriculture, but particularly for soybean crops. In laboratory conditions, the cumulative stress index for seedlings was determined to identify the susceptible cultivars. A field experiment with 14 soybean accessions and 2 sowing dates was conducted under organic farming conditions over the course of three years, from 2020 to 2022. Plant population density was found to be significantly (p < 0.01 and p < 0.1) negatively correlated to the degree of resistance to low temperature as well as infestation degree with weeds (for p < 0.05 and p < 0.1), with the exception of early sowing in 2021. Yield was significantly (p < 0.05, p < 0.01, p < 0.1) correlated with plant population density, with the exception of optimal sowing in 2022. Early sowing variants emerged with vigor in the first two years, breeding lines and registered varieties showed low input, and organic agriculture systems showed low yields in the drought years of 2020 and 2022. Although early sowing even in the first two years proved to be a practice that increased the cultivars' performance, in 2022, due to the long period of chilling stress in the field, this option had negative effects on yield due to the high weed frequency. Therefore, the early sowing strategy for the soybean crop in this particular case of non-irrigated conditions in a temperate continental area proved to be a risky practice. [ABSTRACT FROM AUTHOR]

Climate variability is a major threat to maize (Zea mays) crops in Colombia, posing a risk to food security and compliance with Sustainable Development Goals. Therefore, this study aimed to assess the physical vulnerability of maize crops to climate variability in the semi-arid region of the Department of Cesar, Colombia, using the AquaCrop-OS model. Specifically, the study evaluated the vulnerability of maize crops to three typical meteorological years (dry, intermediate, and wet) adjusted to the growth cycle in two semesters of the year (periods I and II). An analysis of 43 years of data (1980–2022) revealed that most years in the area can be classified as intermediate, whereas the number of wet years was higher than the number of dry years. However, under the intermediate typical meteorological year scenario, maize cultivation in the department of Cesar experienced severe drought conditions during periods I and II. The study's vulnerability curve showed an increasing rate within the yield loss index when the average water stress index was between 0.5 and 0.8 for period I. The rate of increase slowed when the index exceeded 0.9. For period II, the maize crop presented a lower degree of vulnerability, with 64% of the area experiencing a yield loss rate between 5% and 30%. The study also determined the required irrigation depth of water for optimal yields, which ranged from 70 to 160 mm during the growing season for all maize crop scenarios in the Department of Cesar. The results of this study can contribute to the consolidation of a database of physical vulnerability and threats of precipitation anomalies on regional and national scales. Overall, this study's evaluation of the physical vulnerability of maize crops can help producers develop better strategies to mitigate the impacts of climate variability and ensure regional food security. [ABSTRACT FROM AUTHOR]

Timely sowing and harvesting play important roles in agricultural production. The appropriate management decisions are necessary to cope with climate change and ensure high and stable crop yields. This study analyzed the effects of sowing date on the growth process of winter wheat and quantified the effects of climate resources and photothermal potential yield on theoretical yield at different stages of winter wheat. The analysis was based on the data from winter wheat interval sowing experiments conducted at the Hebei Gucheng Agricultural Meteorology National Observation and Research Station (Gucheng station) in north China (115°40′ E, 39°08′ N) during 2017–2019. The results showed that: (1) with the delay in sowing date, the growth process of winter wheat significantly advanced, the proportion of vegetative growth period significantly reduced (0.19% for per day delay), the proportion of reproductive growth period (RGP) significantly increased (0.12% for per day delay), and the prewintering light and temperature resources significantly reduced (12.2 °C·d accumulated temperature and 19.0 MJ·m−2 solar radiation for per day delay); (2) the theoretical yield of winter wheat showed a significant exponential relationship with the photothermal potential yield of the whole growth period: the minimum photothermal potential for yield formation was 26.6 t·ha−1, and the maximum theoretical yield was 12.6 t·ha−1; and (3) the wheat yield and yield stability were highest when the RGP photothermal potential yield was 16.0 t·ha−1 and the prewintering active accumulated temperature was 400 °C·d. This study also proposed a method to estimate the suitable sowing and harvesting dates to achieve high and stable yield of winter wheat, showing that the suitable sowing dates of winter wheat at Gucheng station from 1997 to 2021 ranged from 1 to 15 October, with no significant interannual variation; the suitable harvesting period ranged from 5 June to 10 July and showed a trend of gradual advance with the delay of the year. The results of the study provide a reference for sowing date adjustment of crops to adapt to climate change. [ABSTRACT FROM AUTHOR]

