Agriculture, as the largest consumer of freshwater, plays a crucial role in managing limited water resources. However, uncertainties in water supply, particularly in water-scarce regions, hinder further agricultural development. Balancing agricultural development with environmental sustainability is especially demanding in the Karkheh River Basin (KRB), western Iran. Traditional irrigation networks in the upper KRB are inefficient, exacerbated by unregulated water use and over-extraction. This study explores the Water Supply-Demand Balance (WSDB) dynamics under current cropping patterns in the semi-arid Honam sub-basin of the upper KRB. Time-series Landsat imagery and Machine Learning (ML) algorithms classified crop types and estimated major crop cultivation areas during 2019–2021. Regional Crop Water Requirement (ETcreg) and Regional Net Irrigation Requirement (INETreg) estimated the Regional Gross Irrigation Water Demand (GIWDreg), while inflow-outflow analyses determined Surface Irrigation Water Supply (SIWS). The study achieved high crop classification accuracy, facilitating precise water demand estimation across large-scale traditional irrigation networks. Results indicated the highest GIWDreg in 2020 (11.3 × 106 m3/year), driven by increased forage cultivation with crop water requirements (ETc) exceeding 1000 mm. That year also recorded the maximum SIWS (14.8 × 106 m3/year). The Water Scarcity Index (WSI) classified shortages as severe to extreme, indicating WSDB instability due to drought and cropping pattern shifts. This study highlights the necessity for government initiatives promoting water-efficient cropping to align agriculture with water availability. The proposed approach offers practical insights for policymakers seeking to optimize food security while ensuring sustainable water management in traditional irrigation networks, where cropping patterns are difficult to assess.

Agricultural monoculture negatively impacts soil quality, particularly in fragile soils that yield limited crop production and are highly susceptible to degradation. Increasing plant diversity in production systems can be an alternative for maintaining soil ecosystem services and increasing crop yields. This study investigated the influence of increased plant diversity on soil health and its impact on soybean and cotton yield in an Ultisol in the Brazilian savanna in Mato Grosso State, Brazil. Tested five rates of plant diversity after soybean harvest: (1) very low (VL), (2) low, (3) average, (4) long-term average and (5) high (integrated crop–livestock systems (ICLS)) were tested. Plant diversity improves the health of sandy loam soil, increases C and N fractions in particulate organic matter (POM-C and POM-N) and leads to differences in C utilization by the soil microbial community. High ICLS diversity raises total organic carbon content, being POM-C and POM-N, the labile fractions, more efficient to show changes in sandy loam soil, in the short term, over a period of three years. High diversity promoted yield gains of up to 251 % for cotton and 82 % for soybean in relation to VL plant diversity. Changes in soil microbial composition are able to partially explain crop yield in diversified production systems (R2 ranging from 0.51 to 0.80). Diversifying production components is a sustainable way to maintain biological functions and agricultural quality of loam sandy soil in the Brazilian Cerrado in Mato Grosso.

Changes in climate patterns have a significant impact on agricultural production. A comprehensive understanding of weather changes in arable farming is essential to ensure practical and effective strategies for farmers. Our research aimed to investigate how different fertilization interacts with environmental factors, examine their effects on wheat yield and varietal response over time, minimize nitrogen (N) fertilizer using alfalfa as a proceeding crop, and recommend an optimum N dose based on the latest weather conditions. A long-term experiment including 15 seasons (1961–2022) was studied, where a wheat crop followed alfalfa with different N applications. Our results indicated that the average temperature in the Caslav region has increased by 0.045°C per year, more significantly since 1987. Moreover, precipitation slightly decreased by 0.247 mm, but not significantly. The average November temperatures are gradually rising, positively affecting wheat grain yield. July precipitation negatively impacted grain yield only in years with extraordinary rainfall. Additionally, new wheat varieties (Contra, Mulan, Julie) yielded statistically more than the old variety (Slavia). Effectively managing nitrogen under various climate conditions is essential for promoting plant growth and reducing environmental N losses. The optimal N dosage was determined at 65 kg/ha N, resulting in an average yield of 9.1 t/ha following alfalfa as a preceding crop. Alfalfa reduces the need for N fertilization and contributes to sustainable conventional agriculture. Our findings will serve as a foundation for designing future climate change adaptation strategies to sustain wheat production.

