Extensive damage to over 1000 plant species, including food crops, oil and industrial crops, vegetables, fruit trees, ornamentals, fodder species and weeds, has been caused by emerging phytoplasma-mediated diseases, thereby posing significant threat to global food security. Multiple factors, including environmental changes, invasion pathways, vector transmission and the emergence of new pathogen lineages, contribute to the spread of these diseases. Effective management requires stable, long-term strategies to safeguard plant health. Key approaches include comprehensive loss assessments, integration of climate change impacts, predictive modelling, enhanced disease surveillance, and improved detection techniques targeting phytoplasmas. This review highlights phytoplasma-associated plant diseases, emerging pathogen threats, and the factors facilitating their spread, alongside methods for surveillance and detection. In addition, case studies and global collaborative efforts are discussed. Finally, we outline future research priorities aimed at improving the management of phytoplasma-induced plant diseases.

Water and light are essential resources for crop development, and their limitations can significantly affect agricultural productivity. While irrigation systems are widely used to mitigate water scarcity, the role of nighttime artificial lighting in open-field conditions remains an emerging research area. This review explores the potential of nighttime light supplementation as a crop management strategy by analysing its physiological, morphological, and biochemical effects on plants. A key question addressed is whether supplemental lighting can enhance crop productivity in the field and under which conditions this approach is most effective. We examine which crops are more likely to benefit from artificial lighting based on their light limitations and physiological responses. Additionally, we discuss whether alternative agronomic practices, such as planting arrangements and canopy management, could achieve similar benefits without artificial light supplementation. The review also considers how the timing and spectral composition of supplemental light influence plant development. While continuous or nighttime lighting may alter physiological processes, it remains unclear whether these changes are beneficial or detrimental to productivity. Studies on light penetration, particularly the role of green and far-red wavelengths, suggest that spectral composition can impact plant morphology and light-use efficiency, raising questions about optimal lighting strategies. Finally, we address the feasibility of large-scale nighttime lighting in agriculture by discussing energy demands, potential environmental impacts, and economic viability. While preliminary studies suggest promising physiological responses, experimental validation under field conditions is still needed to determine whether this technology represents a profitable and sustainable investment.

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.

A growing demand for wheat as a staple crop leads to an expansion of its production. The consequence is land use change and short rotations for wheat. But wheat grown in short rotations causes yield decline. To secure future food supplies, a deeper understanding of the physiological processes contributing to this yield reduction is needed. Therefore, a three-year data set from a long-term field trial in Northern Germany was analysed to investigate the impact of crop rotational position (CRP) (wheat grown in the first [W1] and in the third [W3] year in self sequence after break crop) in combination with three genotypes and four rates of nitrogen (N) fertilizer on intercepted radiation by the canopy (Q), radiation use efficiency (RUE), grain yield and yield components. All genotypes showed a reduction of Q, RUE and yields in W3. The focus was further set on differences in yield formation pre- and post-anthesis. This revealed a significant interaction between CRP and genotype. An overall reduction in intercepted radiation pre-anthesis as well as in kernels/m2 in W3 suggested, that yield formation under adverse pre-crop conditions was rather ‘source limited’. A possibility to compensate this limitation might be a prolonged phase of radiation interception post-anthesis.

Pruning and nutrient supply after pruning are crucial to restore growth and productivity of old, unproductive coffee trees. The effect of pruning type (stumping, heavy pruning and light pruning) and fertiliser rate (100, 140, 180 and 220 g nitrogen, phosphorus and sulphur (NPS) mixed fertiliser per tree per year) on coffee yield and yield components and fertiliser agronomic efficiency (AE) was studied in southwest Ethiopia to identify the best pruning type and fertiliser rate combination for high crop productivity and AE. The experiment was conducted in a split-plot design with three replicates, where pruning type was the whole-plot factor and fertiliser rate was the subplot factor. Both main and interaction effects of pruning type and fertiliser rate on response variables were significant. Stumping and heavy pruning showed a much higher number of primary branches and fruiting nodes per tree than did light pruning. The 100 g fertiliser rate showed a significantly higher number of verticals and fruiting nodes per tree, yield and AE than did the other rates. Besides, the combination of heavy pruning and 100 g, stumping and 220 g, and stumping and 100 g provided a much higher number of fruiting nodes per tree, yield and AE; number of fruiting nodes per tree, canopy diameter and yield; and yield and AE, respectively than others. These findings show the importance of stumping and heavy pruning each combined with 100 g NPS fertiliser for renewing coffee productivity and maximizing AE in the study area.

