Сравнение на методи
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| Индекс на зрялост× | Симулация на съхранение след прибиране на реколтата× | |
|---|---|---|
| Област | Градинарство | Градинарство |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 1970 | 2001 |
| Създател≠ | Pomology and horticulture research | Luc Tijskens and Bart Nicolaï |
| Тип≠ | multi-parameter assessment pipeline | computational modeling pipeline |
| Основополагащ източник≠ | 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 ↗ |
| Други названия | maturity index, harvest readiness assessment, fruit maturation scoring | shelf life prediction, storage modeling, quality decay simulation |
| Свързани | 4 | 4 |
| Резюме≠ | 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. |
| ScholarGateНабор от данни ↗ |
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