Nitrogen / calcium ratio gives better prediction of kiwi fruit firmness during postharvest regarding the nutrients alone

Artificial intelligence systems have been employed for the development of predictive models that estimate many agricultural processes. In present study, the predictive capabilities of artificial neural networks (ANNs) were evaluated with respect to assessing fruit firmness as a postharvest life index, with determinations made at four stages of storage: 1, 60, 120 and 180?days after harvesting. Single concentrations of nitrogen (N), potassium (K), calcium (Ca) and magnesium (Mg) on fruit (D1 ), all of these nutrient concentrations (D2 ), the ratios of the nutrient concentrations alone (D3 ), and a combination of nutrient concentrations and their ratios (D4 ), were considered. The results obtained showed that fruit firmness at 1 and 60?days after harvesting was not influenced by nutrients. However, the ANN model estimated fruit firmness of 120 and 180?days, respectively, for D1 and D3 more accurately than for the D2 and D4 datasets. Application of D3 (nitrogen/calcium ratio) as the input dataset improved predictions of fruit firmness, with a correlation coefficient of 0.85 between the measured and estimated data.? SourcesUsing artificial neural network in determining postharvest life of kiwifruitMohammadi Torkashvand A 1 , Ahmadi A 2 , G?mez PA 3 , Maghoumi M 1?1.?Department of Horticultural Corps and Agronomy, Science and Research Branch, Islamic Azad University, Tehran, Iran.2.?Department of Soil Science, University of Tabriz, Tabriz, East Azerbaijan, Iran.3.?Institute of Plant Biotechnology, Universidad Polit?cnica de Cartagena, Campus Muralla del Mar, Cartagena, Murcia, Spain.Journal of the Science of Food and Agriculture [17 Jun 2019]DOI: 10.1002/jsfa.9866 Europe PMChttps://europepmc.org/abstract/med/31206684 Picture by?Supermercados Gadis, Beneficios del kiwi en ayunas y propiedades