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Индекс спелости×Моделирование хранения после сбора урожая×
ОбластьСадоводствоСадоводство
СемействоProcess / pipelineProcess / pipeline
Год появления19702001
Автор методаPomology and horticulture researchLuc Tijskens and Bart Nicolaï
Типmulti-parameter assessment pipelinecomputational modeling pipeline
Основополагающий источникPratt, H. K., & Goeschl, J. D. (2006). Physiological roles of ethylene in plants. Annual Review of Plant Physiology, 20, 541–566. DOI ↗Tijskens, L. M., & Polderdijk, J. J. (2001). A generic model for keeping quality of vegetable produce during storage and distribution. Postharvest Biology and Technology, 23(1), 13–25. link ↗
Другие названияmaturity index, harvest readiness assessment, fruit maturation scoringshelf life prediction, storage modeling, quality decay simulation
Связанные44
СводкаRipeness index combines multiple quality measurements—soluble solids, firmness, color, starch degradation, ethylene production—into a single composite score indicating fruit maturity and harvest readiness. Unlike single-parameter metrics, this integrated approach accounts for cultivar variation and environmental influence to predict consumer acceptability more reliably. It is widely adopted in export industries and research settings to standardize harvest decisions.Postharvest storage simulation uses computational models to predict fruit and vegetable quality degradation during storage and distribution under variable temperature and humidity conditions. Pioneered by Tijskens and Nicolaï in 2001, these mechanistic and empirical models enable logistics optimization, reduce food waste, and improve supply chain transparency. They are integrated into decision support systems for commercial packinghouses and research facilities.
ScholarGateНабор данных
  1. v1
  2. 2 Источники
  3. PUBLISHED
  1. v1
  2. 2 Источники
  3. PUBLISHED

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ScholarGateСравнение методов: Ripeness Index · Postharvest Storage Simulation. Получено 2026-06-19 из https://scholargate.app/ru/compare