Search Results (249)

Water deficiency and low water use efficiency severely constrain wheat yield in dryland regions. This study aimed to identify suitable tillage methods and straw management to improve dry matter production, grain yield, and water use efficiency of wheat in the dryland winter wheat–summer bean (hereafter referred to as wheat-soybean) double-cropping system. A long-term located field experiment (onset in October 2009) with two tillage methods—plowing (PT) and rotary tillage (RT)—and two straw management—no straw mulching (NS) and straw mulching (SM)—was conducted at a typical dryland in China. The wheat yield and yield component, dry matter accumulation and translocation characteristics, and water use efficiency were investigated from 2014 to 2018. Straw management significantly affected wheat yield and yield components, while tillage methods had no significant effect. Furthermore, the interaction of tillage methods and straw management significantly affected yield and yield components except for the spike number. RTSM significantly increased the spike number, grains per spike, 1000-grain weight, harvest index, and grain yield by 12.5%, 8.4%, 6.0%, 3.4%, and 13.4%, respectively, compared to PTNS. Likewise, RTSM significantly increased the aforementioned indicators by 14.8%, 10.1%, 7.5%, 3.6%, and 20.5%, compared to RTNS. Mechanistic analysis revealed that, compared to NS, SM not only significantly enhanced pre-anthesis and post-anthesis dry matter accumulation, and pre-anthesis dry matter tanslocation to grain, but also significantly improved pre-sowing water storage, water consumption during wheat growth, water use efficiency, and water-saving for produced per kg grain yield, with the greatest improvements obtained under RT than PT. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) analysis confirmed RTSM’s yield superiority was mainly ascribed to straw-induced improvements in dry matter and water productivity. In a word, rotary tillage with straw mulching could be recommended as a suitable practice for high-yield wheat production in a dryland wheat-soybean double-cropping system. Full article

The main soil type in the Sanjiang Plain of Northeast China, dryland albic soil is of great significance for studying nutrient distribution characteristics. This study focuses on 852 Farm in the typical dryland albic soil area of the Sanjiang Plain, using a combination of paired t-test, geostatistics, correlation analysis, and principal component analysis to systematically reveal the spatial differentiation of soil nutrients in the black soil layer and white clay layer of dryland albic soil, and to clarify the impact mechanism of plow layer nutrient characteristics on crop productivity. The results show that the nutrient content order in both the black and white clay layers is consistent: total potassium (TK) > organic matter (OM) > total nitrogen (TN) > total phosphorus (TP) > alkali-hydrolyzable nitrogen (HN) > available potassium (AK) > available phosphorus (AP). Both layers exhibit a spatial pattern of overall consistency and local differentiation, with spatial heterogeneity dominated by altitude gradients—nutrient content increases with decreasing altitude. Significant differences exist in nutrient content and distribution between the black and white clay layers, with the comprehensive fertility of the black layer being significantly higher than that of the white clay layer, particularly for TN, TP, TK, HN, and OM contents (effect size > 8). NDVI during the full maize growth period is significantly positively correlated with TP, TN, AK, AP, and HN, and the NDVI dynamics (first increasing. then decreasing) closely align with the peak periods of available nitrogen/phosphorus and crop growth cycles, indicating a strong coupling relationship between vegetation biomass accumulation and nutrient availability. These findings provide important references for guiding rational fertilization, agricultural production layout, and ecological environmental protection, contributing to the sustainable utilization of dryland albic soil resources and sustainable agricultural development. Full article

