Search Results (2,252)

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

Background: The implementation of advanced agronomical strategies, including the use of antitranspirant, in order to mitigate the negative effects of environmental stress, particularly heat stress on plants, has become a focal area of research in the Mediterranean basin. This region is characterized by hot and dry summer that affects plant physiology. Methods: The experiment was carried out in Sicily (South Italy) on 12-year-old avocado cv. Hass grafted onto Walter Hole rootstock. Two subplots each of forty homogenous trees were selected and treated (1) with calcium carbonate (DECCO Shield^®) and (2) with water (control) at the following phenological phases: 711, 712 and 715 BBCH. The climatic parameters were recorded throughout the year. Physiological measurements (leaf transpiration, net photosynthesis, stomatal conductance, leaf water potential) were measured at 105, 131 and 168 days after full bloom. Fruit growth was monitored, and physico-chemical analyses were carried out at harvest. Results: The antitranspirant increased photosynthesis and stomatal conductance and reduced leaf transpiration (−26.1%). Fruit growth rate increased during summer, although no morphological and qualitative difference was observed at harvest. PCA highlighted the positive effect of the calcium carbonate on overall plant physiology. Conclusions: Antitranspirant foliar application reduced heat stress effects by improving physiological responses of avocado trees. Full article

Groundwater plays a crucial role in sustaining agriculture and livelihoods in the arid Middle Draa Valley (MDV) of southeastern Morocco. However, increasing groundwater extraction, declining rainfall, and the absence of effective floodwater harvesting systems have led to severe aquifer depletion. This study applies and compares six machine learning (ML) algorithms—decision trees (CART), ensemble methods (random forest, LightGBM, XGBoost), distance-based learning (k-nearest neighbors), and support vector machines—integrating GIS, satellite data, and field observations to delineate zones suitable for groundwater recharge. The results indicate that ensemble tree-based methods yielded the highest predictive accuracy, with LightGBM outperforming the others by achieving an overall accuracy of 0.90. Random forest and XGBoost also demonstrated strong performance, effectively identifying priority areas for artificial recharge, particularly near ephemeral streams. A feature importance analysis revealed that soil permeability, elevation, and stream proximity were the most influential variables in recharge zone delineation. The generated maps provide valuable support for irrigation planning, aquifer conservation, and floodwater management. Overall, the proposed machine learning–geospatial framework offers a robust and transferable approach for mapping groundwater recharge zones (GWRZ) in arid and semi-arid regions, contributing to the achievement of Sustainable Development Goals (SDGs))—notably SDG 6 (Clean Water and Sanitation), by enhancing water-use efficiency and groundwater recharge (Target 6.4), and SDG 13 (Climate Action), by supporting climate-resilient aquifer management. Full article

The work presents a comprehensive analysis and costing of sugar beet cultivation in 2020–2022, for individual farms of the Lublin region. About 120 farms were analyzed. Based on this analysis, the criteria for a model farm were determined and adopted for the calculation of sugar beet production costs. ARIMA process modeling was performed, based on which forecasts were determined for several selected parameters. Customs tariffs introduced by the USA have a drastic impact on the economy. The effects of the COVID19 pandemic may also have a significant impact on the current market situation. Forecasting in the current geopolitical situation is very difficult because of the lack of stationarity of parameters. The financial result obtained by growers is mainly influenced by indirect costs absorbing 61.31% of total costs in 2020. In 2021 and 2022, indirect costs were 61.16% and 59.61% of production income, respectively. Among this group of costs, the largest share is accounted for by the costs of sowing services, sugar beet harvesting, and soil liming amounting from 14.27% to 15.92%. During the analyzed period, sugar beet cultivation remained profitable, with a production profitability index of 1.31 in 2020 and 2021, and 1.10 in 2022. The unit cost of production increased every year. In 2020, it was 14.27% and in 2021, it increased to 15.19%. The unit cost of production in 2022 was the highest, at 23.41%. Sugar beet cultivation is one of the profitable activities in agricultural production, but it is characterized by high production costs, which increased during the years analyzed (2020 to 2022), topping out at 90.87% of total revenue. The information and data presented in this study will be used in the development of a farmer-oriented application and will support the creation of an expert system for sugar beet growers. Cost forecasting will enable farmers to plan their production more effectively. Full article

