Search Results (2,744)

Genome editing-mediated haploid inducer systems (HISs) present a promising strategy for enhancing breeding efficiency in legume crops, which are vital for sustainable agriculture due to their nutritional benefits and ability to fix nitrogen. Traditional legume breeding is often slow and complicated by the complexity of legumes’ genomes and the challenges associated with tissue culture. Recent advancements have broadened the applicability of HISs in legume crops, facilitating a reduction in the duration of the breeding cycle. By integrating genome editing technology with haploid breeding systems, researchers can achieve precise genetic modifications and rapidly produce homozygous lines, thereby significantly accelerating the development of desired traits. This review explores the current status and future prospects of genome editing-mediated HISs in legumes, emphasizing the mechanisms of haploid induction; recent breakthroughs; and existing technical challenges. Furthermore, we highlight the necessity for additional research to optimize these systems across various legume species, which has the potential to greatly enhance breeding efficiency and contribute to the sustainability of legume production. Full article

Low vegetable consumption in sub-Saharan Africa partly arises from limited availability across cereal-based zones. A field experiment in southern Benin (April to September 2023) evaluated four maize–chili and five maize–mungbean relay intercropping. Growth and yield data and farmers’ perceptions were analyzed using analysis of variance with the least significant difference test, land equivalent ratio (LER) and monetary indexes. Maize grain yield was statistically similar across patterns, whereas chili and mungbean yields differed significantly. All sowing patterns achieved LER > 1. Pattern (1:1) maize–chili had a modest LER (1.15), while treatment (1:3) had a high LER (1.60) for mungbean–maize. Both patterns showed high actual yield gain and intercropping advantage. Pattern (2:2) for maize–chili and pattern (1:3) for maize–mungbean yielded the greatest gross return (7796.6 USD/ha and 1301.2 USD/ha, respectively). Sole mungbean and all intercropping sowing patterns significantly increased mineralizable carbon. Pattern (1:3) maize-mungbean slightly increased total nitrogen and potassium. Farmers ranked the highest pattern (2:2) for maize–chili and (1:3) for maize–mungbean due to sup erior weed, water, and soil management and increased yields. These findings suggest that diversified maize systems incorporating chili pepper and mungbean offer economic benefits and better soil health in southern Benin. Full article

Mangrove swamp rice (MSR) production is critical for the diet of small farmers of coastal Guinea-Bissau. In mangrove swamp agroecosystems, rice is grown during the rainy season when freshwater and nutrients are abundant. However, small-scale farmers face challenges like unpredictable rainfall and rising sea levels, which increase soil salinity and acidity. This study aims to assess soil physical–chemical properties, paired with farmers’ local practices, to evaluate fertility constraints, and to support sustainable soil–plant management practices. This co-designed research contributes to filling a gap concerning the adoption of sustainable agricultural practices adapted to specific contexts in West Africa. In two regions, Oio (center) and Tombali (south), rice yields were measured in semi-controlled trials both in two agroecological settings: Tidal Mangrove (TM) and Associated Mangrove (AM) fields. 380 soil samples were collected, and rice growing parameters were assessed during the 2021 and 2022 rice sowing, transplanting, and flowering periods. Principal Component Analyses (PCA) and Multivariate Regression Analysis (MRA) were applied to understand trends and build fertility proxies in predicting yields. Significant spatial and temporal variability in the soil properties between agroecologies was found. Salinity constraints in Oio TMs limit production to an average of 110 g/m², compared to 250 g/m² in Tombali. Yield predictions account for 81% and 56.9% of the variance in TMs and AMs, respectively. Variables such as organic matter (OM), nitrogen (N), potassium (K), and precipitation positively influence yields, whereas sand content, pH, and iron oxides show a negative effect. This study advances the understanding of MSR production in Guinea-Bissau and underscores the importance of incorporating farmers’ knowledge of their diverse and complex production systems to effectively address these challenges. Full article