Analyzing the soil organic carbon (SOC) stock in dryland areas of southern Shanxi, particularly under the influence of fertilization and mulching conditions, is crucial for enhancing soil fertility and crop productivity and understanding the SOC pool’s resilience to future climate change scenarios in the region. In a long-term experimental site located in Hongtong County, Shanxi Province, soil samples were collected from the 0–100 cm depth over a nine-year period. These samples were analyzed to evaluate the impact of five treatments: no fertilization and no mulching (CK), conventional farming practices (FP), nitrogen reduction and controlled fertilization (MF), nitrogen reduction and controlled fertilization with ridge-film furrow-sowing (RF), and nitrogen reduction and controlled fertilization with flat-film hole-sowing (FH). The average annual yield of wheat grain, SOC stock, water-soluble organic carbon (WSOC), particulate organic carbon (POC), light fraction organic carbon (LFOC), mineral-associated organic carbon (MOC), and heavy fraction organic carbon (HFOC) stocks were measured. The results revealed that the FH treatment not only significantly increased wheat grain yield but also significantly elevated the SOC stock by 23.71% at the 0–100 cm depth compared to CK. Furthermore, this treatment significantly enhanced the POC, LFOC, and MOC stocks by 106.43–292.98%, 36.93–158.73%, and 17.83–81.55%, respectively, within 0–80 cm. However, it also significantly decreased the WSOC stock by 34.32–42.81% within the same soil layer and the HFOC stock by 72.05–101.51% between the 20 and 100 cm depth. Notably, the SOC stock at the 0–100 cm depth was primarily influenced by the HFOC. Utilizing the DNDC (denitrification–decomposition) model, we found that future temperature increases are detrimental to SOC sequestration in dryland areas, whereas reduced rainfall is beneficial. The simulation results indicated that in a warmer climate, a 2 °C temperature increase would result in a SOC stock decrease of 0.77 to 1.01 t·ha⁻¹ compared to a 1 °C increase scenario. Conversely, under conditions of reduced precipitation, a 20% rainfall reduction would lead to a SOC stock increase of 1.53% to 3.42% compared to a 10% decrease scenario. In conclusion, the nitrogen reduction and controlled fertilization with flat-film hole-sowing (FH) treatment emerged as the most effective practice for increasing SOC sequestration in dryland areas by enhancing the HFOC stock. This treatment also fortified the SOC pool’s capacity to withstand future climate change, thereby serving as the optimal approach for concurrently enhancing production and fertility in this region. Full article

The reduced N fertilization rate and N supplied by pea (Pisum sativum L.) residue may sustain subsequent spring wheat (Triticum aestivum L.) growth, yield, and quality. We examined the response of spring wheat growth, yield, and quality to cropping systems and N fertilization rates from 2012 to 2019 in the US northern Great Plains. Cropping systems were conventional till spring wheat–fallow (CTWF), no-till spring wheat–fallow (NTWF), no-till spring wheat–pea (NTWP), and no-till continuous wheat (NTCW), and N fertilization rates to spring wheat were 0, 50, 100, and 150 kg N ha⁻¹. Wheat plant density and straw yield were 13–100% greater for CTWF and NTWF than NTWP and NTCW in most years. Wheat grain yield and protein concentration were also 15–115% greater for CTWF and NTWF than other cropping systems at most N fertilization rates and years. In contrast, wheat grain test weight was 1–2% lower for CTWF and NTWF at most N fertilization rates and years. Increasing N fertilization rate mostly increased grain yield and protein concentration but reduced grain test weight for most cropping systems and years. Although CTWF and NTWF with or without N fertilization increased wheat yield and quality, these practices are not sustainable due to reduced annualized yield, soil health, and environmental quality. Because of similar or greater grain yields and test weights among NTWP with 50 kg N ha⁻¹ and NTWP and NTCW with other N rates, NTWP with reduced N rates may sustain spring wheat yield and grain size but not grain protein in the northern Great Plains. Full article