Disease resistance is one of the most important target traits for sugarcane genetic improvement. Sugarcane brown stripe (SBS) caused by Helminthosporium stenospilum is one of the most destructive foliar diseases, which not only reduces harvest cane yield but also sugar content. This study aimed to identify quantitative trait loci (QTL) and candidate genes associated with SBS resistance. Here, the phenotypic investigation in six field habitats showed a continuous normal distribution, revealing that the SBS resistance trait is a quantitative trait. Two high-density linkage maps based on the single-dose markers calling from the Axiom Sugarcane100K SNP chip were constructed for the dominant sugarcane cultivars YT93-159 (SBS-resistant) and ROC22 (SBS-susceptible) with a density of 2.53 cM and 2.54 cM per SNP marker, and mapped on 87 linkage groups (LGs) and 80 LGs covering 3069.45 cM and 1490.34 cM of genetic distance, respectively. A total of 32 QTL associated with SBS resistance were detected by QTL mapping, which explained 3.73–11.64% of the phenotypic variation, and the total phenotypic variance explained (PVE) in YT93-159 and ROC22 was 107.44% and 79.09%, respectively. Among these QTL, four repeatedly detected QTL (qSBS-Y38-1, qSBS-Y38-2, qSBS-R8, and qSBS-R46) were considered stable QTL. Meanwhile, two major QTL, qSBS-Y38 and qSBS-R46, could account for 11.47% and 11.64% of the PVE, respectively. Twenty-five disease resistance candidate genes were screened by searching these four stable QTL regions in their corresponding intervals, of which Soffic.01G0010840-3C (PR3) and Soffic.09G0017520-1P (DND2) were significantly up-regulated in YT93-159 by qRT-PCR, while Soffic.01G0040620-1P (EDR2) was significantly up-regulated in ROC22. These results will provide valuable insights for future studies on sugarcane breeding in combating this disease. Full article

In China’s Loess Plateau, sustainable agricultural end products are affected by an insufficiency of water resources. Rising crop water use efficiency (WUE) through field management pattern improvement is a crucial plan of action to address this issue. However, there is no agreement among researchers on the most appropriate field management practices regarding WUE, which requires further integrated quantitative analysis. We conducted a meta-analysis by quantifying the effect of agricultural practices surrounding nitrogen (N) fertilizer management. The two experimental cultivars were Yunhan–20410 and Yunhan–618. The subplots included nitrogen 0 kg·ha⁻¹ (N0), 90 kg·ha⁻¹ (N90), 180 kg·ha⁻¹ (N180), 210 kg·ha⁻¹ (N210), and 240 kg·ha⁻¹ (N240). Our results show that higher N rates (up to N210) enhanced water consumption during the node-flowering and flowering-maturity time periods. YH–618 showed higher water use during the sowing–greening and node-flowering periods but decreased use during the greening-node and flowering-maturity periods compared to YH–20410. The N210 treatment under YH–618 maximized water use efficiency (WUE). Increased N rates (N180–N210) decreased covering temperatures (T_max, T_min, T_aver) during flowering, increasing the level of grain filling. Spike numbers rose with N application, with an off-peak at N210 for strong-gluten wheat. The 1000-grain weight was at first enhanced but decreased at the far end of N180–N210. YH–618 with N210 achieved a harvest index (HI) similar to that of YH–20410 with N180, while excessive N (N240) or water reduced the HI. Dry matter accumulation increased up to N210, resulting in earlier stabilization. Soil water consumption from wintering to jointing was strongly correlated with pre-flowering dry matter biological process and yield, while jointing–flowering water use was linked to post-flowering dry matter and spike numbers. Post-flowering dry matter accumulation was critical for yield, whereas spike numbers positively impacted yield but negatively affected 1000-grain weight. In conclusion, our results provide evidence for determining suitable integrated agricultural establishment strategies to ensure efficient water use and sustainable production in the Loess Plateau region. Full article

