Search Results (2,297)

Long-term simplification of cropping systems and crop protection practices promotes increased weed infestation and may lead to yield decline. The aim of this study was to assess the effect of crop sequence systems and levels of crop protection on weed infestation, weed community diversity, and grain yield of winter wheat under long-term field experiment conditions. The research was conducted in a static field experiment established in 1967 in Bałcyny, Poland. Two cropping systems were analyzed, monoculture and a six-course crop rotation, combined with three levels of protection: no protection, herbicide, and herbicide + fungicide. Weed density, biomass, and species composition were evaluated, as well as diversity indices (Shannon–Wiener and Simpson) and grain yield. Monoculture significantly increased weed density and biomass, promoting the dominance of competitive species such as Apera spica-venti and Centaurea cyanus. In the crop rotation system, lower weed infestation, higher species diversity, and a more even community structure were observed. The application of herbicide effectively reduced weed infestation; however, it led to a decline in species diversity and an increase in the dominance of tolerant species. Grain yield was strongly negatively correlated with the level of weed infestation. The highest yields were obtained in the crop rotation system with full chemical protection, whereas monoculture resulted in a significant yield reduction regardless of the level of protection. These results highlight the key role of crop rotation and integrated crop protection in reducing weed infestation and stabilizing winter wheat yields. Full article

Maize is one of the most widely grown and used crops in the world. Nowadays, weather anomalies such as drought and sudden heavy rains due to climate change bring up serious challenges to maize production. One environmentally conscious approach that contributes to climate change resilience is cover cropping. In the production technology of corn-legume cover crops, corn as the cash crop was examined in two ways in a field small-plot experiment in four repetitions in randomized block design plots. In one case, the legume cover crops were sown as an interseeding cover crop in a corn monoculture; in the other case, the crop rotation agrotechnique was applied to what CCs could be included in the cereal-maize crop rotation after winter cereals. The experiment was set up in Vertisol and Chernozem. In all cases control treatment was included. Our results showed that pea vine and cowpea contributed to increased corn yield on both soil types and agrotechniques. White sweet clover cannot be recommended as a cover crop because this seemed too competitive with the cash crop. Field pea is recommended for the crop rotation agrotechnique. Trifolium species like Persian clover, red clover, and crimson clover show good adaptability to Vertisol. Full article

Rainfed wheat (Triticum aestivum L.) production in semi-arid regions is strongly influenced by precipitation variability, soil water availability, and crop management practices. This study evaluated the effects of nutrient management under uniform weed control on soil water dynamics, weed density, and grain yield of winter wheat grown under rainfed no-till conditions in southern Kazakhstan. Field experiments were conducted during the 2018–2021 growing seasons on gray soils characterized by low organic matter and limited nitrogen and phosphorus availability. Eight fertilization treatments, including phosphorus and nitrogen combinations and a micronutrient treatment, were arranged in a randomized complete block design. Soil moisture reserves, weed density, and grain yield were analyzed in relation to precipitation variability. Productive soil moisture reserves in the 0–100 cm layer at tillering (BBCH 21–25) ranged from 155 to 178.8 mm and were closely associated with overwinter precipitation. Balanced nitrogen–phosphorus fertilization reduced weed density from 38 plants m⁻² in the control to 16 plants m⁻² under the P₄₅N₇₀ treatment. Yield stability varied across dry, normal, and wet years, reflecting the influence of precipitation conditions on crop performance. Overall, the results suggest balanced fertilization in no-till systems contributes to improved resource use and more stable wheat production under variable precipitation. Full article