Climate change is expected to substantially reduce future crop yields in South Africa, thus affecting food security and livelihood. Adaptation strategies need to be implemented to mitigate the effect of climate change-induced yield losses. In this paper, we used the WEAP-MABIA model, driven by six CORDEX climate change data for representative concentration pathways (RCPs) 4.5 and 8.5, to quantify the effect of climate change on several key crops, namely maize, soya beans, dry beans, and sunflower, in the Olifants catchment. The study further investigated climate change adaptation such as the effects of changing planting dates with the application of full irrigation, rainwater harvesting, deficit irrigation method, and the application of efficient irrigation devices on reducing the impact of climate change on crop production. The results show that average monthly temperature is expected to increase by 1 °C to 5 °C while a reduction in precipitation ranging between 2.5% to 58.7% is projected for both RCP 4.5 and RCP 8.5 relative to the baseline climate for 1976–2005, respectively. The results also reveal that increased temperature and decreased precipitation during planting seasons are expected to increase crop water requirements. A steady decline in crop yield ranging between 19–65%, 11–38%, 16–42%, and 5–30% for maize, soya beans, dry beans, and sunflower, respectively, is also projected under both RCPs climate change scenarios. The study concludes that adaptation measures such as the integration of changing planting dates with full irrigation application and the use of rainwater harvest will help improve current and future crop production under the impact of climate change. [ABSTRACT FROM AUTHOR]

African countries such as Nigeria are anticipated to be more susceptible to the impacts of climate change due to large dependence on rainfed agriculture and to several uncertainties in the responses of crop production to climate change. The impacts of climate change on crop water requirements (CWR), irrigation water requirements (IWR), yields and crop water productivity (CWP) of rainfed maize in Ogun-Osun River Basin, Nigeria were evaluated for a baseline period (1986–2015) and future projection period (2021–2099) under Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 scenarios. For the baseline period, there is no significant trend within the variables studied. However, IWR is projected to increase significantly by up to 140% in the future period, while yield might likely decline under both scenarios up to −12%. This study shows that in the future periods, supplemental irrigation has little impact in improving yields, but an increase in soil fertility can improve yields and CWP by up to 80% in 2099. This paper offers useful information on suitable adaptation measures which could be implemented by stakeholders and policymakers to counterbalance the effects of climate change on crop production. [ABSTRACT FROM AUTHOR]

With food insecurity rising dramatically in Sub-Saharan Africa, promoting the use of sorghum, cowpea and cassava flours in staple food such as bread may reduce wheat imports and stimulate the local economy through new value chains. However, studies addressing the technological functionality of blends of these crops and the sensory properties of the obtained breads are scarce. In this study, cowpea varieties (i.e., Glenda and Bechuana), dry-heating of cowpea flour and cowpea to sorghum ratio were studied for their effects on the physical and sensory properties of breads made from flour blends. Increasing cowpea Glenda flour addition from 9 to 27% (in place of sorghum) significantly improved bread specific volume and crumb texture in terms of instrumental hardness and cohesiveness. These improvements were explained by higher water binding, starch gelatinization temperatures and starch granule integrity during pasting of cowpea compared to sorghum and cassava. Differences in physicochemical properties among cowpea flours did not significantly affect bread properties and texture sensory attributes. However, cowpea variety and dry-heating significantly affected flavour attributes (i.e., beany, yeasty and ryebread). Consumer tests indicated that composite breads could be significantly distinguished for most of the sensory attributes compared to commercial wholemeal wheat bread. Nevertheless, the majority of consumers scored the composite breads from neutral to positive with regard to liking. Using these composite doughs, chapati were produced in Uganda by street vendors and tin breads by local bakeries, demonstrating the practical relevance of the study and the potential impact for the local situation. Overall, this study shows that sorghum, cowpea and cassava flour blends can be used for commercial bread-type applications instead of wheat in Sub-Saharan Africa. [ABSTRACT FROM AUTHOR]

