Agriculture

Soluble solid content (SSC) is a key indicator of strawberry quality. Conventional SSC measurement methods are destructive and impractical for large-scale applications. Therefore, this study developed a region-based hyperspectral imaging (HSI) and lightweight one-dimensional convolutional neural network (1D CNN) framework for nondestructive SSC prediction in strawberries. To evaluate spatial effects on predictive accuracy, the fruit surface was segmented into five groups (G1–G5). Three spectral preprocessing methods were applied with partial least squares regression and five convolutional neural network (CNN) architectures, including a simplified VGG-CNN. Larger regions generally improved prediction performance; however, the 50% region (G2) and 75% region (G3) achieved comparable performance to the full region, reducing data requirements. The simplified VGG-CNN model with SNV outperformed other models, exhibiting high accuracy with reduced computational cost, supporting its potential integration into portable and real-time sensing systems. The proposed approach can contribute to improved postharvest quality control and enhanced consumer confidence in strawberry products.

Postharvest lignification of juice sacs in Meizhou pomelo is a major physiological disorder that compromises fruit quality and limits sustainable industry development. Through a comprehensive three-year field study, we investigated the effects of key factors—soil organic matter, storage temperature, and tree age—on fruit lignification, and evaluated the efficacy of ten plant growth regulators (PGRs) and their combinations in mitigating granulation. Our results demonstrated that soil rich in organic matter and exchangeable calcium significantly reduced the granulation index. Constant storage at 15 °C effectively suppressed weight loss and lignification compared to fluctuating ambient temperatures. Among the tested PGRs, 28-Homobrassinolide (28-homo-BR), 28-Epihomobrassinolide (28-epi-BR), 24-Epibrassinolide (24-epi-BR), and 14-Hydroxybrassinosteroid (14-hydro-BR) exhibited the most pronounced effects in alleviating granulation. Two superior PGR combinations were subsequently identified, which functioned by synergistically downregulating the activities of key phenylpropanoid pathway enzymes—phenylalanine ammonia-lyase, 4-coumarate: CoA ligase, cinnamyl alcohol dehydrogenase, and peroxidase. This downregulation likely contributed to reduced lignin biosynthesis and accumulation. Metabolomic profiling further revealed an accumulation of phenylpropanoid precursors, including ferulic acid and p-coumaric acid, in lignified juice sacs, indicating that the overactivation of this pathway is a key metabolic feature associated with lignification. This finding provides critical evidence for the potential mechanism whereby PGRs suppress lignification, thus offering both mechanistic insights and practical strategies for controlling lignification in pomelo and other citrus fruits.

The rhizosphere, a confined area of soil plant roots, is an intersection of microbial activity and root exudates. Known as the rhizosphere effect, it enhances crop yield and sustainability by improving nutrient availability, beneficial compounds, and pathogen control. This study combines a field-based rhizosphere–bulk soil comparison for peanut with a geostatistical approach to quantify the spatial variability of rhizosphere-driven changes in soil quality indicators in the Ghardaïa region (southern Algeria), which is known for its sandy–clay and sandy–loam soils. Samples of rhizosphere and bulk soils were prospected using a systematic plan. Subsequently, the pH, electrical conductivity, calcium carbonate, organic matter, total nitrogen, available phosphorus, total potassium, and soluble sodium were determined for each soil (rhizosphere and bulk soil). To assess the spatial variability of rhizosphere soil parameters, semi-variograms of the fitted models were generated using auto-kriging. The results showed that both types of soils were moderately alkaline, with a reduction of 5.52% in the pH of the rhizosphere compared to the bulk soils. Soils were relatively low in organic matter, with only 3.3% of soils having organic matter levels above 20 g kg⁻¹. However, organic matter contents were consistently higher in the rhizosphere (8.51 ± 4.59 g kg⁻¹) than in the bulk soil (6.78 ± 3.52 g kg⁻¹). In the rhizosphere, an increase of 10% in labile phosphorus was noted. Total nitrogen was increased by 52.57%. T-tests suggested no significant difference in potassium and sodium levels, and they were moderately present in both soils. Significantly positive relationships were noted between available phosphorus and total nitrogen (R = 0.59, p < 0.001). However, negative correlations were revealed between pH and organic matter available phosphorus (R = −0.77, p < 0.001) and pH and total nitrogen (R = −0.56, p < 0.01). These results indicate the effects of rhizosphere interactions on soil property improvements and their implications for sustainable agricultural practices, including crop rotation, intercropping, and green manure applications.