Drylands cover approximately 41% of Earth’s land surface, supporting about 500 million people and 45% of global agriculture. Groundwater is essential in drylands and is crucial for maintaining ecosystem services and offering numerous benefits. This article, for the first time, analyses and valuates the hydrological ecosystem services (HESs) provided by groundwater in a region of the Colorado River Delta in Mexico, an area with uncertain economic impact due to water scarcity. The main water sources are the Colorado River and groundwater from the Mexicali and San Luis Rio Colorado valley aquifers, both of which are overexploited. Valuation techniques include surrogate and simulated market methods for agricultural, industrial, urban, and domestic uses, the shadow project approach for water conservation and purification cost avoidance, and the contingent valuation method for recreation. Data from 2013 to 2015 and 2020 were used as they are the most reliable sources available. The annual value of HESs provided by groundwater was USD 883,520 million, with water conservation being a key factor. The analyzed groundwater uses reflect differences in efficiency and economic value, providing key information for decisions on governance, allocation, conservation, and revaluation of water resources. These results suggest reorienting crops, establishing differentiated rates, and promoting payment for environmental services programs. Full article

Efficient water management is critical for sustainable dryland agriculture, especially under increasing water scarcity and climate variability. Shanxi Province, a typical dryland region in northern China characterized by pronounced climatic variability and limited soil water availability, faces severe challenges due to uneven precipitation and restricted water resources. This study aimed to evaluate the spatiotemporal dynamics of soil water resources and their coupling with crop water demand under different hydrological year types. Using daily meteorological data from 27 stations (1963–2023), we identified dry, normal, and wet years through frequency analysis. Soil water resources were assessed under rainfed conditions, and water deficits of major crops—including millet, soybean, sorghum, winter wheat, maize, and potato—were quantified during key reproductive stages. Results showed a statistically significant declining trend in seasonal precipitation during both summer and winter cropping periods (p < 0.05), which corresponds with the observed intensification of crop water stress over recent decades. Notably, more than 86% of daily rainfall events were less than 5 mm, indicating low effective rainfall. Soil water availability closely followed precipitation distribution, with higher values in the south and west. Crop-specific analysis revealed that winter wheat and sorghum had the largest water deficits in dry years, necessitating timely supplemental irrigation. Even in wet years, water regulation strategies were required to improve water use efficiency and mitigate future drought risks. This study provides a practical framework for soil water–crop demand assessment and supports precision irrigation planning in dryland farming. The findings contribute to improving agricultural water use efficiency in semi-arid regions and offer valuable insights for adapting to climate-induced water challenges. Full article

Efficient weed detection in dryland spring wheat fields is crucial for sustainable agriculture, as it enables targeted interventions that reduce herbicide use, minimize environmental impact, and optimize resource allocation in water-limited farming systems. This paper presents HSG-Net, a novel lightweight object detection model based on YOLOv8 for weed identification in dryland spring wheat fields. The proposed architecture integrates three key innovations: an HGNetv2 backbone for efficient feature extraction, C2f-S modules with star-shaped attention mechanisms for enhanced feature representation, and Group Head detection heads for parameter-efficient prediction. Experiments on a dataset of eight common weed species in dryland spring wheat fields show that HSG-Net improves detection accuracy while cutting computational costs, outperforming modern deep learning approaches. The model effectively addresses the unique challenges of weed detection in dryland agriculture, including visual similarity between crops and weeds, variable illumination conditions, and complex backgrounds. Ablation studies confirm the complementary contributions of each architectural component, with the full HSG-Net model achieving an optimal balance between accuracy and resource efficiency. The lightweight nature of HSG-Net makes it particularly suitable for deployment on resource-constrained devices used in precision agriculture, enabling real-time weed detection and targeted intervention in field conditions. This work represents an important advancement in developing practical deep learning solutions for sustainable weed management in dryland farming systems. Full article