To support low-cost, non-destructive crop growth monitoring, this study systematically compared different vegetation indices, voxel sizes, and camera angles using a point cloud voxelization approach combined with a vegetation index weighted canopy volume index (CVM_VI) to assess aboveground biomass (AGB) in winter oilseed rape (Brassica napus L.). Field experiments were conducted from 2021 to 2024 at the Yangma Experimental Base of the Chengdu Academy of Agricultural and Forestry Sciences. Red, green, blue (RGB) imagery of oilseed rape was acquired using an unmanned aerial vehicle (UAV) during the following five key growth stages: seedling, bolting, flowering, podding, and maturity. Collected images were processed to generate point clouds, which were subsequently voxelized at four resolutions (0.03, 0.05, 0.07, and 0.1 m). CVM_VI was constructed by integrating vegetation indices (VIs) derived from the RGB data and the voxelized canopy structural information. Regression models were established between the CVM_VI values and field-measured AGB to estimate biomass. Model performance was evaluated using the coefficient of determination (R²), root mean square error (RMSE), and relative error (RE). There were strong correlations (r > 0.80) between the estimated and measured AGB across all voxelization treatments throughout the growth period. Among the 20 VIs tested, regression methods based on the blue green ratio index (BGI), color intensity index, blue red ratio index, vegetative index, and green red ratio index consistently showed superior estimation performance across three consecutive years, demonstrating their good applicability for estimating AGB in oilseed rape under varying agronomic conditions (different varieties, densities, and sowing dates). The cubic regression model CVM_BGI performed best under a 45° UAV camera angle, with the highest R² and lowest RMSE and RE (2021–2022: R² = 0.864, RMSE = 2414.18 kg/ha, RE = 14.8%; 2022–2023: R² = 0.754, RMSE = 2550.53 kg/ha, RE = 14.9%; 2023–2024: R² = 0.863, RMSE = 1953.61 kg/ha, RE = 22.9%). Since the estimation performance showed negligible differences among voxel sizes, and the 0.1–m voxel offered the smallest data volume and shortest analysis time, the CVM_BGI model with a 0.1–m voxel was selected as the preferred approach, providing a practical balance between estimation performance and processing demand. These findings highlight the application potential of point cloud voxelization technology for crop biomass estimation. This study proposes a novel, non-destructive, and efficient framework for estimating field crop AGB using low-cost UAV RGB imagery, facilitating the wider adoption of UAV technology in practical agricultural production. Full article

Rising production costs have increased interest in lower-cost, non-inversion crop establishment systems in Ireland, yet uptake remains relatively limited. Growers’ perceptions of relative performance of innovations compared to current practice are key determinants of adoption. We surveyed 154 Irish arable growers (77 plough-based, 59 min-till, 18 direct drill) to assess perceived performance of min-till and direct drill across multiple parameters relative to ploughing to identify potential barriers to adoption. Respondents rated impacts on Likert scales; analyses summarized response distributions and between-system differences. For example: >30% of min-till growers believed min-till winter cereal yields exceed ploughing, compared with 0% of plough and <10% of direct drill growers. Growers generally favoured their own establishment system, consistent with adoption theory. Potential barriers to non-inversion adoption included perceived lower establishment reliability, crop performance concerns (especially spring crops), and anticipated increases in weed pressure, herbicide reliance, and herbicide resistance development risk. Several perceptions diverged from the Ireland-relevant literature, revealing both knowledge gaps (notably establishment stability and winter/spring crop performance of establishment systems) and misperceptions (including establishment system on soil structure). Targeted research to address knowledge gaps, combined with focused, grower-centred knowledge exchange, is required to support evidence-based evaluation and sustainable adoption of establishment systems in Ireland. Full article

To investigate the thermal environments of three large-span plastic tunnels with different orientations and shapes (two east–west-oriented asymmetrical tunnels, WE15-5 and WE13-7, and one north–south-oriented symmetrical tunnel, NS10-10) under summer high-temperature and winter low-temperature conditions, we continuously monitored the air and soil temperature and conducted a comparative analysis of both under typical weather conditions. Computational fluid dynamics (CFD) simulations were used to further analyze the temperature and airflow fields. The results showed that, in summer, NS10-10 exhibited a superior ventilation and cooling performance with the most uniform temperature distribution, making it more suitable for summer crop cultivation. In winter, WE13-7 demonstrated optimal insulation and heat retention, with the highest minimum air temperatures and best daylighting capacity. CFD model validation showed a good agreement with the measured data (RMSE: 0.73–0.85 °C). These findings provide structural optimization recommendations for large-span plastic tunnels in different seasons. Full article

