Search Results (2,623)

Agricultural production in southern Angola faces challenges due to unsustainable practices, including inefficient use of water, fertilizers, and machinery, resulting in low yields and environmental degradation. Therefore, clear and measurable indicators are needed to guide farmers toward more sustainable practices. The scientific literature insufficiently addresses this issue, leaving a significant gap in the evaluation of key performance indicators (KPIs) that can guide good agricultural practices (GAPs) adapted to the context of southern Angola, with the goal of promoting a more resilient and sustainable agricultural sector. So, the objective of this study is to identify and assess KPIs capable of supporting the selection of GAPs suitable for maize, potato, and tomato cultivation in the context of southern Angolan agriculture. A systematic literature review (SLR) was conducted, screening 2720 articles and selecting 14 studies that met defined inclusion criteria. Five KPIs were identified as the most relevant: gross margin, net profit, water use efficiency, nitrogen use efficiency, and machine energy. These indicators were analyzed and standardized to evaluate their contribution to sustainability across different GAPs. Results show that organic fertilizers are the most sustainable option for maize, drip irrigation for potatoes, and crop rotation for tomatoes in southern Angola because of their efficiency in low-resource environments. A clear, simple, and effective representation of the KPIs was developed to be useful in communicating to farmers and policy makers on the selection of the best GAPs in the cultivation of different crops. The study proposes a validated KPI-based methodology for assessing sustainable agricultural practices in developing regions such as southern Angola, aiming to lead to greater self-sufficiency and economic stability in this sector. Full article

Monitoring crop damage caused by wildlife remains a significant challenge in agricultural management, particularly in the case of large-scale monocultures such as maize. The given study presents a semi-automated process for detecting wildlife-induced damage using RGB imagery acquired from unmanned aerial vehicles (UAVs). The method is designed for non-specialist users and is fully integrated within the QGIS platform. The proposed approach involves calculating three vegetation indices—Excess Green (ExG), Green Leaf Index (GLI), and Modified Green-Red Vegetation Index (MGRVI)—based on a standardized orthomosaic generated from RGB images collected via UAV. Subsequently, an unsupervised k-means clustering algorithm was applied to divide the field into five vegetation vigor classes. Within each class, 25% of the pixels with the lowest average index values were preliminarily classified as damaged. A dedicated QGIS plugin enables drone data analysts (Drone Data Analysts—DDAs) to adjust index thresholds, based on visual interpretation, interactively. The method was validated on a 50-hectare maize field, where 7 hectares of damage (15% of the area) were identified. The results indicate a high level of agreement between the automated and manual classifications, with an overall accuracy of 81%. The highest concentration of damage occurred in the “moderate” and “low” vigor zones. Final products included vigor classification maps, binary damage masks, and summary reports in HTML and DOCX formats with visualizations and statistical data. The results confirm the effectiveness and scalability of the proposed RGB-based procedure for crop damage assessment. The method offers a repeatable, cost-effective, and field-operable alternative to multispectral or AI-based approaches, making it suitable for integration with precision agriculture practices and wildlife population management. Full article

Legume crops are sensitive to shifting environmental conditions, as they depend on a narrow range of climatic stability for growth and nitrogen fixation. This research sought to assess the sustainability of Faba Asturiana (FA) cultivation under current and future climatic scenarios by establishing generalized linear mixed models (GLMMs). Specifically, it aimed to (1) investigate the effects of significant climatic stressors, including higher nighttime temperatures and extended drought periods, on crop viability, (2) analyze future scenarios based on Representative Concentration Pathways (RCP 4.5 and RCP 8.5), and (3) recommend adaptive measures to mitigate threats. Six spatial GLMMs were developed, incorporating variables such as extreme temperatures, precipitation, and the drought duration. Under present-day conditions (1971–2000), all the models exhibited strong predictive performances (AUC: 0.840–0.887), with warm nights (tasminNa20) consistently showing a negative effect on suitability (coefficients: −0.58 to −1.16). Suitability projections under future climate scenarios revealed considerable variation among the developed models. Under RCP 4.5, Far Future, Model 1 projected a 7.9% increase in the mean suitability, while under RCP 8.5, Far Future, the same model showed a 78% decline. Models using extreme cold, drought, or precipitation as climatic stressors (e.g., Models 2–4) revealed the most significant suitability losses under RCP 8.5, with the reductions exceeding 90%. In contrast, comprising variables less affected by severe fluctuations, Model 6 showed relative stability in most of the developed scenarios. The model also produced the highest mean suitability (0.130 ± 0.207) in an extreme projective scenario. The results highlight that high night temperatures and prolonged drought periods are the most limiting factors for FA cultivation. ecological niche models (ENMs) performed well, with a mean AUC value of 0.991 (SD = 0.006) and a mean TSS of 0.963 (SD = 0.024). According to the modeling results, among the variables affecting the current distribution of Protected Geographical Indication-registered AF, prspellb1 (max consecutive dry days) had the highest effect of 28.3%. Applying advanced statistical analyses, this study provides important insights for policymakers and farmers, contributing to the long-term sustainability of PGI agroecosystems in a warming world. Full article