Salinity stress poses a major obstacle to agricultural productivity. Employing plant growth-promoting rhizobacteria (PGPR) has attracted significant attention due to its potential to improve plant development in challenging conditions. Yet, additional investigation is essential to fully understand the potential of PGPR in mitigating salinity stress, especially in field applications. Hence, this study investigated the resistance mechanisms of soybean (Glycine max (L.) Merr.) under salt stress with PGPR application through a field experiment with four treatments: normal soybean planting (NN), normal planting + PGPR (NP), salt stress planting (SN), and salt stress planting + PGPR (SP). This research investigated how applying PGPR under salt stress influences soybean photosynthetic traits, osmotic regulation, rhizosphere microbial communities, and yield quality. The results demonstrated that salt stress enhanced leaf temperature and significantly reduced the leaf area index, SPAD value, stomatal conductance, photosynthetic rate, and transpiration rate of soybeans. Compared to SN treatment, SP treatment significantly improved the stomatal conductance, photosynthetic rate, and transpiration rate by 10.98%, 16.28%, and 35.59%, respectively. Salt stress substantially increased sodium (Na⁺) concentration and Na⁺/K⁺ ratio in leaves, roots, and grains while reducing potassium (K⁺) concentration in roots and leaves. Under salinity stress, PGPR application significantly minimized Na⁺ concentration in leaves and enhanced K⁺ concentration in leaves, roots, and grains by 47.05%, 25.72%, and 14.48%, respectively. PGPR application boosted carbon assimilation (starch synthesis) by enhancing the activities of sucrose synthase, fructokinase, and ADP-glucose pyrophosphorylase. It improved physiological parameters and increased soybean yield by 32.57% compared to SN treatment. Additionally, PGPR enhanced antioxidant enzyme activities, including glutathione reductase, peroxidase, ascorbate peroxidase, and monodehydroascorbate reductase, reducing oxidative damage from salt stress. Analysis of rhizosphere microbial communities revealed that PGPR application enriched beneficial bacterial phyla such as Bacteroidetes, Firmicutes, Nitrospirae, and Patescibacteria and fungal genera like Metarhizium. These microbial shifts likely contributed to improved nutrient cycling and plant–microbe interactions, further enhancing soybean resilience to salinity. This study demonstrates that PGPR enhances soybean growth, microbial diversity, and salt tolerance under salinity stress, while future efforts should optimize formulations, explore synergies, and scale up for sustainable productivity. Full article

Currently, large-scale burning is an important straw disposal method in most developing countries. To execute prescribed burning while mitigating air pollution, it is crucial to explore the maximum possible range of meteorological changes. This study conducted a three-year monitoring program in Changchun, a core agricultural area in Northeast China severely affected by straw burning. The data included ground-level pollutant monitoring, ground-based polarized LiDAR observations, and ground meteorological factors such as planetary boundary layer height (PBLH), relative humidity (RH), and wind speed (WS). Using response surface methodology (RSM), this study analyzed key weather parameters to predict the optimal range for emission reduction effects. The results revealed that PM_2.5 was the primary pollutant during the study period, particularly in the lower atmosphere from March to April, with PM_2.5 rising sharply in April due to the exponential increase in fire points. Furthermore, during this phase, the average WS and PBLH increased, whereas the RH decreased. Univariate analysis confirmed that these three factors significantly impacted the PM_2.5 concentration. The RSM relevance prediction model (MET-PM_2.5) established a correlation equation between meteorological factors and PM_2.5 levels and identified the optimal combination of meteorological indices: WS (3.00–5.03 m/s), RH (30.00–38.30%), and PBLH (0.90–1.45 km). Notably, RH (33.1%) emerged as the most significant influencing factor, while the PM_2.5 value remained below 75 μg/m³ when all weather indicators varied by less than 20%. In conclusion, these findings could provide valuable meteorological screening schemes to improve planned agricultural residue burning policies, with the aim of minimizing pollution from such activities. Full article