Despite stringent national clean air policies, severe PM_2.5 and ozone (O₃) pollution persists in some parts of China, notably the Sichuan Basin—a key economic zone in the southwest. High-resolution assessment of the health and crop impacts of these pollutants remains limited in this region. In this study, we developed a multi-source data fusion framework based on a machine learning model to reconstruct daily PM_2.5 and O₃ concentrations at 1 km resolution during 2015–2021. The model integrates ground observations, meteorological data, chemical transport model outputs, and satellite retrievals. The model performed robustly, achieving R² values of 0.91 for PM_2.5 and 0.64 for O₃. PM_2.5 exhibited a decreasing tendency after 2017, while O₃ showed interannual variability, with peaks in 2016 and 2018. Spatially, PM_2.5 was more concentrated in urban centers, whereas O₃ showed higher levels in western Sichuan and a banded pattern in the east. Seasonal patterns were also evident: PM_2.5 increased in autumn and winter due to meteorological and emission factors, while O₃ peaked in spring and summer, driven by photochemistry and high temperatures. Topography and emissions further shaped these distributions, with mountains in the west trapping O₃ and urban clusters exacerbating PM_2.5. Based on the reconstructed dataset, we further explored the potential impacts of pollutant exposure on human health and crop yields. The results provide a high-resolution dataset for understanding pollutant variability. Full article

Opuntia ficus-indica (L.) Mill., also named Cactus pear, is a crop widespread in many countries with Mediterranean and subtropical climates, where it represents a valuable source of food. However, in southern Europe, this fruit market is limited to a few months, from summer to autumn. The possibility to extend the ripening period of fruit is represented by the special pruning of the first bloom flush and consequent new development of late flowers and fruits. Extending the cultivation period would allow farmers to maximize the crop’s potential, thereby extending the Cactus pear market season throughout much of the year. In this study, conducted in southern Sardinia (Italy), progressive pruning was applied with the aim of evaluating the fruit characteristics in relation to this type of cultivation, also considering the weather conditions during the experimental period. Morphological traits and physicochemical compositions of fruit picked in four harvests during two sampling seasons from August 2022 to March 2023, and from August 2023 to March 2024 were compared. According to principal component analysis (PCA), most of the observed characters showed significant differences among harvest periods but also between the two seasons of cultivation (year of cultivation: r = 0.722 on PC1), suggesting that the meteorological trend strongly modulated fruit traits. Some fruit qualities were partially lost during the winter months, such as juice acidity and total soluble solids (TSS). October was the month with the highest TSS levels (13.5 ± 0.25), followed by August, January and March. On the other hand, juiciness and fresh weight remained unchanged or even improved in fruit harvested out-of-season. As observed in the redundancy analysis (RDA) a contribution of 54% due to weather variability emerged. In Particular, TSS levels, pH and juice dry matter were associated with high temperatures, solar radiation, and wind intensity. Wind speed was also moderately linked with betalain content. Moreover, high relative humidity was associated with lower pH values, higher water content, and higher fruit fresh weight. A significant difference was found between the two years in betalains content (80.0 ± 3.7 µg·mL⁻¹ in 2022–2023 and 28.2 ± 2.5 µg·mL⁻¹ in 2023–2024). The breakdown in the 2023–2024 season was likely due to the strong heat wave of July 2023 (up to 47 °C), which caused their partial degradation. In light of seasonal variability, this work provides some useful insights for future management of Cactus pear, also considering the possibility of usefully extending the period of cultivation and harvesting. Full article