Returning straw and green manure to the field is a vital agronomic practice for improving crop yields and ensuring food security. However, the existing research primarily focuses on drylands and low-fertility paddy fields. A systematic discussion of the yield-increasing mechanisms and soil response patterns of medium- and long-term organic fertilization in subtropical, high-organic-matter paddy fields is lacking. This study conducted a six-year field experiment (2019–2024) in a typical high-fertility rice production area, where the initial organic matter content of the 0–20 cm topsoil layer was 44.56 g kg⁻¹. Four treatments were established: PK (no nitrogen, only phosphorus and potassium fertilizer), NPK (conventional nitrogen, phosphorus, and potassium fertilizer), NPKM (NPK + full-amount winter milk vetch return), and NPKS (NPK + full-amount rice straw return). We collected 0–20 cm topsoil samples during key rice growth stages to monitor the dynamic changes in nitrate and ammonium nitrogen. The rice SPAD, LAI, plant height, and tiller number were also measured during the growth period. After the six-year rice harvest, we determined the properties of the topsoil, including its organic matter, pH, total nitrogen, phosphorus, potassium, available phosphorus and potassium, and alkali hydrolyzable nitrogen. The results showed that, compared to NPK, the organic matter content of the topsoil (0–20 cm) increased by 6.36% and 5.16% (annual average increase of 1.06% and 0.86%, lower than in low-fertility areas) in the NPKS and NPKM treatments, respectively; the total nitrogen, phosphorus, and potassium content increased by 16.59%, 8.81%, and 10.37% (NPKS) and 6.70%, 5.12%, and 11.62% (NPKM), respectively; the available phosphorus content increased by 21.87% and 8.42%, respectively; the available potassium content increased by 47.38% and 11.56%, respectively; and the alkali hydrolyzable nitrogen content increased by 3.24% and 2.34%, respectively. However, the pH decreased by 0.07 in the NPKS treatment while it increased by 0.17 in the NPKM treatment, respectively, compared to the PK treatment. NPKS and NPKM improved key rice growth indicators such as the SPAD, LAI, plant height, and tillering. In particular, the tillering of the NPKS treatment showed a sustained advantage at maturity, increasing by up to 13.64% compared to NPK, which also led to an increase in the effective panicle number. Compared to NPK, NPKS and NPKM increased the average yield by 9.52% and 8.83% over the six years, respectively, with NPKM having the highest yield in the first three years (2019–2021) and NPKS having the highest yield from the fourth year (2022–2024) onwards. These results confirm that inputting organic materials such as straw and green manure can improve soil fertility and rice productivity, even in rice systems with high organic matter levels. Future research should prioritize the long-term monitoring of carbon and nitrogen cycle dynamics and greenhouse gas emissions to comprehensively assess these practices’ sustainability. Full article

Living mulch intercropping systems are considered as nature-based solutions with a low environmental footprint for managing weeds, improving biodiversity and agroecosystem sustainability. In drylands, however, they may increase intra/inter-specific competition for water, reducing crop productivity. We tested conservation tillage (TLG) carob plots with and without irrigation (TLG_irr; TLG_dry) vs. rainfed intercropping systems of carob and (i) thyme (Thymbra capitata; T-System) or (ii) clover (Trifolium squarrosum; C-System), strategically planted on the south (sun)-exposed soil side (SES) of carobs, to reduce soil temperature/evaporation. Carob water relations, productivity and environmental footprints were examined for three years under semi-arid, low weed-competition (Skarinou-SKR) and arid high weed-competition (Vrysoules-VRY) conditions in Cyprus. Carob yield efficiency (kg/m³) in SKR, was >27% higher for the T-System (p < 0.05; SES cover ca. 85%; year-3), matching a higher leaf water content (p < 0.001) compared to TLG_dry. The T-System reached 28% and 56% of TLG_irr yields during very dry and normal rainfall years; TLG_dry yields approached zero. For VRY, no negative impacts on carob leaf water, at 25% SES cover, were found. SKR’s C-System improved leaf water content (p < 0.05) for only one year. The T-System also outperformed TLG_irr and TLG_dry in terms of reducing irrigation needs and energy consumption, breaking new grounds for dryland agroforestry. Full article