The accuracy prediction for the crop yield is conducive to the food security in regions and/or nations. To some extent, the prediction model for crop yields combining the crop mechanism model with statistical regression model (SRM) can improve the timeliness and robustness of the final yield prediction. In this study, the accumulated biomass (AB) simulated by the Agricultural Production Systems sIMulator (APSIM) model and multiple climate indices (e.g., climate suitability indices and extreme climate indices) were incorporated into SRM to predict the wheat yield in the North China Plain (NCP). The results showed that the prediction model based on the random forest (RF) algorithm outperformed the prediction models using other regression algorithms. The prediction for the wheat yield at SM (the period from the start of grain filling to the milky stage) based on RF can obtain a higher accuracy (r = 0.86, RMSE = 683 kg ha−1 and MAE = 498 kg ha−1). With the progression of wheat growth, the performances of yield prediction models improved gradually. The prediction of yield at FS (the period from flowering to the start of grain filling) can achieve higher precision and a longer lead time, which can be viewed as the optimum period providing the decent performance of the yield prediction and about one month's lead time. In addition, the precision of the predicted yield for the irrigated sites was higher than that for the rainfed sites. The APSIM-simulated AB had an importance of above 30% for the last three prediction events, including FIF event (the period from floral initiation to flowering), FS event (the period from flowering to the start of grain filling) and SM event (the period from the start of grain filling to the milky stage), which ranked first in the prediction model. The climate suitability indices, with a higher rank for every prediction event, played an important role in the prediction model. The winter wheat yield in the NCP was seriously affected by the low temperature events before flowering, the high temperature events after flowering and water stress. We hope that the prediction model can be used to develop adaptation strategies to mitigate the negative effects of climate change on crop productivity and provide the data support for food security. [ABSTRACT FROM AUTHOR]

Chitosan is a natural polymer with multiple applications in agriculture due to its ability to stimulate plant growth and resistance to both biotic and abiotic stressors. The impact of chitosan application on fruit production and quality was studied under greenhouse conditions in a summer crop in a semi-arid climate. Treatments consisted of the spray application of this biostimulant to the aerial plant part at different doses (0, 0.1, and 1 g L−1). Treatment with the lowest dose did not produce significant differences in yield (total production, number, and mean weight of the fruit), but increased the concentration of flavanones (trusses 2 and 7) and phloretin-C-diglucoside (truss 2) with regard to the control. On the contrary, the high-dose treatment increased the yield due to the rise in the number of fruits and produced a significant decrease in the concentration of vitamin C, lutein, β-carotene, and hydroxycinnamic acids (trusses 2 and 7); lycopene, phytoene, and phytofluene in truss 2; and flavanols and phloretin-C-diglucoside in truss 7. These results show the ability of chitosan to improve tomato yield or to enhance the accumulation of bioactive compounds (phenolic compounds) in fruit, depending on the dose. Results are explained on the basis of the ability of chitosan to activate yield and secondary metabolite production, the dilution effect due to an increased fruit load, and the interaction of chitosan with changing environmental factors throughout the crop cycle. [ABSTRACT FROM AUTHOR]

The overall goal of this study was to examine the impacts of climate change on the mean and variance of rice yields in China by using historical climate and crop data. An econometric model was established to estimate Just–Pope stochastic production functions and identify the potential impacts of climate change on the mean and variance of rice yields by type, keeping other factors constant. Based on the estimated production functions, the contribution rate of climatic factors to rice yield was then assessed by conducting the growth accounting of yields over the past 30 years. The results showed that both the mean rice yield and the yield variability were influenced by changes in the mean climate conditions and climatic variance. In the future, the impacts of climate change on rice yields will depend on local regions' present climatic conditions. The results have implications for improving the adaptation capacity of rice production. [ABSTRACT FROM AUTHOR]

Wheat yield variability will increase in the future due to the projected increase in extreme weather events and long-term climate change effects. Currently, regional agricultural statistics are used to monitor wheat yield. Remotely sensed vegetation indices have a higher spatio-temporal resolution and could give more insight into crop yield. In this paper, we (i) evaluate the possibility to use Normalized Difference Vegetation Index (NDVI) time series to estimate wheat yield in Latvia and (ii) determine which weather variables impact wheat yield changes using both ALARO-0 and REMO Regional Climate Models (RCM) output. The integral from NDVI series (aNDVI) for winter and spring wheat fields is used as a predictor to model regional wheat yield from 2014 to 2018. A correlation analysis between weather variables, wheat yield and aNDVI was used to elucidate which weather variables impact wheat yield changes in Latvia. Our results indicate that high temperatures in June for spring wheat and in July for winter wheat had a negative correlation with yield. A linear regression yield model explained 71% of the variability with a residual standard error of 0.55 Mg/ha. When RCM data were added as predictor variables to the wheat yield empirical model a random forest approach resulted in better results compared to a linear regression approach, the explained variance increased up to 97% and the residual standard error decreased to 0.17 Mg/ha. We conclude that NDVI time series and RCM output enabled regional crop yield and weather impact monitoring at higher spatio-temporal resolutions than regional statistics. [ABSTRACT FROM AUTHOR]