A long-term positioning experiment was conducted from 2014 to 2021 to determine the appropriate tillage method for rapidly improving soil quality in reclaimed land. Four tillage methods were arranged before winter wheat sowing: deep tillage (DT), shallow tillage (ST), DT-ST alternate rotation (DST) and no tillage (NT). The results showed that: (1) with increasing reclamation years, ST, DT and DST had lower soil bulk density (SBD) and higher soil total porosity (STP) and soil capillary porosity (SCP) compared to NT. In the early stage of reclamation, ST had the lowest SBD and the highest STP and soil non-capillary porosity (NCP) in 0–20 cm soil layer, DT had the highest SCP and lowest NCP. In the 20–40 cm soil layer, DT has the lowest SBD and highest STP and SCP, followed by DST. In the late stage, SBD of each soil layer was NT > ST > DT > DST, while STP and SCP were NT < ST < DT < DST. (2) Different tillage methods influenced soil organic carbon (SOC) accumulation by affecting carbon sequestration rate (CSR). As opposed to NT, DT rapidly increased SOC of 0–40 cm soil layer in the early stages of reclamation, whereas DST facilitates maintaining higher SOC in the later stages. As compared to DT and DST, ST contributed more to SOC accumulation in surface soil, but less to SOC accumulation in deep soil. (3) Different tillage methods had various influences on SOC stratification ratio (SR). During the initial reclamation stage, NT had the lowest SR. Nevertheless, NT and ST maintained their high SR in the subsequent stage, whereas the SR of DT and DST experienced a notable decline due to the increase in SOC in deep soil. (4) It was observed that ST, DT and DST had higher grain yields compared with NT. The correlation analysis showed that DT improved soil properties by promoting SOC accumulation, increasing SCP and reducing NCP, thus increasing grain yield in the early stage of reclamation, while in the later stage of reclamation, DST can maintain better soil quality by reducing SBD and maintaining higher STP, SCP and SOC, and balanced the reasonable distribution of soil nutrients between the upper and lower soil layers by reducing SR of SOC, which helps the crop to maintain higher grain yields over time. Full article

Common wheat (Triticum aestivum ssp. vulgare) is one of the three major cereal crops cultivated worldwide and plays a key role in ensuring food safety. Adequate nitrogen supply is a key factor affecting the yield and functional properties of the grain of common wheat. Improving the efficiency of soil nitrogen use can be achieved through the application of appropriate mineral fertilizers and proper variety selection. The aim of this study was to determine the effect of residual nitrogen (N_res) remaining after maize cultivation on the functional properties of winter and spring wheat grain. The results of the present study clearly indicate that appropriate selection of the maize hybrid (preceding crop) and nitrogen fertilization strategy (residual nitrogen, N_res) can significantly enhance the antioxidant potential of grain in both forms of wheat (winter and spring). At the same time, our results highlight the practical importance of agronomic practices in improving the functional value of grain, both in terms of nutritional quality and health-promoting potential. Total polyphenol content in grain was stable, while antioxidant activity (ABTS⁺, DPPH) depended on genotype × fertilization interaction, particularly in winter wheat. These changes likely result from differences in polyphenol profile and the proportion of other antioxidants. Appropriate cultivar selection and nitrogen fertilization can enhance the antioxidant potential of wheat. No significant effect of either the preceding crop (maize) or its cultivar, or the form of nitrogen fertilizer, was found on the amino acid and total polyphenol content in winter and spring wheat grain. Population growth and the need to ensure adequate food supply highlight the importance of improving nitrogen management efficiency in agriculture by accounting for the amount and quality of residual soil nitrogen after the preceding crop. Full article

Asparagus (Asparagus officinalis L.) represents a high-value horticultural crop in Thailand with significant export potential; however, optimizing productivity in tropical environments requires a precise understanding of how cultivation practices and harvest seasons influence marketability. Here, a split-plot experiment arranged in a completely randomized design with three replications was conducted to examine how different crop methods and harvest seasons affect asparagus yield and quality in Lopburi Province, Thailand. The main plots were categorized by harvest season—summer, rainy, and winter—while the subplots included three crop methods: conventional, GAP, and organic. Summer produced the highest yield and asparagus with the greatest levels of total chlorophyll, phenolics, and DPPH radical scavenging activity compared to other seasons. Although the conventional methods yielded the most spears per plant, these spears contained higher levels of contaminants, including cadmium, lead, and nitrate. In contrast, spears from GAP and organic methods had higher phosphorus levels. However, no pesticide residues were found in any spear samples. Economically, the organic method had the shortest payback period, owing to lower production costs; despite a lower annual yield, stable market prices kept it profitable. In addition, organic soils had the highest levels of organic matter, nitrogen, and phosphorus. Overall, while conventional methods enhance the yield and certain qualities, organic farming, particularly when harvested in summer, yields the highest economic returns and the most sustainable system among those tested. Full article