Wheat productivity in dry regions of the world such as Central Asia and the Mediterranean is experiencing significant declines due to erratic weather events. Conservation agriculture (CA) has been promoted as a promising alternative for drylands to address climate-change-induced water scarcity and soil degradation. A long-term experiment in the Central Anatolian region of Türkiye compared CA and conventional tillage (CT) using diversified two- and four-year rotations. All rotations outperformed the wheat–wheat control, with the highest yields in wheat–fallow and wheat–lentil rotations. Four-year rotations generally yielded more than two-year ones under both CA and CT, except wheat–fallow and wheat–lentil, which matched four-year results. In two-year-rotations, yield differences between CA and CT were largest in wheat–wheat and wheat–lentil, with CA increasing yields by around 50% and 60% for chickpea and lentil, respectively. Chickpea and lentil also had a similar positive effect on wheat yield in four-year rotations. All rotations were more profitable under CA than CT, with chickpea and lentil rotations achieving the highest gross margin. Soil organic matter content was significantly greater under CA compared to CT within each two-year crop rotation. Our study clearly demonstrated the advantages of CA over CT in terms of production, soil quality and economics. Full article

This study aimed to address the challenge of monitoring and managing soil moisture in dryland agriculture with supplemental irrigation under increasingly extreme climate conditions. Using unmanned aerial vehicles (UAVs) equipped with hyperspectral sensors, we collected imagery of wheat fields on Kinmen Island at various growth stages. The Modified Perpendicular Drought Index (MPDI) was calculated to quantify soil drought conditions. Simultaneously, soil samples were collected to measure the actual soil moisture content. These datasets were used to develop a Gradient Boosting Regression (GBR) model to estimate soil moisture across the entire field. The resulting AI-based model can guide decisions on the timing and scale of supplemental irrigation, ensuring water is applied only when needed during crop growth. Furthermore, MPDI values and wheat spike samples were used to construct another GBR model for yield prediction. When applying MPDI values from multispectral imagery collected at a similar stage in the following year, the model achieved a prediction accuracy of over 90%. The proposed approach offers a reliable solution for enhancing the resilience and productivity of dryland crops under climate stress and demonstrates the potential of integrating remote sensing and machine learning in precision water management. Full article

Agricultural systems exhibit a large degree of within-field yield variability. We require a better understanding of the drivers of this variability in order to optimally manage croplands. We investigated drivers of sub-field spatial variability in yield for three crops (hard red winter wheat, Triticum aestivum L. variety Langin; corn, Zea mays L.; and proso millet, Panicum milaceum L.) usings a multi-year dataset from a dryland research farm in northeastern Colorado, USA. The dataset spanned 18 2.6–4.3 ha management units, over 4 years, and included high-resolution topographic data, densely sampled soil properties, and on-site weather data. We modeled yield for each crop separately using random forest regression and evaluated model performance using spatially blocked cross-validation. The topographic position index (TPI) and increasing percent sand had a strong negative effect on yield, while the nitrogen application rate (N) and total soil carbon had strong positive effects on yield in both the wheat and millet models. Remarkably, TPI had almost as large of an effect size as N, and outperformed other more commonly used topographic predictors of yield such as the topographic wetness index (TWI), elevation, and slope. Despite the size and quality of our dataset, cross-validation results revealed that our models account for approximately one-quarter of the total yield variance, highlighting the need for continued research into drivers of spatial variability within fields. Full article

Erratic rainfall and extended dry periods challenge forage production and livestock feed sustainability in dryland agriculture regions. This study investigated the effects of planting dates and genotype selection on the nutritive value and in-vitro dry matter degradability (IVDMD) of fodder radish genotypes in Midlands of KwaZulu-Natal, South Africa. The experiment followed a completely randomised design with three fodder radish genotypes (Endurance, Line 2, and Nooitgedacht) and five planting dates (December, January, February, March and May). After three months of growth in each planting date, crops were harvested, prepared and analysed for various nutritional parameters including crude protein, fibre content, and IVDMD. Results revealed that December had the highest crude protein (28–31%) across genotypes, while March plantings optimised total non-structural carbohydrates (13.31%) and metabolisable energy (6.64 MJ/kg). The Nooitgedacht genotype demonstrated improved performance, achieving higher IVDMD of 85.54% for leaves in December plantings and 77.51% for tubers in February plantings. Significant interactions between planting dates and genotypes were observed for ash, crude protein, and cellulose in leaves. In conclusion, these findings highlight the crucial role of planting date selection and genotype choice in optimising fodder radish production under dryland conditions, offering valuable insights for enhancing livestock productivity and supporting sustainable rural livelihoods. Full article

