Almond is one of the most featured nut crops owing to its high nutritional value. However, due to three different waves of flower and fruitlet drop, fruit drop is a major concern for growers. In this study, we carried out a time-course transcriptome analysis to investigate gene expression differences between normal and abnormal fruitlet development. By de novo assembly analysis, we identified 33,577 unigenes and provided their functional annotations. In total, we identified 7,469 differentially expressed genes and observed the most apparent difference between normal and abnormal fruits at 12 and 17 days after flowering. Their biological functions were enriched in carbon metabolism, carbon fixation in photosynthetic organisms and plant hormone signal transduction. RT-qPCR validated the expression pattern of 14 representative genes, includingglycosyltransferase like family 2,MYB39,IAA13,gibberellin-regulated protein 11-likeandPOD44, which confirmed the reliability of our transcriptome data. This study provides an insight into the association between abnormal fruit development and carbohydrate signaling from the early developmental stages and could be served as useful information for understanding the regulatory mechanisms related to almond fruit drop.

Ethylene metabolism is very important for climacteric fruit, and apricots are typical climacteric fruit. The activity of pectinase is closely related to fruit firmness, which further affects fruit quality. To better understand ethylene metabolism, pectinase activity and their molecular regulation mechanisms during the development and ripening of apricot fruit, ethylene metabolism, pectinase activity and the “Luntaibaixing” apricot fruit transcriptome were analyzed at different developmental stages. Ethylene metabolic precursors, enzyme activities and ethylene release increased during fruit development and ripening, with significant differences between the ripening stage and other stages (P < 0.05). Fruit firmness decreased significantly from the S1 to S5 stages, and polygalacturonase, pectin methylesterase, and pectin lyase activities were significantly higher in the S5 stage than in other stages. RNA sequencing (RNA-seq) analysis of fruit resulted in the identification of 22,337 unigenes and 6629 differentially expressed genes (DEGs) during development and ripening, of which 20,989 unigenes are annotated in public protein databases. In functional enrichment analysis, DEGs among the three stages were found to be involved in plant hormone signal transduction. Four key genes affecting ethylene metabolism, six key ethylene signal transduction genes and seven genes related to pectinase in apricot fruit were identified by KEGG pathway analysis. By RNA-sequencing, we not only clarified the molecular mechanism of ethylene metabolism during the ripening of "Luntaibaixing" apricot fruit but also provided a theoretical basis for understanding pectin metabolism in apricot fruit.

Imbalanced and excessive fertilization leads to low nutrient utilization efficiency and wastage of fertilizer resources in processing tomatoes in Xinjiang. Determining nutrient requirements is vital for devising fertilization strategies that enhance yield, profitability, and environmental sustainability. This study utilized observational data from 181 farms across Xinjiang’s major processing tomato production areas from 2003 to 2023 to explore the relationship between fruit yield and nutrient uptake in aboveground dry matter. The Quantitative Evaluation of the Fertility of Tropical Soils (QUEFTS) model was employed to estimate nutrient requirements. The results indicated that when the target yield reached 60–70% of its potential, nutrient uptake by processing tomatoes increased linearly with fruit yield. To produce 1000 kg of fruit, the aboveground parts required 1.95 kg of nitrogen, 0.33 kg of phosphorus, and 2.28 kg of potassium, reflecting a N:P:K ratio of 1:0.17:1.17. In contrast, during harvesting, alternative plant parts required 1.31 kg of nitrogen, 0.21 kg of phosphorus, and 0.71 kg of potassium, with fruit nutrient uptake rates of 67.3%, 65.6%, and 74.9%, respectively. Field validation showed a strong correlation between the observed and simulated nutrient uptake rates, demonstrating the model’s accuracy in predicting nutrient demands. These findings provide critical insights for developing optimized fertilization strategies to enhance yield and nutrient use efficiency in Xinjiang’s processing tomato production.