Myanmar is the country with the highest economic vulnerability (EV) to climate change in the Southeast Asian region. The dry zone of Myanmar occupies two-thirds of the agricultural lands and it has higher temperatures than elsewhere in the country. Climate change has severe impacts on agricultural production in this region. Moreover, changes in the precipitation patterns increase the likelihood of crop failures in the short-run and production declines in the long run. Therefore, an assessment of the economic impacts of climate change on crop production in the dry zone of Myanmar is very relevant. This paper examines the interactions between agriculture and climate and assesses the economic impact of climate change while using a Ricardian model. A cross-sectional survey covering three regions in the central dry zone: (Magwe, Mandalay, and Sagaing regions) was conducted, yielding a sample of 425 farmers. A non-linear relationship between climate indicators (temperature and precipitation) and revenue of land was found. The marginal effects were calculated by selecting economic and socio-demographic variables. The estimated marginal impacts suggest that the projected changes in temperature will affect the crop productivity of the region. The results also show that the temperature and rainfall components of global warming are both important. Predictions from three global circulation models all confirm that temperature is predicted to increase in all seasons. A significant marginal impact of increasing temperature on the net revenue of farm households was observed in the region. These findings call for policy makers and development planners to articulate the necessary climate change adaptation measures and mitigation options for reducing the negative impacts of climate change. Improved management and conservation of the available water resources could generate water for irrigation purposes and the dissemination of climate smart agricultural practices could lessen the negative impacts of climate change effects on agriculture in the dry zone of Myanmar. [ABSTRACT FROM AUTHOR]

The influence of regional climate change (CC) on agricultural production variance in the Mediterranean region has been discussed based on the assessment of the last decade. Most of the Mediterranean region has experienced frequent natural disasters, expanding population, increase in temperature, and increase in the surface of the Mediterranean Sea. Furthermore, the temperature in the Mediterranean area is rising 25% faster than the rest of the globe, and in the summer, it is warming 40% faster than the global average. Climate change can alter the food supply, restrict access to food, and degrade food quality. Temperature rises, changes in precipitation patterns, changes in severe weather events, and decreased water availability, for example, might all result in lower agricultural production. The fact that most Mediterranean nations rely on imported basic foodstuffs adds to the severity of the situation. Instability and insecurity of agricultural supply in the region might lead to massive population movement, transforming most Mediterranean nations into a global source of instability. Based on the experience of similar geographical locations, the article has highlighted the essential elements affecting crop productivity and the five domains of water, ecosystems, food, health, and security. Despite the region's complexity, the Mediterranean region has been offered an overall assessment that predicts the best strategy for the best solution. Such an attempt describes a methodical integration of scientific discoveries to understand better the combined hazards illustrated by the fact that CC has affected food production, resulting in widespread insecurity. Utilizing current technologies in agricultural production has been recommended to support regional nations in reaching higher yields. The significance of this study could be realized by mitigating climatic shocks through a sustainable food production system to accomplish development goals in vulnerable nations. [ABSTRACT FROM AUTHOR]

Evapotranspiration is an essential component of the hydrologic cycle, and its accurate quantification is crucial for managing crop water requirements and the operation of irrigation systems. Evapotranspiration data is key to hydrological and water management research investigations, including studying the impact of various climatic factors on crop water requirements. It has been estimated as the product of the reference crop evapotranspiration and crop coefficient. Daily reference crop evapotranspiration (ETo) can be determined by several methods and equations. The Food and Agriculture Organization Penman-Monteith equation requires complete weather data, whereas empirical equations such as Hargreaves and Samani, Valiantzas, Priestley-Taylor, Makkink, and Stephens-Stewart require limited weather data. This work evaluated different empirical equations for West Texas using the standard FAO Penman-Monteith method and calibrated their parameters to improve ETo estimation. Detailed meteorological data from West Texas Mesonet and high resolution (800 m) Parameter-elevation Regressions on Independent Slopes Model (PRISM) datasets from 2007 to 2016 were used. Daily ETo calculated using the standard FAO Penman-Monteith equation was compared to ETo estimated based on different empirical methods. The results show that all original empirical equations underestimated ETo. Calibration improved the performance of tested equations; however, there seems to be underestimation of ETo in the 8–16 mm range. Overall, the monthly Hargreaves and Samani equation with either original or calibrated values of its parameters outperformed all tested models. This equation seems to be a reasonable estimator, especially under limited weather data conditions. [ABSTRACT FROM AUTHOR]