Grazing is a crucial component of dairy farms across many regions of the world. This review explores challenges related to grazing infrastructure and opportunities for future improvement. Farmers who aim to increase pasture utilisation face heightened inter-animal competition necessitated by pasture restriction to achieve target post-grazing sward heights. Increasing the frequency of fresh pasture allocation beyond once per day has been observed to reduce milk production in primiparous animals, due to intensified competition for limited feed resources. Implementing grazing paddocks tailored for 24- to 36-hour allocations helps to mitigate inter-animal competition while concurrently preventing the grazing of fresh regrowth. Crucial to this approach is establishing farm roadway infrastructure that allows access to all sections of the grazing platform. However, the development of these roadway networks has often occurred without a comprehensive assessment of their impact on the efficiency of the dairy herd’s movement between grazing paddocks and the milking parlour. The efficiency of the dairy herd’s movement is most significantly influenced by the location of the milking parlour within the grazing platform. Extreme walking distances or challenging terrain on farm roadways may have an impact on milk production per cow. Factors such as farm roadway surface quality and width significantly influence cow throughput on farm roadways. Recent studies have highlighted inadequate roadway widths on many farms relative to their herd size, while surface condition may also be limiting cow throughput on these farms. Enhancing roadway width and surface condition of farm roadways may improve labour efficiency on commercial farms.

The concept of interaction classes (iClasses) for multi-environment trial data was introduced to address the problem of summarising variety performance across environments in the presence of variety by environment interaction (VEI). The approach involves the fitting of a factor analytic linear mixed model (FALMM), with the resultant estimates of factor loadings being used to form groups of environments (iClasses) that discriminate varieties with different patterns of VEI. It is then meaningful to summarise variety performance across environments within iClasses. The iClass methodology was developed with respect to a FALMM in which the genetic effects for different varieties were assumed independent. This was done for pedagogical reasons but it was pointed out that the accuracy of variety selection is greatly enhanced by considering the genetic relatedness of varieties, either via ancestral or genomic information. The focus of the current paper is therefore to extend the iClass approach for FALMMs which incorporate such information. In addition, a measure of stability of variety performance across iClasses is defined. The utility of the approach for variety selection is illustrated using a multi-environment trial dataset from the lentil breeding programme operated by Agriculture Victoria.

This study aimed to investigate vetch genotypes’ responses to moderate and severe drought stress and identify stress tolerance markers in arid conditions. Ten vetch genotypes (Vicia dassycarpa Ten., V. pannonica Crantz., V. michauxii Spereng., V. sativa-Ardebil, V. sativa-Dashtyar, V. sativa-Fereydonshahr, V. sativa-Mashhad, V. sativa-Semirom, V. sativa-Shahrekord and V. villosa Roth.) were cultivated under three water-deficit conditions: control, moderate and severe drought stress. These conditions represented maximum allowable depletion levels of 30, 50 and 85% of soil available water, applied after the six-leaf stage in the 2019–20 and 2020–21 growing seasons. The findings highlight the vetch's response to drought stress is influenced by stress severity and genotype. The result indicated a wide range of genetic diversity in agro-physiological traits among the studied vicia germplasm. Vicia dassycarpa Ten. shows highest straw yield and shorter days to flowering and maturity. Vicia michauxii Spreng. demonstrates high grain yield and advantageous traits like increased water content, photochemical efficiency of photosystem II, chlorophyll b, carotenoids and membrane stability index. It has lower soluble carbohydrate, DPPH (2,2-diphenyl-1-picrylhydrazyl) and proline content. Additionally, V. michauxii Spreng. exhibits superior agronomic traits such as more seeds per pod, per plant and higher 1000 seeds weight, serving as reliable markers for drought tolerance. The results emphasize V. dassycarpa Ten. for fodder and V. michauxii Spreng. for grain production in water-limited regions. Further research on gene expression related to drought tolerance traits should enhance our understanding of vetch.