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.

Sugar beet root damage at harvest promotes sucrose losses of circa 0.1 – 0.4 % day–1 in storage. However, root response to environmental stresses at harvest and their consequential rates of damage are not known. We investigated the effects of temperature and water stress at harvest on root resilience to damage and tissue strength. Water (irrigated to field capacity and non-irrigated) and temperature (cold and mild) treatments were imposed on physiologically mature sugar beet plants for seven weeks prior to and for three days after harvesting, respectively. Water status at harvest significantly affected relative water content (RWC) (p < 0.001), root weight (p < 0.001) and root width (p < 0.001). RWC was positively correlated to surface damage (R2 = 0.43, p = 0.02), root tip damage (R2 = 0.42, p = 0.03), tissue compression (R2 = 0.41, p = 0.05) and tissue puncture (R2 = 0.46, p = 0.01). Tissue damage was not affected by root tissue temperature of 4 °C compared to 12 °C. We conclude that sugar beet damage at harvest is not influenced by root temperatures over the range commonly observed in the UK and temperate production areas. However, higher water status at harvest, such as would be observed in a wet season, increases root tip and surface damage. These findings will help to inform optimum harvesting conditions to minimize sugar loss from the sugar beet crop.

Crop establishment system choice is crucial for growers, with various options differing in tillage type, depth and intensity. In Ireland, plough-based establishment dominates, but interest in and adoption of non-inversion systems is growing. These systems have proven successful in drier climates, where they evolved, but their performance under wetter Atlantic-influenced conditions is less studied. Limited research indicates challenges such as increased grass weed pressure, inconsistent yields, poorer crop establishment and reduced suitability for spring cropping. Additionally, the suitability of conventional replicated trials for extrapolating performance to farm level is frequently questioned for systems-type research. This research combines two complementary studies: a replicated field trial and detailed on-farm studies. The performance of wheat grown following a break crop in plough, min-till and direct drill systems was evaluated using both methods over three seasons. In the replicated trial, where management and input use were consistent across treatments, variation was recorded in plant densities and growth with only minor effects on yield. In contrast, the on-farm study, where management and input use varied between systems, showed no variation in plant densities and growth but did reveal significant yield differences. These were associated with input use and establishment system. The on-farm study provided valuable insight into the range of performance of these systems in commercial settings. However, it was less effective at isolating which specific components were responsible for the observed performance differences between systems.

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.

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.

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.

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.

A meta-analysis was conducted to evaluate the effects of whey protein supplementation on growth performance, nutrient digestibility, blood parameters and carcase quality in broiler chickens. The dataset was compiled from studies published between 1964 and 2025, following the PICO framework, which included the following components: population = broiler chickens; intervention = various whey products (types of whey, inclusion methods and different inclusion levels); comparison = control versus treatment; and outcome = growth performance, nutrient digestibility, carcase traits, humoral immunity, antioxidant properties, intestinal morphology and microbiota composition. Overall, the inclusion of whey protein in broiler diets significantly improved average daily gain, feed intake, breast percentage and villus height (g’ > 0.500; P < 0.001). In conclusion, this meta-analysis highlights the strong potential of whey protein as an alternative protein source in poultry nutrition.

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.

Winter barley is mainly grown in Europe. Before new varieties are recommended for cultivation, they undergo evaluation in breeding and variety trials. Based on the results of these trials, the stability and adaptability of promising new lines or varieties are assessed. In the present study, based on results from post-registration trials, we compared varieties grown in the 2020/21, 2021/22 and 2022/23 seasons. We fitted two Bayesian mixed models and assessed the stability of the varieties using the posterior estimates of variance components from the preferred model. We also used Bayesian probabilistic methods to recommend the best varieties. Using the probabilistic methods, we identified the varieties that were the most stable and had the highest yield in the barley post-registration trials. The varieties Melia, Mirabelle and Zenek were shown to be the three most stable and highest yielding. Furthermore, these three varieties had the highest joint probability of superior performance and stability. This study demonstrates that probabilistic methods within a Bayesian framework are a powerful tool for recommending the best winter barley varieties. The R-codes for both models are provided in a Supplement.