Pea (Pisum sativum L.) is a multifunctional legume of growing importance in sustainable cropping systems. This study presents an integrative assessment of a forage pea variety across multiple agronomic functions under temperate continental conditions. Results from three environmentally comparable field trials were synthesized to evaluate (i) grain yield and protein traits, (ii) biomass production and nutrient accumulation in cover cropping systems, and (iii) effects on soil nitrate dynamics and maize (Zea mays L.) yield. Compared with vegetable- and dry-seed-type genotypes, the forage-type cultivar exhibited greater plant height and lodging tendency, moderate grain yield, and elevated protein content (28.8%), characterized by a legumin-dominated protein profile. As a winter cover crop grown in mixture with oat (Avena sativa L.), pea produced lower total biomass than rye (Secale cereale L.) but showed substantially higher nitrogen concentrations (2.93–3.01%), indicating enhanced nitrogen input potential. In crop rotation, pea-based treatments significantly affected soil nitrate distribution and maize productivity. Complementary resource use in pea-based systems enhanced biomass production, supporting forage and green manure functions while contributing to soil fertility and system stability. Its morphological and physiological adaptability enables integration into diverse production models, from intensive to regenerative systems. Overall, pea should be regarded not merely as a single crop, but as a strategic component of diversified farming systems aimed at increasing protein yield, optimizing inputs, improving soil quality, and strengthening the long-term sustainability of agroecosystems. Full article

Enhancing nitrogen use efficiency (NUE) in cereal crops is a major challenge for dryland systems that rely heavily on synthetic nitrogen (N) inputs. Microbial biostimulants have recently emerged as promising alternatives for cost-effective N inputs in wheat through foliar colonization and endophytic biological N fixation. Methylobacterium symbioticum strain SB23 (also known as BlueN or Utrisha N) is a pink-pigmented, obligately aerobic, Gram-negative, facultative methylotrophic bacterium demonstrated to potentially reduce N chemical fertilization and improve yields in various crops. A field trial consisting of large replicated 2.3 ha plots of Australian Prime Hard (APH) wheat cv. Rockstar was established in south central New South Wales, Australia, to evaluate the foliar application of M. symbioticum strain SB23 under both standard and reduced N regimes for winter wheat maturing in late spring. Application of the SB23 biostimulant significantly increased wheat leaf chlorophyll concentration at 30 and 60 days after application (DAA) and promoted biomass accumulation at 60, 90 and 120 DAA in contrast to the untreated control, with the strongest positive response under reduced N input. Specifically, the 75% N + biostimulant treatment improved biomass by up to 23% and grain yield by 14% relative to the reduced-N control, demonstrating potential supplemental fertility without yield loss. Correlation analyses revealed that mid-season chlorophyll was strongly associated with biomass and carbon assimilation (r = 0.87 and 0.84, respectively), while biomass at 60 DAA was highly correlated with grain spike weight (r = 0.81), suggesting a strong association of improved crop vigor and yield with inoculation. At harvest, SB23 enhanced biomass nitrogen accumulation and nitrogen use efficiency, with the 75%N + biostimulant treatment achieving the highest plant N uptake (25% above the reduced-N control) and the greatest partial factor productivity of nitrogen (51.8 kg grain kg⁻¹ N applied), while both 100%N treatments showed the lowest efficiency. Collectively, these findings suggest that Methylobacterium symbioticum SB23 improves NUE through enhanced crop performance thereby providing a supplementary N source and delivering a cost–benefit advantage of approximately A$170 ha⁻¹ under reduced N application. Full article

