Agriculture

The objective of this study was to evaluate the effects of age, sex, and dietary supplementation with resveratrol and defatted black soldier fly (Hermetiaconfirmedillucens) larvae meal (BSF) on the carcass traits, meat quality, and lipid profile in Manchurian Golden quail. A total of 180 birds were examined: 90 young quail at 35 days of age before the onset of laying and 90 older quail at 128 days of age during the laying period, with both sexes represented. The birds were assigned to three dietary treatments: a commercial basal diet, the same basal diet supplemented with 250 mg/kg of resveratrol, and a diet including 10% BSF. The carcass composition, meat physicochemical properties, lipid profile, and nutritional quality indices were analyzed. Older quail exhibited higher body, carcass, and organ weights and greater internal fat deposition, whereas younger quail showed more intense breast meat color and higher ash and cholesterol contents. Females generally demonstrated leaner carcasses and more favorable lipid profiles than males. Dietary BSF supplementation increased body weight and the intramuscular fat content but negatively influenced fatty acid indices, whereas resveratrol supplementation enhanced polyunsaturated fatty acid levels and the PUFA/SFA ratio (p < 0.001), despite an associated increase in meat cholesterol. Meat from older quail was tougher but showed healthier lipid characteristics, including higher (p < 0.001) PUFA proportions, lower (p < 0.001) atherogenic index (AI) and thrombogenic index (TI) values, and more favorable (p < 0.001) hypocholesterolemic/hypercholesterolemic fatty acid ratio (H/h) and health-promoting index (HPI) values. Overall, slaughtering dual-purpose quail after three months of laying did not compromise meat nutritional quality and may even enhance certain health-related attributes.

This review examines the potential impact of potato biofortification on boosting climate resilience and enhancing the nutritional content of potato tubers to combat hidden hunger. It also explores future possibilities for biofortified potatoes as a food source during space travel or colonization. Widespread mineral deficiencies are prevalent globally, particularly in developing countries. Additionally, climate change could adversely affect potato production and soil nutrient absorption. In this context, developing breeding methods to develop cultivars that respond better to biofortification amid climate change is essential. These cultivars may be physiologically efficient at absorbing and transporting minerals into tubers. The review covers various approaches, including identifying germplasm accessions with enhanced micronutrient storage, understanding mechanisms of micronutrient uptake and translocation, and pinpointing genes related to micronutrient, oligopeptide transport, and ligands. It also discusses in vitro selection and screening of calli with improved capacity for micronutrient absorption and transport.

Accurate and timely mapping of paddy rice is essential for agricultural management, food security, and climate-resilient policy. However, high-precision mapping remains challenging in subtropical monsoon regions due to persistent cloud cover, long revisit intervals, and striping noise, which compromise satellite data quality and availability. To address these limitations, a rice mapping framework suitable for different geographical environments was developed based on a random forest (RF) by combining time-series harmonic analysis (HANTS) with Sentinel-1 and Sentinel-2 multi-source data. To address these limitations, a rice mapping classification algorithm for different geographical environments was developed by combining Harmonic Analysis of Time Series (HANTS) with Sentinel-1/2 multi-source data. The research obtained annual maps of single-season and double-season rice in the research area from 2019 to 2024, with a spatial resolution of 10 m. The results indicated that the Sentinel-1, Sentinel-2, GEE, and HANTS algorithm can effectively support the yearly mapping of single- and double-season paddy rice in Anhui Province, China. The resultant paddy rice map has a high accuracy with overall accuracies exceeding 92% and Kappa coefficients above 0.84. HANTS effectively captures key phenological features of paddy rice, and it can especially enhance the discrimination between single- and double-season rice; compared to existing rice mapping products, the proposed approach reduces classification errors by an average of 3.92% in six major rice-producing cities, each with cultivation areas exceeding 1 million hectares; spatial correlation analysis indicates substantial heterogeneity in rice cultivation patterns across northern, central, and southern Anhui, associated with both biophysical and anthropogenic factors. These results indicate that integrating phenological data with machine learning can enhance the accuracy of long-term, high-resolution crop monitoring, and annual rice maps will offer valuable support for food security assessment, water resource management, and policy planning.