Reliable seasonal weather forecasts are essential for irrigation management and crop yield prediction, particularly in regions with limited water resources. This study aimed to improve the usability of the North American Multi-Model Ensemble (NMME), an experimental real-time seasonal weather forecast system, for regional crop modelling and irrigation decision-making. Coarse resolution of NMME may introduce bias and uncertainty at regional/local scales. To address this, a statistical downscaling method with bias correction for both mean and variability was used to produce 1-km gridded daily weather projections for temperature and precipitation across the contiguous United States from a representative NMME model, the Canadian Coupled Climate Model version 4 (CanCM4). The daily surface weather and climatological summaries (DAYMET) data were used to calibrate the downscaled hindcast projections of CanCM4. The reliability of downscaled CanCM4 forecasts for local crop modelling was evaluated at lead times of up to six months using a calibrated DSSAT model at a research station in the semi-arid Texas Rolling Plains region. Cross-validation during the hindcast period demonstrated strong forecast skill, with R2 values of 0.72 and 0.71 for maximum and minimum temperatures, respectively. The precipitation forecast remained sensitive to extreme events, with seasonal and annual relative errors of 31 and 1 %, respectively. Crop yield predictions had a relative error of 9 %, and irrigation water requirements closely matched field observations, outperforming both raw CanCM4 and multi-model mean methods. The downscaling method used in this study significantly improved NMME data reliability, although the degree of improvement may vary with time and location.

Nitrogen (N) is the most significant nutrient affecting crop growth and development for all types of crops, except legumes. The goal of this study was to optimize the N level for cotton grown in a semi-arid environment to enhance growth and development, determine N status, and increase seed cotton yield and biomass. Two independent field experiments each three years in duration were conducted, from 2007 to 2009 (Exp.-I) and 2018 to 2020 (Exp.-II). Experiments were laid out in a randomized complete block design with three replicates. The N treatments in Exp.-I were comprised of 0, 40, 80, 120, 160, 200 and 240 kg N/ha, while treatments in Exp.-II were comprised of 0, 70, 140, 210 and 280 kg N/ha. A wide range of data sets for cotton traits were recorded, including canopy height, leaf area index, the N status of the leaf and stem, seed cotton yield and time-series biomass data. The higher N rates 240 and 280 kg N/ha performed better for all these traits. However, the highest leaf N contents were recorded for 210 kg N/ha. Based on these results, it is suggested that under semi-arid conditions, slightly higher rates than optimum or recommended N rates could be applied as a strategy by cotton growers for a higher seed cotton yield. The findings of this study may also increase profitability in other cotton-growing areas that have similar weather conditions.

Grazing management is an important component affecting pasture stability, but the underlying demographic mechanisms remain poorly understood in mixed-species systems. This three-year study investigated how grazing height (15 and 20 cm pre-grazing) and strategic spring defoliation (7 cm) influence stability in mixed pastures composed of complementary C3/C4 grasses (Lolium arundinaceum and Cenchrus clandestinus). Utilising demographic and tiller size/density relationship theories, we examined population dynamics to better understand pasture stability. The results indicated that height management significantly affected the demographic traits, with shorter grazing (15 cm) increasing tiller emergence and population density while reducing individual tiller weight (TW). In addition, higher tiller population density (TPD) and lower TW were observed in the shorter treatments. Despite these contrasting responses, the mixed pasture maintained consistent stability across treatments through compensatory relationships between tiller traits. The stability index remained close to 1 (0.956 ± 0.02) regardless of management, demonstrating robust demographic equilibrium. Individual species showed distinct seasonal stability patterns – L. arundinaceum dominating in winter and C. clandestinus in spring and summer – yet their complementary growth maintained year-round system stability. The self-thinning law effectively revealed stable size-density compensation across treatments, suggesting its utility for assessing mixed sward persistence. These findings demonstrate that mixed pastures can maintain demographic stability under varying grazing regimes through species complementarity and population compensatory mechanisms.

The study analysed corn harvested areas from 1960 to 2030, using data from the USDA open-access official dataset and 1000 autoregressive integrated moving average models. The global corn harvested area experienced a steady growth rate of 1.0 % in the 1960s, followed by a slight setback in the 1980s and a recovery in the 1990s. The early 2000s saw significant expansion, while the 2010s saw a slightly slower pace of 1.4 %. From 2020 to 2024, the global growth rate declined to 0.0 %, suggesting a potential shift towards a more stable or slower growth phase. The most likely scenario for the global corn area is an optimistic outlook with a 37 % likelihood of steady growth. China’s most likely scenario is a gradual expansion with a rate of 2.0 %. The United States’ most likely scenario suggests a neutral trend. Brazil has remarkable growth trajectories in its areas, reflecting land availability. Ukraine’s area by 2030 is projected to experience varying outcomes due to uncertainties in the agricultural landscape.

