Zinc deficiency is common under heat stress, and further research is needed to determine how to enhance the fruit quality of mango trees through the use of three forms of zinc, namely Zn-NPs, zinc sulfate (ZnSO₄), and chelated zinc (Zn-chelated), as a foliar spray. This research was carried out using ten treatments to investigate the effect of zinc forms on the fruit quality of Timor mango trees. With a few notable exceptions, every fruit quality measurement (physical characteristics, chemical properties, mineral contents, and antioxidant compounds) responded to every treatment looked into; however, the extent of the reaction differed depending on the fruiting measurement. Furthermore, the Zn-NPs created a larger difference in the fruiting measurements than the ZnSO₄ and Zn-chelated forms. ZnO NPs at 100 ppm ranked first, followed by ZnO NPs in the first spray and zinc EDTA in the second spray, followed by ZnO NPs in the first spray and ZnSO₄ in the second, for all mineral content and antioxidant compound measurements and most of the fruit physico-chemical characteristics. In contrast, the lowest levels of minerals and antioxidant compounds and most of the fruit physico-chemical characteristics were found in the controls. The outcomes of the other treatments after the three treatments lay somewhere between these two extremes, and this pattern was detected throughout two seasons. Spraying Timor mango trees with nano, chelated, and sulfate zinc can be considered a safe and environmentally friendly natural method for improving fruit quality in abiotic stress regions.

The management of mango orchards is beset with a number of issues, including micronutrient deficits and significant fruit drop, which both contribute to decreases in mango tree output. Among these micronutrients, zinc is vital for increasing agricultural productivity, ensuring crop sustainability, and improving plant nutritional status during the growing season. To overcome zinc (Zn) deficiencies, this study was carried out during two successive seasons in an expected “Off” year (2022) and an expected “On” year (2023) on mature mango trees cv. Timor. To ameliorate this Zn deficiency, the effect of zinc in three forms—zinc oxide nanoparticles (ZnO NPs), sulfate (ZnSO₄), and chelated (Zn-chelated)—as a foliar sprayon leaves’ mineral, chlorophyll, total carotenoids, and total carbohydrate contents and productivity were studied. Ten spray treatments were used in this study, including nano zinc (100 ppm), zinc sulfate (0.1%), and chelated zinc (0.2%) on two occasions, 7 January and 4 weeks after the first application, either alone or in combination with each other as compared to the control. In both study seasons, the results showed that all the zinc forms in mineral, chelated, or nano form had a positive effect on the number of flowers per panicle, the percentage of fruit set, the number of fruits per panicle, and the number of fruits per tree, and it decreased the percentage of fruit drop. Furthermore, all zinc forms significantly increased the leaf N, P, K, Ca, Mg, Cu, Fe, Mn, B, and Zn contents (%), and all the treatments improved the chlorophyll, total carotenoid, and total carbohydrate contents compared with the other treatments. The most effective treatment was two applications of nano zinc at 100 ppm in terms of the nutritional status and productivity of Timor mango trees.

Most existing techniques for assessing mango quality rely on biochemical analyses that destroy the fruit. This study evaluated and predicted the quality parameters of Timor mangoes using an artificial neural network (ANN) model. Data were collected from nine plantation sites in Gizan, Jazan Province, southwestern Saudi Arabia, over two growing seasons. The ANN model was configured with a 6-30-8 architecture and trained using 54 data patterns, while 18 patterns were used for testing. The input variables included peel weight, fruit length, fruit weight, fruit width, stone weight, and fruit firmness. The predicted output variables were ash content, pH, total soluble solids (TSS), titratable acidity (TA), vitamin C (VC), carotenoid content, total sugar content (TSC), and reducing sugar content (RSC) in mango juice, representing key internal quality attributes. The ANN model demonstrated satisfactory predictive performance on the testing dataset, with coefficients of determination (R2) of 0.9537, 0.9807, 0.9892, 0.9894, 0.9912, 0.9928, 0.9779, and 0.8436, respectively, for the output variables following the aforementioned sequence. These findings indicate that the proposed ANN-based approach is an effective, nondestructive tool for predicting internal mango quality attributes at harvest.