Breeding programs often overlook the use of root traits. Therefore, we investigated the relevance of sorghum root traits in explaining its adaptation to combined drought and heat stress (CDHS). Six (i.e., three pre-release lines + three checks) sorghum genotypes were established at two low-altitude (i.e., <600 masl) locations with a long-term history of averagely very high temperatures in the beginning of the summer season, under two management (i.e., CDHS and well-watered (WW)) regimes. At each location, the genotypes were laid out in the field using a randomized complete block design (RCBD) replicated two times. Root trait data, namely root diameter (RD), number of roots (NR), number of root tips (NRT), total root length (TRL), root depth (RDP), root width (RW), width–depth ratio (WDR), root network area (RNA), root solidity (RS), lower root area (LRA), root perimeter (RP), root volume (RV), surface area (SA), root holes (RH) and root angle (RA) were gathered using the RhizoVision Explorer software during the pre- and post-flowering stage of growth. RSA traits differentially showed significant (p < 0.05) correlations with grain yield (GY) at pre- and post-flowering growth stages and under CDHS and WW conditions also revealing genotypic variation estimates exceeding 50% for all the traits. Regression models varied between pre-flowering (p = 0.013, R² = 47.15%, R² Predicted = 29.32%) and post-flowering (p = 0.000, R² = 85.64%, R² Predicted = 73.30%) growth stages, indicating post-flowering as the optimal stage to relate root traits to yield performance. RD contributed most to the regression model at post-flowering, explaining 51.79% of the 85.64% total variation. The Smith–Hazel index identified ICSV111IN and ASAREACA12-3-1 as superior pre-release lines, suitable for commercialization as new varieties. The study demonstrated that root traits (in particular, RD, RW, and RP) are linked to crop performance under CDHS conditions and should be incorporated in breeding programs. This approach may accelerate genetic gains not only in sorghum breeding programs, but for other crops, while offering a nature-based breeding strategy for stress adaptation in crops. Full article

This study proposes an integrated framework for sustainable tropical agriculture by combining biochemical waste valorization with spatial carbon footprint estimation in ‘Phulae’ pineapple production. Peel and eye residues from fresh-cut processing were enzymatically converted into rare sugar, achieving average conversion efficiencies of 35.28% for peel and 37.51% for eyes, with a benefit–cost ratio of 1.56 and an estimated unit cost of USD 0.17 per gram. A complementary zero-waste pathway produced functional gummy products using vinegar fermented from pineapple eye waste, with the preferred formulation scoring a mean of 4.32 out of 5 on a sensory scale with 158 untrained panelists. For spatial carbon modeling, the Bare Land Referenced Algorithm (BRAH) and Otsu thresholding were applied to multi-temporal Sentinel-2 and THEOS imagery to estimate plantation age, which strongly correlated with field-measured emissions (r = 0.996). This enabled scalable mapping of plot-level greenhouse gas emissions, yielding an average footprint of 0.2304 kg CO₂ eq. per kilogram of fresh pineapple at the plantation gate. Together, these innovations form a replicable model that aligns tropical fruit supply chains with circular economy goals and carbon-related trade standards. The framework supports waste traceability, resource efficiency, and climate accountability using accessible, data-driven tools suitable for smallholder contexts. By demonstrating practical value addition and spatially explicit carbon monitoring, this study shows how integrated circular and geospatial strategies can advance sustainability and market competitiveness for the ‘Phulae’ pineapple industry and similar perennial crop systems. Full article