The objective of this study was to assess the fermentation profile, chemical composition, aerobic stability and taxonomic diversity of corn grain silages rehydrated with water or cactus pear. Two rehydration methods were tested: corn grain silage rehydrated with water (CW) and corn grain silage rehydrated with cactus pear (CCP), each subjected to four opening times (30, 60, 90 and 120 days). The experiment employed a 2 × 4 factorial completely randomized design (two rehydration methods and four opening times) with four repetitions, units 32 experimental units. pH values were higher in water-rehydrated corn grain silage compared to cactus pear-rehydrated silage at 60 (average of 4.78 and 4.33) and 90 days (average of 4.33 and 3.83). For NH3-N, CW surpassed CCP at 30 days (average of 0.73% and 0.63%) and 60 days (average of 1.09% and 0.74%), respectively. Regarding rehydration, CCP had a higher dry matter (DM) content at 30 and 60 days, while CW showed the highest DM content at 90 and 120 days. Initially, the microbiota of CW and CCP treatments differed, primarily in the abundance of the Weissella genus, more abundant in CCP. However, from 30 to 120 days, microbiotas in all treatments became taxonomically similar, with no significant differences. Both silage experienced an increase in bacteria of the Lactobacillus genus. The use of cactus pear for rehydration in ensiling rehydrated corn grain is viable, showing superior results for fermentation profile and aerobic stability compared to water rehydration. It is recommended to open the silo after 60 days of fermentation.

Elephant grass [Cenchrus purpureus (Schum.) Morrone] is a tropical forage grass widely used in ruminant feeding in tropical and subtropical areas, mainly in cut-and-carry systems due to is high potential for herbage accumulation. However, most common genotypes (tall genotypes) generally show an early stem elongation, which contributes to a rapid decline in the forage nutritive value. Dwarf elephant grass types usually present less stem elongation and may be considered an option for the production of high nutritive value forage in cut-and-carry systems. The aims of this study were to evaluate and explain variations in herbage characteristics and kinetics of in vitro gas production of irrigated elephant grass genotypes (two tall-types – Elephant B and IRI-381 – and two dwarf-types genotypes – Mott and Taiwan A-146 2.37) under two harvest frequencies (60 and 90 days) in the dry and rainy seasons of two years. Herbage characteristics varied among genotypes, harvest frequency and seasons. Dwarf genotypes showed better in vitro fermentation parameters with the advancement of maturity compared to the tall size genotypes. Harvesting tall genotypes at a higher frequency (60-day) contributed to improving the fermentation, while dwarf elephant grass maintained greater fermentation when less frequent harvests were adopted (90-day).

Soil health is essential for a resilient ecosystem. The European Union proposed a Soil Monitoring Law for a legal framework of soil health. This study proposes a way to assess the mineral soil health. A database of mineral soils containing <20% organic matter and consisting of 10 soil classes and 22 soil types was used. There were four altitudinal groups (HM [high mountains], LM [low mountains and high hills], LH [low hills], PL [low plains]), covering the vegetation/climate floors, two land uses (forestland and grassland combined and cropland) and three soil textures (coarse [CO], loamy [LO] and clayey [CL]). Both soil organic carbon (SOC)/clay ratios and observed per mean SOC (O/M SOC) ratios were calculated for 19 regions. For SOC/clay, the 1/13, 1/10 and 1/8 thresholds were used, whereas O/M SOC categories were grouped as ‘low’, ‘intermediate’, ‘high’ and ‘very high’ health. SOC/clay and O/M SOC ratios combined were used to characterize soil health. SOC sequestration depends on many factors that are specific for each pedo-climatic region and texture and so is the soil characterization as healthy or not healthy. The recommended simultaneous application of these two indicators revealed specific SOC content values as reference levels for good soil health, which decrease from the wetter climates towards the drier ones. SOC content considerably differed among pedo-climatic regions, and soil health should be compared within the same regions that have specific SOC sequestration conditions. Correlations between support points SOC values and the aridity index allow separation between ‘healthy’ and ‘non-healthy’ soil conditions for any climate, vegetation floor and land use.