Carbon neutrality is an important goal for addressing global warming. It can be achieved by increasing carbon storage and reducing carbon emissions. Vegetation plays a key role in storing carbon, but it is often lost or damaged, especially in areas affected by desertification. Therefore, restoring vegetation in these areas is crucial. Using advanced techniques to improve ecosystem structure can support ecological processes, and enhance soil and environmental conditions, encourage vegetation growth, and boost carbon storage effectively. This study focuses on optimizing Ecological Spatial Networks (ESNs) for revitalization and regional development, employing advanced techniques such as the MCR model for corridor construction, spatial analysis, and Gephi for mapping topological attributes. Various ecological and topological metrics were used to evaluate network performance, while the EFCT model was applied to optimize the ESN and maximize carbon sinks. In the Thal Desert, ecological source patches (ESPs) were divided into four modularity levels (15.6% to 49.54%) and five communities. The northeastern and southwestern regions showed higher ecological functionality but lower connectivity, while the central region exhibited the reverse. To enhance the ESN structure, 27 patches and 51 corridors were added to 76 existing patches, including 56 forest and 20 water/wetland patches, using the EFCT model. The optimized ESN resulted in a 14.97% improvement in carbon sink capacity compared to the unoptimized structure, primarily due to better functioning of forest and wetland areas. Enhanced connectivity between components contributed to a more resilient and stable ESN, supporting both ecological sustainability and carbon sequestration. Full article

During the last six decades, Lebanon’s landscapes have undergone significant regime shifts whose causes are under-investigated. Using land cover maps from 1962 and satellite imagery from 2014 and 2023 in five randomly selected villages across Lebanon’s major agroecological zones (AEZs), we identified salient trends in the urbanization-driven transformation of land use and land cover (LULC). Household socio-economic characteristics and environmental pressures were analyzed as independent variables influencing land use decisions. Logistic regression (LR) was employed to assess the significance of these variables in shaping farmers’ choices to transition toward “perennialization”—namely fruit tree monocropping or protected agriculture. The LR results indicate that education reduced the likelihood of “perennialization” by 45% (p < 0.001). Farm size positively influenced “perennialization” (p < 0.01), suggesting that land availability encourages this agricultural practice. In contrast, water availability negatively affects “perennialization” (p < 0.01), though farmers may still opt to irrigate by purchasing water during shortages. Our findings underline the complex interplay of socio-economic and environmental dynamics and historical events in shaping Lebanon’s rural landscapes and they offer insights into similar transformations across the Middle East and North Africa (MENA) region. Full article

Developing vegetable agriculture is crucial for ensuring a balanced dietary structure and promoting nutritional health. However, remote sensing extraction in open-field vegetable planting areas faces several challenges, such as the mixing of target crops with natural vegetation caused by differences in climate conditions and planting practices, which hinders the development of large-scale vegetable field mapping. This paper proposes a classification method based on vegetable phenological characteristics (VPC), which takes into account the spatiotemporal heterogeneity of vegetable cultivation in Northeast China. We used a two-step strategy. First, Sentinel-2 satellite images and land use data were utilized to identify the optimal time and key indicators for vegetable detection based on the phenological differences in crop growth. Second, spectral analysis was integrated with three machine learning classifiers, which leveraged phenological and spectral features extracted from satellite images to accurately identify vegetable-growing areas. This combined approach enabled the generation of a high-precision vegetable planting map. The research findings reveal a consistent year-by-year increase in the planting area of vegetables from 2019 to 2023. The overall accuracy (OA) of the results ranges from 0.81 to 0.93, with a Kappa coefficient of 0.83. Notably, this is the first 10 m resolution regional vegetable map in China, marking a significant advancement in economic vegetable crop mapping. Full article

The olive fly (Bactrocera oleae, OLF) is a major pest of global significance that occurs in places where olive cultivation thrives. This paper highlights the economic and environmental damage caused by OLF infestations, including reduced olive oil yield and quality, disrupted supply chains, and ecosystem imbalances due to heavy insecticide use. Understanding olive fly ecology is crucial for developing effective control strategies. The review explores the fly’s life cycle, its relationship with olive trees, and how environmental factors like temperature and humidity influence population dynamics. Additionally, studying the role of natural enemies and agricultural practices can pave the way for sustainable control methods that minimize environmental harm. Climate change, intensive cultivation, and the development of resistance to insecticides necessitate a shift towards sustainable practices. This includes exploring alternative control methods like biological control with natural enemies and attract-and-kill strategies. Furthermore, a deeper understanding of OLF ecology, including its response to temperature and its ability to find refuge in diverse landscapes, is critical for predicting outbreaks and implementing effective protection strategies. By employing a holistic approach that integrates ecological knowledge with sustainable control methods, we can ensure the continued viability of olive cultivation, protect the environment, and produce high-quality olive oil. Full article