Fall detection is a critical task in healthcare monitoring systems, especially for elderly populations, for whom timely intervention can significantly reduce morbidity and mortality. This study proposes a privacy-preserving and scalable fall-detection framework that integrates federated learning (FL) with transfer learning (TL) to train deep learning models across decentralized data sources without compromising user privacy. The pipeline begins with data acquisition, in which annotated video-based fall-detection datasets formatted in YOLO are used to extract image crops of human subjects. These images are then preprocessed, resized, normalized, and relabeled into binary classes (fall vs. non-fall). A stratified 80/10/10 split ensures balanced training, validation, and testing. To simulate real-world federated environments, the training data is partitioned across multiple clients, each performing local training using pretrained CNN models including MobileNetV2, VGG16, EfficientNetB0, and ResNet50. Two FL topologies are implemented: a centralized server-coordinated scheme and a ring-based decentralized topology. During each round, only model weights are shared, and federated averaging (FedAvg) is applied for global aggregation. The models were trained using three random seeds to ensure result robustness and stability across varying data partitions. Among all configurations, decentralized MobileNetV2 achieved the best results, with a mean test accuracy of 0.9927, F1-score of 0.9917, and average training time of 111.17 s per round. These findings highlight the model’s strong generalization, low computational burden, and suitability for edge deployment. Future work will extend evaluation to external datasets and address issues such as client drift and adversarial robustness in federated environments. Full article

Understanding future changes in crop phenology and climate suitability is essential for sustaining winter wheat production in the Huang-Huai-Hai (3H) Plain under climate change. This study integrates bias-corrected CMIP6 climate projections, the DSSAT CERES-Wheat crop model, and Random Forest analysis to assess spatiotemporal shifts in winter wheat phenology and climate suitability. The assessment focuses on the mid- (2041–2060) and late 21st century (2081–2100) under the SSP2-4.5 and SSP5-8.5 scenarios. The results indicate that the vegetative and whole growing periods (VGP and WGP) will be extended in the mid-century but shorten by the late century. In contrast, the reproductive growing period (RGP) will be slightly reduced in the mid-century and extended under high emissions in the late century. Temperature suitability is projected to increase during the VGP and WGP but decline during the RGP. Precipitation suitability generally improves, except for a decrease during the reproductive period south of 32° N. Solar radiation suitability is expected to decline across all stages. Temperature is identified as the primary driver of phenological changes, with solar radiation and precipitation playing increasingly important roles in the mid- and late 21st century, respectively. Adaptive strategies, including the adoption of heat-tolerant varieties, longer reproductive periods, and earlier sowing, are recommended to enhance yield stability under future climate conditions. Full article

Sustainable Development Reserves are organized units in the Amazon that are essential for the proper use and sustainable management of the region’s natural resources and for the livelihoods and economy of the local communities. This study aims to provide a climatic characterization of the Madeira River Sustainable Development Reserve (MSDR), offering scientific support to efforts to assess the feasibility of implementing adaptation measures to increase the resilience of isolated Amazon communities in the face of extreme climate events. Significant statistical analyses based on time series of observational and reanalysis climate data were employed to obtain a detailed diagnosis of local climate variability. The results show that monthly mean two-meter temperatures vary from 26.5 °C in February, the coolest month, to 28 °C in August, the warmest month. Monthly precipitation averages approximately 250 mm during the rainy season, from December until May. July and August are the driest months, August and September are the warmest months, and September and October are the months with the lowest river level. Cold spells were identified in July, and warm spells were identified between July and September, making this period critical for public health. Heavy precipitation events detected by the R80, Rx1day, and Rx5days indices show an increasing trend in frequency and intensity in recent years. The analyses indicated that the MSDR has no potential for wind-energy generation; however, photovoltaic energy production is viable throughout the year. Regarding the two major commercial crops and their resilience to thermal stress, the region presents suitable conditions for açaí palm cultivation, but Brazil nut production may be adversely affected by extreme drought and heat events. The results of this study may support research on adaptation strategies that includethe preservation of local traditions and natural resources to ensure sustainable development. Full article

Moringa (Moringa oleifera Lam.) is widely recognised as a multipurpose crop suitable for human and animal consumption, medicinal, and industrial purposes, making it attractive for introduction into new ranges. Its extracts have been found to have beneficial impacts on various crop species and biological activity against multiple weeds, making their use in agriculture promising. However, concerns have also been raised about moringa’s potential to negatively impact the growth and development of other cultivated and non-cultivated plant species, especially in areas where it has been introduced outside its native range. To understand the positive and negative interactions between moringa and other plants, it is essential to investigate its allelopathic potential. Allelopathy is a biological activity by which one plant species produces and releases chemical compounds that influence the reproduction, growth, survival, or behaviour of other plants with either beneficial or detrimental effects on the receiver. Plants produce and release allelochemicals by leaching, volatilisation, or through root exudation. These biochemical compounds can affect critical biological processes such as seed germination, root and shoot elongation, photosynthesis, enzymatic activities, and hormonal balance in neighboring plants. Therefore, allelopathy is an important driver of plant composition and ecological interactions in an ecosystem. This review explores the positive and negative allelopathic effects of moringa extracts on other plant species, which may help to inform decisions regarding its introduction into new biogeographical regions and incorporation into existing farming systems, as well as the use of moringa plant extracts in agriculture. Full article