To manage anaerobic digestion residues (digestate) sustainably, it is important to determine their agricultural properties. In the present study, the effects of two digestate fractions (solid and liquid) on processing tomato yield parameters, quality traits, health-related compounds and some fruit physiological disorders were evaluated. The solid and liquid digestate fractions were compared with chemically fertilized and unfertilized control to evaluate the potential of the digestate as a fertilizer. A 2-year experiment was conducted in a randomized complete block design, with three replications and using two tomato varieties: cv. ‘Arte F1’ and cv. ‘Zeplin F1’. The results indicated that (1) compared with chemical fertilizer, the solid digestate produced equal or even better results in terms of fruit size, yield parameters (solid digestate treatment increased the total fruit weight per plant by an average of 30.7, 8.2 and 22.4% in 2019 and 25.3, 14.2 and 17.9% in 2022 compared with control, chemical fertilizer and liquid treatments, respectively) and percentage of fruit affected by sunscald and blossom-end rot in both years; (2) use of liquid digestate led to similar or significantly higher fruit size, yield parameters and percentage of fruit affected by sunscald and blossom-end rot than control in both years and (3) use of both solid and liquid digestate fractions significantly maintained or improved fruit quality in terms of colour traits, pericarp thickness, dry matter content, total soluble solid content, titratable acidity, pH, vitamin C and antioxidant activity. However, the effects of solid and liquid digestate fractions varied with year and variety.

Cephalaria joppensis Rchb. (CJ) has recently been domesticated as a new forage crop in Israel. Feeding trials with dairy cows and sheep have shown that CJ silage can replace wheat silage for these animals. The current work tested the effect of row spacing on the growth, yield, chemical composition and digestibility of CJ for forage. Two field trials were performed at a research farm in Acre to test three row spacings: (T1) 16 cm between rows (narrow row spacing), (T2) pairs of adjacent (16 cm apart) rows with 32 cm spacing between pairs (alternated row spacing) and (T3) 32 cm between rows (wide row spacing). T1 row spacing had the advantage of a better area coverage rate, which may be beneficial at the beginning of growth, reflected by the rapid establishment of the plants in the field, as well as in the competition with weeds. The growth rate was more significant in T2 and T3 row spacings. In the first year, a higher yield was obtained for T2 and T3 row spacings; in the second year, no differences in yield were found among the row spacing treatments. Row spacing did not affect the plant’s digestibility or chemical nutrition for ruminants. There was no uniformity in plant quality among the cultivars between the two years. Thus, we should define the phenological stages of Cephalaria joppensis and their relationship to nutritional quality at different sites having different climate conditions, in both small and semi-commercial plots.

The facilities where the livestock carry their production cycle must have as their main characteristic the control of the influence of variation of environmental factors on the animals, which can be controlled through the use of different ventilation systems. In this way, the objective of this research was to evaluate the influence of different conditioning systems in the swine farrowing house. Three treatments were tested in a farrowing house located in Parana, Brazil: refrigerated ventilation (T1), forced ventilation (T2) and natural ventilation (T3), on 12 females with 11 piglets each. The climatic parameters evaluated were temperature, velocity and relative humidity of the air. For the females were analysed the parameters: surface temperature (laser thermometer and thermal image), average weight and feed conversion at the end of lactation; and for the piglets: surface temperature (thermal image), average weight and weekly feed conversion. The data were interpreted statistically by analysis of variance and Tukey’s test with 5% probability of error, using the program SAS (2008). The use of the refrigerated ventilation system decreased the temperature of the air and the superficial temperature of the females, without affecting the comfort of the piglets. There was no difference in the productive indexes of the animals, thus other aspects of the production chain could be explored to reflect a higher financial gain.

The presence of excessive arsenic (As) in paddy fields poses a significant risk to human health due to its accumulation in rice grains. However, the current level of As in Sri Lankan paddy fields remains unclear. Therefore, this research aims to assess the distribution of exchangeable As concentration and investigate the effects of agro-climatic zones (ACZs), soil orders and water sources on exchangeable As concentration in Sri Lankan paddy fields. For this purpose, 7,154 soil samples were collected from paddy fields using a stratified random sampling method representing six ACZs, six soil orders and three water sources. Arsenic extraction was made using 0.01 M CaCl2 followed by the detection with inductive coupled plasma mass spectrophotometry. The concentration of exchangeable As ranged from 0.01 to 392.9 µg/kg with an average of 24.6 µg/kg. Samples from the Low-country Wet zone exhibited higher exchangeable As levels compared to those from the Low country Dry zone (P < 0.05). Among soil orders, Histosols, Inceptisols and Ultisols showed higher exchangeable As concentrations than Alfisols and Vertisols (P < 0.05). Rainfed paddy fields had higher exchangeable As compared to the fields with access to supplementary irrigation. Additionally, exchangeable As concentration was inversely correlated with soil pH and paddy grain yield (P < 0.05). The observed variations in soil-As concentration across ACZs, soil orders and water sources highlight the need for climate, soil order and water source-specific strategies to mitigate further accumulation of As in paddy fields.