The projected increase of the world's population, coupled with the shrinking area of arable land required to meet future food demands, is building pressure on Earth's finite agricultural resources. As an alternative to conventional farming methods, crops can be grown in protected environments, such as traditional greenhouses or the more modern plant factories. These are usually more productive and use resources more efficiently than conventional farming and are now receiving much attention—especially in urban and peri-urban areas. Traditionally, protected cropping has been predominantly practised in temperate climates, but interest is rapidly rising in hot, arid areas and humid, tropical regions. However, maintaining suitable climatic conditions inside protected cropping structures in warm climates—where warm is defined as equivalent to climatic conditions that require cooling—is challenging and requires different approaches from those used in temperate conditions. In this paper, we review the benefits of protected cropping in warm climates, as well as the technologies available for maintaining a controlled growing environment in these regions. In addition to providing a summary of active cooling methods, this study summarises photovoltaic (PV)-based shading methods used for passive cooling of greenhouses. Additionally, we also summarise the current humidity-control techniques used in the protected cropping industry and identify future research opportunities in this area. The review includes a list of optimum growing conditions for a range of crop species suited to protected cropping in warm climates. [ABSTRACT FROM AUTHOR]

Optimization of agronomic practices for cultivation of quinoa, a super food and climate resilient crop, is critical to obtain its maximum grain yield under the current scenario of climate change. In the present experimentation, we evaluated the appropriate sowing time of ten elite lines of quinoa, already screened from USDA germplasm. Seeds of each line were sown in the experimental area at Square No. 22, Block No. 5, Directorate of Farm, University of Agriculture, Faisalabad, Pakistan on 15 November, 30 November and 15 December during quinoa cultivation season of 2019–2020. Sowing time significantly affected the emergence percentage, days taken to anthesis, chlorophyll contents, sodium and potassium concentrations in leaf, plant height, stem diameter, number of leaves and leaf area, panicle length, grain yield and 1000-grain weight. Lines; PIA-922, PIA-924, PIA-928 and PIA-929 performed better under first sowing and produced higher grain yield as compared to other lines. Similarly, PIA-921, PIA-922, PIA-925 and PIA-932 produced maximum biomass and grain yield under second sowing date while in case of third sowing date, PIA-926, PIA-928, PIA-930 and PIA-931 were observed more responsive regarding growth and yield attributes. A diversified pattern of agronomic, growth and yield contributing attributes of quinoa lines was observed when cultivated under varying sowing dates. The collected data will be very informative for the breeders and agronomists during selection and variety development process in future. [ABSTRACT FROM AUTHOR]

Livestock farming is a livelihood activity and is critically important for the food and nutritional security of the majority of the population in West African countries, including Senegal. Nevertheless, livestock farming operates far below the optimum production potential, mainly due to demographical, biophysical, economic, environmental, and sociopolitical challenges. To address these issues, we conducted this review with an overall objective of characterizing different livestock farming systems and to identify challenges and opportunities to improve livestock production in West Africa through the broader perspectives from the case of Senegal. Pastoral, agropastoral, and off-land systems are the three major livestock production systems in this region, which are unique in terms of agroclimatology and degree of intensification and integration. The major challenges identified in livestock farming systems are lack of pasture and quality feed, scarcity of water resources, climate change, undeveloped breeding and management of livestock, poor marketing and trade, and socioeconomic constraints. Moreover, we contribute to the literature on crop-livestock farming in Senegal and West Africa by proposing plausible interventions to improve the productivity of the farming system to improve food and nutritional security. Concentrated efforts must be taken in co-designing effective management interventions for sustainable intensification of livestock sector in the region, considering site-specific approaches. [ABSTRACT FROM AUTHOR]

One percent of the global population requires a gluten-free diet. With concurrent global warming and population growth, it is increasingly necessary to optimize the use of ingredients from resilient crops, such as tapioca. Tapioca flour is used in low proportions in bread due to its lack of gluten. Sourdough fermentation can enhance the nutritional value of bread but also causes a sour taste. Propionibacterium freudenreichii subsp. globosum can reduce food acidity while synthesizing several nutrients, such as vitamin B12. Aquafaba is a known hydrocolloid and prebiotic. Therefore, the objective of this study was to test the sourdough fermentation of a composite bread based on tapioca and brown rice flour, cultured with Lactobacillus lactis and Propionibacterium freudenreichii subsp. globosum enriched in aquafaba. The bread quality was measured instrumentally (hardness, volume, moisture content) and with a semi-trained sensory panel (focus group). The co-fermentation of the Lactobacillus lactis and Propionibacterium freudenreichii subsp. Globosum produced palatable bread, improving the appearance, taste, and texture in comparison to the yeast-leavened recipe. This co-fermentation also enabled shorter production times, reducing it from 1 h to 30 min. The addition of the aquafaba further improved the bread appearance, texture, and volume, although a bitter tasting crust was reported. The co-fermentation of the tapioca–brown rice composite flour with Lactobacillus lactis and Propionibacterium freudenreichii subsp. globosum produced acceptable bread, which could provide a climate-resilient solution to food sustainability. The aquafaba addition further enhanced such improvements and the baking performance, offering sustainability in terms of nutrition, sensory quality, and price. [ABSTRACT FROM AUTHOR]