Although the strawberry tree (A. unedo L.) has been long considered a neglected species of the Mediterranean maquis, the valorization of its fruit production may enhance its socioeconomic value, especially in rural areas. In this study, strawberry trees from different Sicilian sites were investigated in terms of macronutrients, fatty acid (FA) composition, tocopherols, total phenols, carotenoids, and minerals. Sicilian berries were a good source of carbohydrates (mainly fructose, glucose and sucrose) and dietary fiber. They were low in fat; however, the FA composition revealed the abundance of unsaturated FAs over saturated FAs and an advantageous n-6/n-3 ratio. Additionally, Sicilian berries showed an inversed linoleic/α-linolenic acid ratio with respect to berries from other Mediterranean regions, that had previously investigated in literature. This evidence suggests that this ratio may have a chemotaxonomic relevance. Considering antioxidants, the fruits had levels of tocopherols, particularly α-tocopherol, total phenols and carotenoids similar to those of certain commercial fruits. Precious amounts of minerals, such as Ca, K, Zn and Fe were also determined. Interestingly, berries harvested near a Sicilian volcanic area had higher levels of minerals, as well as tocopherols, phenols and carotenoids, than fruits from other Sicilian sites, thereby advancing the hypothesis that fruits from volcanic areas may have a superior nutritional value. Overall, data from this study elaborated by a proper statistical analysis revealed that the geographical origin was a relevant variable to consider in the reliable study of this fruit species. Full article

The method of extracting energy from a fluid environment using flapping foils offers advantages such as structural simplicity and environmental friendliness. However, its low energy harvesting efficiency remains a significant factor limiting its development. This study employs suction and blower-based control (SBC) to enhance the energy harvesting efficiency of flapping foils. Using an orthogonal experimental design and numerical methods, 49 representative combinations of SBC geometries were selected for numerical simulation. The effects and priority rankings of geometric parameters on foil performance were statistically analyzed. It was found that under the optimal geometry (the suction slot position is 0.54c, the injection slot position is 0.79c, the width of the slot is 0.015c, the angle of the suction slot is −3°, and the angle of the injection slot is −9°), the energy harvesting efficiency can reach 40.7%. Furthermore, under laminar flow conditions, the benefit of SBC increases with higher Reynolds numbers (Re). At Re = 2200, SBC maximized the improvement in energy harvesting efficiency by 76%. No significant correlation was observed between the flapping amplitude and the SBC effect. However, the reduced frequency significantly influences the efficiency improvement generated by SBC. The SBC method shifts the foil’s optimal operating region towards lower reduced frequencies, which benefits energy harvesting efficiency. The research presented herein may have potential applications in the development of marine energy systems and bio-inspired propulsion. Full article

Rainwater harvesting for sustainable agriculture (RWHSA) offers a viable and eco-friendly strategy to alleviate water scarcity in semi-arid regions, particularly for agricultural use. This study aims to identify optimal sites for implementing RWH systems in northern Iraq to enhance water availability and promote sustainable farming practices. An integrated geospatial approach was adopted, combining Remote Sensing (RS), Geographic Information Systems (GIS), and Multi-Criteria Decision Analysis (MCDA). Key thematic layers, including soil type, land use/land cover, slope, and drainage density were processed in a GIS environment to model runoff potential. The Soil Conservation Service Curve Number (SCS-CN) method was used to estimate surface runoff. Criteria were weighted using the Analytical Hierarchy Process (AHP), enabling a structured and consistent evaluation of site suitability. The resulting suitability map classifies the region into four categories: very high suitability (10.2%), high (26.6%), moderate (40.4%), and low (22.8%). The integration of RS, GIS, AHP, and MCDA proved effective for strategic RWH site selection, supporting cost-efficient, sustainable, and data-driven agricultural planning in water-stressed environments. Full article