Alkaline stress is one of the major abiotic constraints that limits plant growth and development. However, the genetic basis underlying alkaline tolerance in soybean [Glycine max (L.) Merr.] remains largely unexplored. In this study, an integrated genomic analysis approach was employed to elucidate the genetic architecture of alkaline tolerance in a diverse panel of 326 soybean cultivars. Through association mapping, we detected 28 single nucleotide polymorphisms (SNPs) significantly associated with alkaline tolerance. By examining the genomic distances around these significant SNPs, five genomic regions were characterized as stable quantitative trait loci (QTLs), which were designated as qAT1, qAT4, qAT14, qAT18, and qAT20. These QTLs are reported here for the first time in soybean. Seventeen putative candidate genes were identified within the physical intervals of these QTLs. Haplotype analysis indicated that four of these candidate genes exhibited significant allele variation associated with alkaline tolerance-related traits, and the haplotype alleles for these four genes varied in number from two to four. The findings of this study may have important implications for soybean breeding programs aimed at enhancing alkaline tolerance. Full article

This study coupled precision agriculture with agroecology to improve the agricultural systems’ sustainability in a climate variability context, characterized by fewer rainy days and more extreme events. A three-year comparative analysis was carried out in a durum wheat rotation, divided into two plots of 2.5 ha each, one managed with conventional methods (CP, sunflower as intermediate crop) and another managed with an agroecological approach (AE, field bean as green manure crop), featuring prescription maps for site-specific mineral fertilization. The statistical analysis of durum wheat parameters, soil characteristics, and economic variables was conducted alongside the examination of climatic data. In AE soil, the exchangeable calcium was statistically different from CP soil (6044 mg kg⁻¹ and 5660 mg kg⁻¹, respectively). Cation exchange capacity was significantly higher in AE (32.7 meq 100 g⁻¹), compared to CP (30.9 meq 100 g⁻¹). In AE, wheat yield (2.36 t ha⁻¹) was higher than in CP (2.07 t ha⁻¹), despite extreme rainfall causing flooding in some parts of the AE plot. The economic balance was only 6% in favor of CP (EUR + 2157), confirming the AE approach’s resilience (EUR + 2027), despite the higher costs of cover cropping and site-specific fertilization. The novelty of integration between “smartish” precision agriculture and agroecology allows for sustainable management. Full article

Burkina Faso faces chronic food insecurity because of adverse agroclimatic conditions and significant soil degradation. Mulching, the practice of applying organic or synthetic materials to the soil surface, offers a promising avenue for enhancing agricultural production in this challenging agroecological setting. This study utilized the Sustainable Intensification Assessment Framework (SIAF) to evaluate the ecological, economic, and social impacts of mulching on vegetable production in Burkina Faso. Experimental and survey data collected from Sonsongona village in Bobo-Dioulasso were used to compare the production of mulched and non-mulched vegetables (tomato, cabbage, and onion) across the five SIAF domains. A calibrated AquaCrop crop model was also applied with 30-year historical weather data to simulate mulched and non-mulched cabbages for the study site. Our results reveal that mulching conserves soil moisture, suppresses weed growth, and enhances soil fertility, contributing to enhanced vegetable production and long-term sustainability. Economically, adopting mulching positively influences vegetable yields, reduces labor requirements, and increases income for smallholder farmers. These mulching benefits lead to community empowerment, particularly among women farmers. Our findings highlight the multifaceted benefits of mulching, suggesting that it holds promise for increasing agricultural productivity and improving economic stability, ecological sustainability, and social well-being in Burkina Faso. These insights contribute to developing context-specific strategies for sustainable intensification, with applicability across similar agroecological contexts in sub-Saharan Africa and beyond. Full article