The southwestern regions of the Kingdom of Saudi Arabia (KSA) are geographically and agriculturally diverse. Over millennia, crop production in these regions has evolved to use renewable water resources sustainably. This study analysed environmental and crop production data for 58 governorates in KSA's four southwestern regions: Al Baha, Aseer, Jazan and Makkah. The biplot analysis generated six clusters of cropping systems: sorghum, cereals, dates, watermelon, vegetables and fruits, and mixed. The main biophysical factors shaping these systems are topography, altitude, rainfall, air temperature and soils. Sorghum, grown on more than half of the cultivated land, dominates the two main systems. Fruits (subtropical and temperate) and open field vegetables are important elements in most systems. The main challenge is combining a moderate use of water with greater crop diversity. Cereals consume relatively little water, but their dominance within the systems reduces overall diversity. Another important issue is the low-input technologies used to cultivate sorghum and other cereals. Landraces or older varieties are planted and little, if any, fertilizers and pesticides are applied. The introduction of sustainable intensification packages is needed, which can begin with making improved varieties accessible to farmers, promoting conservation agriculture, and integrated pest management practices. [ABSTRACT FROM AUTHOR]

Heat stress during flowering is a critical limitation for summer maize production. However, the incidence of heat varies with years and locations, and it poses a great risk to successful maize reproduction and kernel setting. Therefore, it is essential to provide a sound quantification of heat occurrence in relation to maize growth and development. Here, we analyzed the characteristics of heat occurrence based on climate data for over 60 years on Huaibei Plain, China. The effective accumulated temperature showed a slight interannual variation. The average maximum temperature ( T ¯ max ) during flowering was 32 °C–33 °C, which was approximately 2 °C higher than that over the whole growing season. The probability (P) for the daily Tmax > 33 °C during flowering was closer to 50% and this maximum temperature ranged between 33 °C and 37 °C. The five levels from normal to extreme heat for Tmax were defined. Across the six studied sites, the mild level heat stress accounted for most of incidents (P, 25–50%), followed by moderate (P, 13–25%) and severe (P, 0.5–13%), and the minimum for extreme heat stress (P, 0.5%). Four phases bracketing flowering during maize development were given, i.e., 1 week prior to anthesis, 1 week during anthesis, 1 week for anthesis-silking, and 1week post silking. There was a greater probability for heat stress incidents from anthesis to silking compared to the other developmental stages. Additionally, maize grain yield slightly increased with the increase in Tmax to 33 °C, but it declined as Tmax surpassed 33 °C. In conclusion, the pattern and characteristics of heat stress were quantified bracketing maize flowering. These findings assist to advise summer maize cropping strategies on the semi-arid and semi-humid Huaibei Plain, China or similar climate and cropping regions. [ABSTRACT FROM AUTHOR]

Africa is one of the regions with high mycotoxin contamination of foods and continues to record high incidences of liver cancers globally. The agricultural sector of most African countries depends largely on climate variables for crop production. Production of mycotoxins is climate-sensitive. Most stakeholders in the food production chain in Africa are not aware of the health and economic effects of consuming contaminated foods. The aim of this review is to evaluate the main factors and their degree of contribution to the high levels of mycotoxins in African foods. Thus, knowledge of the contributions of different factors responsible for high levels of these toxins will be a good starting point for the effective mitigation of mycotoxins in Africa. Google Scholar was used to conduct a systemic search. Six factors were found to be linked to high levels of mycotoxins in African foods, in varying degrees. Climate change remains the main driving factor in the production of mycotoxins. The other factors are partly man-made and can be manipulated to become a more profitable or less climate-sensitive response. Awareness of the existence of these mycotoxins and their economic as well as health consequences remains paramount. The degree of management of these factors regarding mycotoxins varies from one region of the world to another. [ABSTRACT FROM AUTHOR]

Understanding the effect of climate warming and technological progress on crop production systems is crucial for developing climate adaptation strategies. This study presents a methodological framework with which to assess the suitability of the double rice cropping system in Southern China and the effects of crop management and climate warming on its distribution. The results indicate that the isolated effects of climate warming have led to the northward and westward expansions of double rice northern limits over the past six decades and an increase in suitable areas by 4.76 Mha. Under the isolated effect of crop management, the northern limits of the medium- and late-maturity double rice changed significantly due to the increased accumulated temperature required caused by varietal replacement and planting date change, which moved an average of 123 and 134 km southward, respectively. A combined scenario analysis indicated that crop management could offset the effects of climate warming and push the northern limits southward, reducing the overall suitable area by 1.31 Mha. Varietal replacement and other crop management methods should also be appropriately considered in addition to climate warming to develop locally adapted agricultural management strategies. [ABSTRACT FROM AUTHOR]