Accurate, real-time, and dynamic monitoring of crop planting distributions in hilly areas with complex terrain and frequent meteorological changes is highly important for agricultural production. Dual-polarization SAR has high application value in the fields of feature classification and crop distribution extraction because of its all-day all-weather operation, large mapping bandwidth, and easy data acquisition. To explore the feasibility and applicability of dual-polarization synthetic-aperture radar (SAR) data in crop monitoring, this study draws on two basic methods of dual-polarization decomposition (eigenvalue decomposition and three-component polarization decomposition) to construct time series of crop dual-polarization radar vegetation indices (RVIs), and it performs a full coverage analysis of crop distribution extraction in dryland mountainous areas of southeastern China. On the basis of the Sentinel-1 dual-polarization RVIs, the time-series classification and rapeseed distribution extraction impacts were compared using southern Hunan Province’s principal rapeseed (Brassica napus L.) production area as the study area. From the comparison results, $RV{I}_{3-c}$ performed better in terms of single-point recognition capability and area extraction accuracy than the other indices did, as verified by sampling points and samples, and the OA and F-1 score of rapeseed extraction based on $RV{I}_{3-c}$ were 74.13% and 81.02%, respectively. Therefore, three-component polarization decomposition is more suitable than other methods for crop information extraction and remote sensing classification applications involving dual-polarized SAR data. Full article

In light of the current global challenges, such as climate change, the overexploitation of natural resources, and increasing food demand, drought-tolerant forage crops present substantial potential for development in dryland regions. However, there is a notable gap in research that integrates yield improvement, nutritional quality enhancement, and resistance to pests and diseases in the production of forage crops in semi-arid areas. Therefore, selecting oat forage varieties that exhibit high yield, superior quality, and enhanced pest resistance can substantially advance the forage industry and animal husbandry in semi-arid regions. In this study, ten oat varieties, including both domestic and international cultivars, were cultivated in a semi-arid region (Weiqi town, Gansu Province) during the 2023–2024 growing season. A comprehensive analysis was performed to assess the yield, quality, and pest resistance of these varieties. All ten oat varieties successfully completed their growth cycles. Among them, Everleaf 126 exhibited a shorter plant height compared to the other varieties, measuring 103.32 cm and 115.14 cm over two years. However, its superior leaf area and tiller number led to the highest hay yields (11,819.33 kg/ha and 13,550.67 kg/ha) and seed yields (4913.20 kg/ha and 5242.33 kg/ha). Additionally, Everleaf 126 demonstrated significantly higher leaf–stem ratios (0.35 and 0.41), crude protein content (8.52% and 9.13%), and crude fat content (2.19% and 2.69%) relative to other oat varieties (p < 0.05). Furthermore, it showed the best resistance to powdery mildew (MR), red leaf disease (HR), leaf spot disease (MR), and aphids (R). The plant height of Kona was the lowest, measuring 81.22 cm and 87.16 cm, respectively, with the fewest number of tillers and the smallest leaf area. Baler II exhibited the lowest hay yield at 8770.10 kg/ha and 7898.33 kg/ha, as well as the lowest seed yield at 3409.33 kg/ha and 3323.90 kg/ha. Kona also had the lowest leaf–stem ratio (0.19 and 10.13) and crude protein content (5.74% and 6.58%), while exhibiting the highest neutral detergent fiber (NDF) and acid detergent fiber (ADF) values. Furthermore, Kona showed the poorest resistance to powdery mildew (MS) and leaf spot (MS). Finally, based on the comprehensive evaluation analysis of the membership function, in the semi-arid region, Everleaf 126 achieved the highest overall performance based upon a comprehensive evaluation, followed by Molasses and Longyan No.3. In comparison, Kona received the poorest performance. Full article