To investigate the effect of Botrytis cinerea infection severity on the flavor characteristics of Petit Manseng noble rot wine, this study analyzed wines produced from Petit Manseng grapes grown in the eastern foothills of Helan Mountain, Ningxia, China. The grapes were categorized into three groups based on infection status: uninfected, mildly infected, and severely infected with Botrytis cinerea. Headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME-GC-MS) and an electronic nose were employed to detect and analyze the aroma components of wines under the three infection conditions. Additionally, trained sensory panelists conducted sensory evaluations of the wine aromas. The results revealed that wines made from severely infected grapes exhibited the richest and most complex aroma profiles. A total of 70 volatile compounds were identified, comprising 32 esters, 17 alcohols, 5 acids, 8 aldehydes and ketones, 4 terpenes, and 4 other compounds. Among these, esters and alcohols accounted for the highest contents. Key aroma-active compounds included isoamyl acetate, ethyl decanoate, phenethyl acetate, ethyl laurate, hexanoic acid, linalool, decanoic acid, citronellol, ethyl hexanoate, and methyl octanoate. Sensory evaluation indicated that the “floral aroma”, “pineapple/banana aroma”, “honey aroma”, and “overall aroma intensity” were most pronounced in the severely infected group. These findings provide theoretical support for the harvesting of severely Botrytis cinerea-infected Petit Manseng grapes and the production of high-quality noble rot wine in this region. Full article

Redwood (Sequoia sempervirens (Lamb. ex D. Don) Endl.) is a fast-growing, long-lived conifer native to a narrow coastal zone along the western seaboard of the United States. Redwood can accumulate very high amounts of carbon in plantation settings and continuous cover forestry (CCF) represents a highly profitable option, particularly for small-scale forest growers in the North Island of New Zealand. We evaluated the profitability of conceptual CCF regimes using two case study forests: Blue Mountain (109 ha, Taranaki Region, New Zealand) and Spring Creek (467 ha, Manawatu-Whanganui Region, New Zealand). We ran a strategic harvest scheduling model for both properties and used its results to guide a tactical-spatially explicit model harvesting small 0.7 ha units over a period that spanned 35 to 95 years after planting. The internal rates of return (IRRs) were 9.16 and 10.40% for Blue Mountain and Spring Creek, respectively, exceeding those considered robust for other forest species in New Zealand. The study showed that small owners could benefit from carbon revenue during the first 35 years after planting and then switch to a steady annual income from timber, maintaining a relatively constant carbon stock under a continuous cover forestry regime. Implementing adjacency constraints with a minimum green-up period of five years proved feasible. Although small coupes posed operational problems, which were linked to roading and harvesting, these issues were not insurmountable and could be managed with appropriate operational planning. Full article

High-quality green gardens can markedly enhance the quality of life and mental well-being of their users. However, health and lifestyle constraints make it difficult for people to enjoy urban gardens, and traditional methods struggle to offer the high-fidelity experiences they need. This study introduces a 3D scene reconstruction and rendering strategy based on implicit neural representation through the efficient and removable neural radiation fields model (NeRF-RE). Leveraging neural radiance fields (NeRF), the model incorporates a multi-resolution hash grid and proposal network to improve training efficiency and modeling accuracy, while integrating a segment-anything model to safeguard public privacy. Take the crabapple tree, extensively utilized in urban garden design across temperate regions of the Northern Hemisphere. A dataset comprising 660 images of crabapple trees exhibiting three distinct geometric forms is collected to assess the NeRF-RE model’s performance. The results demonstrated that the ‘harvest gold’ crabapple scene had the highest reconstruction accuracy, with PSNR, LPIPS and SSIM of 24.80 dB, 0.34 and 0.74, respectively. Compared to the Mip-NeRF 360 model, the NeRF-RE model not only showed an up to 21-fold increase in training efficiency for three types of crabapple trees, but also exhibited a less pronounced impact of dataset size on reconstruction accuracy. This study reconstructs real scenes with high fidelity using virtual reality technology. It not only facilitates people’s personal enjoyment of the beauty of natural gardens at home, but also makes certain contributions to the publicity and promotion of urban landscapes. Full article