The Guazuma crinita Mart. is a dominant species of great economic importance for the inhabitants of the Peruvian Amazon, standing out for its rapid growth and being harvested at an early age. Understanding its vertical growth is a challenge that researchers have continued to study using different hypsometric modeling techniques. Currently, machine learning techniques, especially artificial neural networks, have revolutionized modeling for forest management, obtaining more accurate predictions; it is because we understand that it is of the utmost importance to adapt, evaluate and apply these methods in this species for large areas. The objective of this study was to build and evaluate the efficiency of the use of a deep neural network for the prediction of the total height of Guazuma crinita Mart. from a large-scale continuous forest inventory. To do this, we explore different configurations of the hidden layer hyperparameters and define the variables according to the function HT = f(x) where HT is the total height as the output variable and x is the input variable(s). Under this criterion, we established three HT relationships: based on the diameter at breast height (DBH), (i) HT = f(DBH); based on DBH and Age, (ii) HT = f(DBH, Age) and based on DBH, Age and Agroclimatic variables, (iii) HT = f(DBH, Age, Agroclimatology), respectively. In total, 24 different configuration models were established for each function, concluding that the deep artificial neural network technique presents a satisfactory performance for the predictions of the total height of Guazuma crinita Mart. for modeling large areas, being the function based on DBH, Age and agroclimatic variables, with a performance validation of RMSE = 0.70, MAE = 0.50, bias% = −0.09 and VAR = 0.49, showed better accuracy than the others. [ABSTRACT FROM AUTHOR]

Complete water accounting (WA) and crop water productivity (CWP) analysis is crucial for evaluating water use efficiency (WUE). This study aims to evaluate the contributions of hydro-meteorological factors to the changes of WA and CWP and subsequent WUE based on the data from 2009–2020 in the Nile River Basin (NRB), East Africa (EA). The Mann-Kendall (MK) statistical test and Sen's slope estimator were applied to detect the trends of climatic factors, and the AquaCrop model was used to simulate the crop yields in response to water balance and consumption based on crop physiological, soil water, and salt budget concepts. For the years 2012 and 2019, the mean of climatic water deficit P − ETa was 71.03 km3 and 37.03 km3, respectively, which was expected to rise to ~494.57 km3 by 2050. The results indicated that the basin water budget was unbalanced due to the coupled impact of year-to-year hot and dry conditions and increase in water abstraction, an indication of water deficit or stress. CWP and WUE increased during the study period with different changing patterns. CWP was also found to correlate to the yield of major crops (p-value > 0.05). It was concluded that climatic factors influenced the crop yield, CWP, and WUE in the study area. Thus, the improvement of CWP and WUE should rely on advanced water-saving innovations. The findings of this study could help water managers to improve water productivity by focusing on water account potentials and creating regional advantages by deploying water in combination with surplus flow from upstream to downstream consumption. [ABSTRACT FROM AUTHOR]

Fusarium mycotoxins in cereals constitute major problems for animal and human health worldwide. A range of plant pathogenic Fusarium species that can infect cereal plants in the field are considered the most important source of mycotoxins, such as deoxynivalenol (DON), zearalenone (ZEA), T-2 toxin, and HT-2 toxin, in small-grain cereal crops in temperate climates. In this article, we (i) critically review the available knowledge on the impact of contrasting production systems (organic versus conventional) and specific agronomic parameters on the occurrence and concentrations of DON, ZEA, and T-2/HT-2 in small-grain cereals (wheat, oats, barley, and rye), and (ii) discuss Fusarium mycotoxin risks in the context of the need to develop more sustainable cereal production systems. Overall, the available evidence from studies of acceptable scientific quality suggests that the incidence and concentrations of Fusarium mycotoxin are lower in organic compared with conventional cereals. Specifically, 24 comparisons showed lower mycotoxin levels in organic production, 16 detected no significant difference, and only 2 showed higher levels in organic production. When the mean concentrations from all studies were compared, conventionally produced cereals had 62%, 110%, and 180% higher concentrations of DON, ZEA, and T-2/HT-2, respectively, than organic cereals. Overall, published studies on the effects of specific agronomic practices on mycotoxin levels suggest that diverse crop rotations and high soil organic matter content/biological activity are associated with a lower risk of Fusarium mycotoxin contamination, whereas (i) high mineral nitrogen fertiliser inputs, (ii) some fungicides and herbicides, and (iii) minimum or no tillage may increase the risks of Fusarium mycotoxin contamination in cereals. The management of Fusarium head blight and mycotoxins, therefore, requires a preventative, integrated, holistic agronomic approach. [ABSTRACT FROM AUTHOR]