Several strains of the genus Serratia isolated from the rhizosphere of crops are plant growth-promoting bacteria (PGPB) that may possess various traits associated with nitrogen metabolism, auxin production, and other characteristics. The objective of the present study was to investigate the in vitro and in vivo characteristics of the growth-promoting activity of S. liquefaciens UNJFSC 002 in potato plants. This strain was inoculated into potato varieties (Solanum tuberosum) under laboratory and greenhouse conditions to determine the bacterial strain’s ability to promote growth under controlled conditions. It was found that the S. liquefaciens strain UNJFSC 002 had a significantly greater effect on the fresh and dry weight of the foliage and induced a higher tuber weight per plant and larger tuber diameter compared to the uninoculated potato plants (p < 0.05). Additionally, in vitro, the strain demonstrated the ability to fix atmospheric nitrogen and produce indole-3-acetic acid (IAA), as well as the capacity to solubilise tricalcium phosphate in the laboratory. This research reveals the potential of S. liquefaciens UNJFSC 002 as an inoculant to improve potato production, demonstrating its ability to promote the growth and productivity of potato varieties suitable for direct consumption and processing under controlled conditions. Full article

Minor cereals are an important part of the Chinese grain industry, accounting for about 8 percent of the country’s total grain-growing area. Minor cereals include millet, buckwheat, Panicum miliaceum, and other similar grains. Influenced by topographical and climatic factors, the distribution of minor cereals in China is mainly concentrated in the plateau and hilly areas north of the Yangtze River. In addition, there are large concentrations of minor cereals in Inner Mongolia, Heilongjiang, and other areas with flatter terrain. However, the level of mechanized harvesting in these areas is still low, and there is little research on the whole process of mechanized harvesting of minor cereals. This paper aims to discuss the current status of the minor cereal industry and its mechanization level, with particular attention to the challenges encountered in research related to the mechanized harvesting of minor cereals, including limited availability of suitable machinery, high losses, and low efficiency. The article provides a comprehensive overview of the key technologies that must be advanced to achieve mechanized harvesting throughout the process, such as header design, threshing, cleaning, and intelligent modular systems. It also summarizes current research progress on advanced equipment for mechanized harvesting of minor cereals. In addition, the article puts forward suggestions to promote the development of mechanized harvesting of minor cereals, focusing on aspects such as crop variety optimization, equipment modularization, and intelligentization technology, aiming to provide a reference for the further development and research of mechanized harvesting technology for minor cereals in China. Full article

The objective of this study was to evaluate the physiological, biochemical, and productive effects of the foliar application of bioregulators, based on auxin, cytokinin, and gibberellic acid, on yellow melon, cultivar DALI^®, plants subjected to different salinity levels in a protected environment to simulate Brazil’s semi-arid conditions. The experiment was conducted using a completely randomized block design, in a 4 × 3 factorial scheme, with four salinity levels (0, 2, 4, and 6 dS m⁻¹) and three doses of the bioregulator, Stimulate^® (0%, 100%, and 150% of the recommended dose), with six weekly applications. The physiological variables (chlorophyll a fluorescence and gas exchange) and biochemical parameters (antioxidant enzyme activity and lipid peroxidation) were evaluated at 28 and 42 days after transplanting, and the agronomic traits (fresh fruit mass, physical attributes, and post-harvest quality) were evaluated at the end of the experiment. The results indicated that salinity impaired the physiological and productive performance of the plants, especially at higher levels (4 and 6 dS m⁻¹), causing oxidative stress, reduced photosynthesis, and decreased yield. However, the application of the bioregulator at the 100% dose mitigated the effects of salt stress under moderate salinity (2 dS m⁻¹), promoting higher CO₂ assimilation rates of up to 31.5%, better water-use efficiency, and reduced lipid peroxidation. In addition, the fruits showed a greater mass of up to 66%, thicker pulp, and higher soluble solids (> 10 °Brix) content, making them suitable for sale in the market. The 150% dose did not provide additional benefits and, in some cases, resulted in inhibitory effects. It is concluded that the application of Stimulate^® at the recommended dose is effective in mitigating the effects of moderate salinity, up to ~3 dS m⁻¹, in yellow melon crops; however, its effectiveness is limited under high salinity conditions, requiring the use of complementary strategies. Full article