The accurate delineation of mega-environments (MEs) and the rigorous evaluation of test locations are critical for optimizing regional variety trial schemes, particularly when addressing unbalanced datasets from multi-year, multi-location wheat (Triticum aestivum L.) trials. This study aimed at refining the regional wheat trial framework in the Huanghuai Winter Wheat Region (HWWR) of China using an integrated BLUP-GGE biplot approach, which combines best linear unbiased prediction (BLUP) values with genotype main effect plus genotype-by-environment interaction (GGE) biplot analysis to account for temporal variability and experimental error. We systematically evaluated the BLUP-GGE biplot approach, focusing on its goodness of fit and its ability to resolve inter-location relationships. We further assessed test location representativeness, discriminating ability, and overall desirability via the BLUP-GGE biplot, and contrasted ME delineation outcomes between the traditional “which-won-where” polygon method and the test location clustering-based approach. The BLUP-GGE biplot explained 72.9% of total phenotypic variation, with all location vectors displaying positive correlations (maximum angle = 88.8°), confirming the ecological homogeneity of the target region and yielding robust evaluation results. Based on the ideal tester view, Puyang was identified as the most desirable location, followed by Zhumadian, Shangqiu, and Huixian, while Lianyungang and Suqian exhibited relatively poor comprehensive performance. MEs delineated by the “which-won-where” method showed strong inter-ME correlations and insufficient differentiation, whereas the location clustering-based method markedly enhanced inter-ME discrimination (maximum vector angle > 60°), stably partitioning the HWWR into three distinct MEs with clear cultivar–ME interaction patterns: ME1 (Lianyungang, Suqian, Fuyang, Suzhou, Guoyang, Huixian, Huai’an, Xinmaqiao, Huayin, and Yangling), ME2 (Luoyang, Xinxiang, Zhumadian, Shangqiu, Puyang, and Luohe), and ME3 (Baoji, Xuzhou, Yuanyang, Sheyang, and Xingyang). This study confirms the superiority of the BLUP-GGE biplot for analyzing unbalanced multi-year multi-environment trial data and validates a robust clustering strategy for ME delineation. The findings provide a scientific basis for optimizing wheat regional trial systems and facilitating precise cultivar deployment in the HWWR, and offer a reference for analogous studies on other crops or ecological regions. Full article

Food insecurity occurs due to the impact of climate change and intense global conditions. Thus, understanding crop farming plans and monitoring crop yields have become major tasks for decision makers. Previous work has applied remote sensing techniques and empirical methods to predict the yields and analyse the relationships between spectral indices and historical crop yield data. However, a limitation of these studies is that they do not extract the values of spectral indices by crop types when the testing area is regional with multiple farmlands and requires a crop classification process. This can cause inaccurate results when investigating the correlations between the yield and the spectral indices. This research develops a yield prediction framework with historical crop maps by means of unsupervised classification with zero ground truth using Sentinel-2 imagery to retrieve the values of spectral indices of winter barley. The extracted spectral indices and the meteorological and historical yield data in North Norfolk, UK, are implemented in 1D Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM) and CNN–LSTM for winter barley yield predictions. LSTM has outstanding performance overall and the best result approaches a Root Mean Square Error (RMSE) of 0.406 kg/hectare, a Mean Square Error (MSE) of 0.165 kg/hectare and a Mean Absolute Error (MAE) of 10.495 kg/hectare. The EVI in April, May and June is the most important feature in the LSTM model and shows strong positive correlation with the yield of winter barley. The developed framework with unsupervised crop classification and LSTM can be applied to multiple crop types and in different regions using opensource datasets, historical yields, spectral indices and meteorological data. Correlations between these datasets indicate that higher EVI and maximum and minimum temperature and sun hours at the germination and seedling growth stages increase the yields of winter barley, but excess Water Content (WC) in plants with a higher Normalised Difference Moisture Index (NDMI) from April to June leads to a decline in the yields of winter barley. Full article