Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Індекс стиглості× | Симуляція зберігання після збору врожаю× | |
|---|---|---|
| Галузь | Садівництво | Садівництво |
| Родина | Process / pipeline | Process / pipeline |
| Рік появи≠ | 1970 | 2001 |
| Автор методу≠ | Pomology and horticulture research | Luc Tijskens and Bart Nicolaï |
| Тип≠ | multi-parameter assessment pipeline | computational modeling pipeline |
| Основоположне джерело≠ | Pratt, 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 ↗ |
| Інші назви | maturity index, harvest readiness assessment, fruit maturation scoring | shelf life prediction, storage modeling, quality decay simulation |
| Пов'язані | 4 | 4 |
| Підсумок≠ | Ripeness 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. |
| ScholarGateНабір даних ↗ |
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