Bird-dropping fouling and hotspot anomalies remain the most prevalent and detrimental defects in utility-scale photovoltaic (PV) plants; their co-occurrence on a single module markedly curbs energy yield and accelerates irreversible cell degradation. However, markedly disparate visual–thermal signatures of the two phenomena impede high-fidelity concurrent detection in existing robotic inspection systems, while stringent onboard compute budgets also preclude the adoption of bulky detectors. To resolve this accuracy–efficiency trade-off for dual-defect detection, we present YOLOv8-SG, a lightweight yet powerful framework engineered for mobile PV inspectors. First, a rigorously curated multi-modal dataset—RGB for stains and long-wave infrared for hotspots—is assembled to enforce robust cross-domain representation learning. Second, the HSV color space is leveraged to disentangle chromatic and luminance cues, thereby stabilizing appearance variations across sensors. Third, a single-head self-attention (SHSA) block is embedded in the backbone to harvest long-range dependencies at negligible parameter cost, while a global context (GC) module is grafted onto the detection head to amplify fine-grained semantic cues. Finally, an auxiliary bounding box refinement term is appended to the loss to hasten convergence and tighten localization. Extensive field experiments demonstrate that YOLOv8-SG attains 86.8% mAP@0.5, surpassing the vanilla YOLOv8 by 2.7 pp while trimming 12.6% of parameters (18.8 MB). Grad-CAM saliency maps corroborate that the model’s attention consistently coincides with defect regions, underscoring its interpretability. The proposed method, therefore, furnishes PV operators with a practical low-latency solution for concurrent bird-dropping and hotspot surveillance. Full article

The Korla fragrant pear is a highly valued economic fruit in China’s Xinjiang region. However, biomechanical data on the fruit-bearing branches and pedicels of this species remain incomplete, which to some extent hinders the advancement of harvesting equipment and techniques. Therefore, refining these data is of great significance for the development of efficient and non-destructive harvesting strategies. This study aims to elucidate the mechanical properties of the fruiting branches and peduncles of Korla fragrant pears, thereby establishing a theoretical foundation for the future development of intelligent harvesting technology for this variety. The research utilized axial and radial compression tests, along with three-point bending test methods, to quantitatively analyze the elastic modulus and shear modulus of the branches and peduncles. The test results reveal that the elastic modulus of the fruiting branches under axial compression is 263.51 ± 76.51 MPa, while under radial compression, it measures 135.53 ± 73.73 MPa (where ± represents the standard deviation). In comparison, the elastic modulus of the peduncles is recorded at 152.96 ± 119.95 MPa. Additionally, the three-point bending test yielded a shear modulus of 75.48 ± 32.84 MPa for the branches and 30.23 ± 8.50 MPa for the peduncles. Using finite element static structural analysis, the simulation results aligned closely with the experimental data, falling within an acceptable error range, thus validating the reliability of the testing methods and outcomes. The mechanical parameters obtained in this study are critical for modeling the stress and deformation behaviors of pear-bearing structures during mechanical harvesting. These findings provide valuable theoretical support for the optimization of harvesting device design and operational strategies, with the aim of reducing fruit damage and improving harvesting efficiency in pear orchards. Full article

This paper discusses the possibilities of using stump wood as a raw material for energy generation. The research was based on an analysis of the state of knowledge, forest field studies, and participatory observations. A formula was sought to optimise the procurement cost of stump wood appropriate to Polish conditions. Conceptualisation was carried out in a selected area of the Notecka Forest in the Wielkopolska region, located in western Poland. A pilot study was designed to test a computational formula to assess the profitability of harvesting wood from stump wood resources for energy generation. The potential of stump wood is estimated to be around half a million cubic metres per year from the Notecka Forest area alone. This resource provides an opportunity for business development in both forestry and the renewable energy sources (RESs) sector, despite the barriers and risks shown in this study. Full article