Northeast China, as a primary grain-producing region, has long drawn attention for its intensive groundwater extraction for irrigation. However, previous studies on the future spatiotemporal changes of groundwater storage (GWS) are lacking. Utilizing the Global Land Data Assimilation System Version 2.2 (GLDAS-2.2), which simulates groundwater storage (as Equivalent Water Height) using the Catchment Land Surface Model (CLSM-F2.5) and calibrates it with terrestrial water storage data from the GRACE satellite, we analyzed the spatiotemporal variations of GWS in northeast China and employed a Long Short-Term Memory (LSTM) neural network model to quantify the responses of GWS to future climate change. Maintaining current socio–economic factors and combining climate factors from four scenarios (SSP126, SSP245, SSP370, and SSP585) under the CMIP6 model, we predicted GWS from 2022 to 2100. The results indicate that historically, groundwater storage exhibits a decreasing trend in the south and an increasing trend in the north, with a 44° N latitude boundary. Under the four scenarios, the predicted GWS increments in northeast China are 0.08 ± 0.09 mm/yr in SSP126, 0.11 ± 0.08 mm/yr in SSP245, 0.12 ± 0.09 mm/yr in SSP370, and 0.20 ± 0.07 mm/yr in SSP585. Although overall groundwater storage has slightly increased and the model projections indicate a continued increase, the southern part of the region may not return to past levels and faces water stress risks. This study provides an important reference for the development of sustainable groundwater management strategies. Full article

Allium ursinum L. (Alliaceae) is a perennial geophyte known for its medicinal properties. This study examines the yield, morphological characteristics, and bioactive component composition of A. ursinum across forty-three different habitats in Serbia, focusing on the relationship between these factors and habitat conditions. Data on habitat locations and soil conditions were gathered from previous studies, while climate parameters were estimated using meteorological data from the Republic Hydrometeorological Institute of Serbia. Cluster analysis identified five habitat clusters, with the first and third clusters representing 88% of the sampled habitats. Fresh leaf yield H1:39.46–H15:564.83 g m⁻² was correlated with morphological parameters grouped into two clusters. A positive correlation was found between habitat conditions, particularly soil type and altitude. Spectrophotometric quantification of phenolics (1.47–2.49 mg FAE g⁻¹) and flavonoids (0.27–0.82 mg QE g⁻¹) identified five clusters, with soil type being the key factor influencing bioactive component concentration. A. ursinum displayed significant adaptability, thriving in higher altitudes and fertile soils, which enhanced yield and morphological traits, though inversely related to bioactive components. These findings support sustainable cultivation and conservation practices for A. ursinum. Full article

Agroecology is increasingly used to study the evolution of farms and food systems, in which livestock plays a significant part. While large-scale specialized livestock farms are sometimes criticized for their contribution to climate change and nutrient cycle disruption, interest in alternative practices such as raising multiple species, integrating crop and livestock, relying on pasture, and marketing through short supply chains is growing. Through a narrative review, we aimed to determine if the scientific literature allowed for an evaluation of the agroecological contribution of alternative livestock farming practices. Taking advantage of ruminants’ capacity to digest human-inedible plant material such as hay and pasture on marginal land reduces the competition between livestock feed and human food for arable land. Taking advantage of monogastric animals’ capacity to digest food waste or byproducts limits the need for grain feed. Pasturing spreads manure directly on the field and allows for the expression of natural animal behavior. Animals raised on alternative livestock farms, however, grow slower and live longer than those raised on large specialized farms. This causes them to consume more feed and to emit more greenhouse gases per unit of meat produced. Direct or short supply chain marketing fosters geographical and relational proximity, but alternative livestock farms’ contribution to the social equity and responsibility principles of agroecology are not well documented. Policy aimed at promoting practices currently in place on alternative livestock farms is compatible with agroecology but has to be envisioned in parallel with a reduction in animal consumption in order to balance nutrient and carbon cycles. Full article