Curcuma spp. is a popular ornamental crop valued for its vibrant appearance and suitability for both regular and off-season production. As global emphasis on freshwater conservation increases and with a demand for compact potted plants, reducing water use while maintaining high aesthetic quality presents a key challenge for horticulturists. Potassium silicate (PS) has been proposed as a foliar spray to alleviate plant water stress. This study aimed to evaluate the effects of PS on growth, ornamental traits, and photosynthetic parameters of off-season potted Curcuma cv. ‘Jasmine Pink’ under deficit irrigation (DI). Plants were subjected to three treatments in a completely randomized design: 100% crop evapotranspiration (ETc), 50% ETc, and 50% ETc with 1000 ppm PS (weekly sprayed on leaves for 11 weeks). Both DI treatments (50% ETc and 50% ETc + PS) reduced plant height by 7.39% and 9.17%, leaf number by 16.99% and 7.03%, and total biomass by 21.13% and 20.58%, respectively, compared to 100% ETc. Notably, under DI, PS-treated plants maintained several parameters equivalent to the 100% ETc treatment, including flower bud emergence, blooming period, green bract number, effective quantum yield of PSII (ΔF/Fm′), and electron transport rate (ETR). In addition, PS application increased leaf area by 8.11% and compactness index by 9.80% relative to untreated plants. Photosynthetic rate, ΔF/Fm′, and ETR increased by 31.52%, 13.63%, and 9.93%, while non-photochemical quenching decreased by 16.51% under water-limited conditions. These findings demonstrate that integrating deficit irrigation with PS foliar application can enhance water use efficiency and maintain ornamental quality in off-season potted Curcuma, promoting sustainable water management in horticulture. Full article

This study aims to improve the understanding of, and provide insights into, the environmental fate of herbicides currently used in agriculture, which is addressed through the analysis of the quality of canal water used for irrigation and the agricultural soil in the immediate vicinity. The research was conducted in the main agricultural region of Serbia, characterized by intensive crop production in conventional agriculture. Monitoring was focused on the Danube–Tisza–Danube canal system, specifically the Bogojevo–Bečej section. The presence of 41 currently used herbicides was analyzed in 520 soil samples collected from two depths (0–30 cm and 30–60 cm), as well as in 100 canal water samples. Results showed a high frequency of clopyralid, 2,4-D-methyl ester, terbuthylazine, fenoxaprop-ethyl, and aclonifen, with the highest amountsbeingterbuthylazine and quizalofop-ethyl, which was possibly a consequence of their recent application shortly before sampling. Concentrations of herbicide residues at different depths were closely similar, without the impact of soil mechanical and chemical characteristics on herbicide levels. In canal water characterized as moderately salty and slightly alkaline, herbicide residues were far below the maximum allowable concentrations, suggesting that the canal water is suitable for aquatic life, irrigation, and other uses. The findings suggest that the appropriate use of herbicides in regions under intensive agriculture is important for reducing environmental contamination. Full article

Mungbean is grown as a summer crop in subtropical climates globally. The global demand for mungbean is increasing, and opportunities exist to expand production regions to more marginal environments, such as southern Australia, as an opportunistic summer crop to help meet the growing global demand. Mungbean has the potential to be an opportunistic summer crop when an appropriate sowing window coincides with sufficient soil water. This expansion from subtropical to temperate climates will pose challenges, including low temperatures, a longer day length and a low and variable water supply. To assess mungbean suitability to temperate, southern Australian summer rainfall patterns and soil water availability, we conducted field experiments applying a range of water treatments across four locations with contrasting rainfall patterns within the state of Victoria (in southern Australia) in 2020–2021 and 2021–2022. The water treatments were applied prior to sowing (60 mm), the vegetative stage (40 mm) and the reproductive stage (40 mm) in a factorial combination at each location. Two commercial cultivars, Celera II-AU and Jade-AU, were used. Water scarcity during flowering and the pod-filling stages were important factors constraining yield. Analysis of yield components showed that increasing water availability at critical growth stages, viz. the vegetative and reproductive stages, of mungbean was associated with increases in total biomass, HI and grain number in addition to increased water use and water use efficiency (WUE). Average WUEs ranged from 1.3 to 7.6 kg·ha⁻¹·mm⁻¹. The maximum potential WUE values were 6.4 and 5.1 kg·ha⁻¹·mm⁻¹ for Celera II-AU and Jade-AU across the sites, with the estimated soil evaporation values (x-intercept) of 83 and 74 mm, respectively. Nitrogen fixation was variable, with %Ndfa values ranging from 9.6 to 76.8%, and was significantly affected by soil water availability. This study emphasises the importance of water availability during the reproductive phase for mungbean yield. The high rainfall zones within Victoria have the potential to grow mungbean as an opportunistic summer crop. Full article