Climate change is a serious threat to the livelihoods of rural communities, particularly in mountainous areas because they are very sensitive to such changes. In this study, we assessed the household determinants to climate change adaptation drawing from a case study of agricultural adaptation in the Mount Rwenzori area of South Western Uganda. The study identified the major adaptation practices that are adopted by farmers to cope with the impacts of climate change and using available on-farm technologies. A total of 143 smallholder farmers were sampled and interviewed using field based questionnaires, field observations, and key informant interviews. Data was cleaned, entered and analysed using SPSS and Stata software for descriptive statistics. Thereafter, a Multinomial logistic regression model was used to assess the drivers of farmers' choice for adaptation practices, factors influencing the choice of adaptation, and barriers. The major adaptation practices that were identified included; use of different crop varieties, tree planting, soil and water conservation, early and late planting, and furrow irrigation. Discrete choice model results indicated the age of the household head, experience in farming, household size, climate change shocks, land size, use of agricultural inputs, landscape position (location), and crop yield varied significantly (p > 0.05), which influenced farmers' choice of climate change adaptation practices. The main barriers to adaptation included inadequate information on adaptation methods and financial constraints, leading us to conclude that contextual adaptation practices are more desirable for adoption to farmers. Adapting to climate change needs support from government and other stakeholders, however the implementation is more successful when appropriate and suitable choices are employed. [ABSTRACT FROM AUTHOR]

Tomatoes are one of the most nutritionally and economically important crops in New Zealand and around the world. Tomatoes require large amounts of water to grow well and are adversely affected by drought stress. However, few studies have evaluated the physicochemical characteristics of commercial tomatoes grown under water stress conditions. Four tomato cultivars (Incas, Marmande, Scoresby Dwarf, and Window Box Red) were grown in a greenhouse under well-watered and drought stress conditions and the tomatoes were harvested when ripe. The physicochemical properties and antioxidant contents of the fruits were compared. There were significant differences between cultivars in quality characteristics--such as dry matter, total soluble solids, and pH parameters--but there were no differences in the quality characteristics between the two treatments of the fruits (p > 0.05); however, there were significant differences (p < 0.05) in the antioxidant compositions (lycopene, total phenolics, and flavonoids) and antioxidant activities (DPPH and ABTS) of the fruits of both cultivars and treatments. Overall, these results indicated that tomatoes increased their bioactive compounds without changing any quality characteristics when exposed to water stress conditions. [ABSTRACT FROM AUTHOR]

Industrial tomatoes are cultivated in about 4000 ha of the Pinios river basin (central Greece), providing significant income to the farmers. In this study, the water footprint (WF) of industrial tomatoes between planting and harvest was estimated in 24 different farms for three consecutive years. The selected farms were representative of the main agro-climatic zones and soil textural classes within the river basin. Green, blue and grey WF calculations were based on datasets of the experimental plots for each farm, including irrigation water volume, meteorological, soil, and crop yield data. The results showed that the WF of tomatoes ranged from 37 to 131 m3 water/ton tomatoes with an average of 61 m3/ton. The WF variation depended mainly on crop yield, local agro-climatic and soil conditions. The green, blue, and grey WF components averaged 13, 27 and 21 m3/ton, respectively. The results reveal the importance of WF in understanding how tomato production relates to the sustainable use of freshwater and pollution at local level. [ABSTRACT FROM AUTHOR]

In the context of climate change, agricultural managers have the imperative to combine sufficient productivity with durability of the resources. Many studies have shown the interest of recent satellite missions as suitable tools for agricultural surveys. Nevertheless, they are not predictive methods. A system able to detect summer crops as early as possible is important in order to obtain valuable information for a better water management strategy. The detection of summer crops before the beginning of the irrigation period is therefore our objective. The study area is located near Toulouse (southwestern France), and is a region of mixed farming with a wide variety of irrigated and non-irrigated crops. Using the reference data for the years concerned, a set of fixed thresholds are applied to a vegetation index (the Normalized Difference Vegetation Index, NDVI) for each agricultural season of multi-spectral satellite optical imagery acquired at decametric spatial resolutions from 2006 to 2013. The performance (i.e., accuracy) is contrasted according to the agricultural practices, the development states of the different crops and the number of acquisition dates (one to three in the results presented here). The detection of summer crops reaches 64% to 88% with a single date, 80% to 88% with two dates and 90% to 99% with three dates. The robustness of this method is tested for several years (showing an impact of meteorological conditions on the actual choice of images), several sensors and several resolutions. [ABSTRACT FROM AUTHOR]