Deviations from optimal storage temperature and its impact on postharvest quality of table grape cv. Scarlotta Seedless

被引:4
|
作者
Owoyemi, Abiola [1 ,2 ]
Balaklav, Moria [3 ,4 ]
Kochanek, Bettina [1 ]
Porat, Ron [1 ]
Koenigstein, Noam [3 ]
Salzer, Yael [4 ]
Lichter, Amnon [1 ]
机构
[1] Agr Res Org, Volcani Inst, Dept Postharvest Sci Fresh Produce, IL-7528809 Rishon Leziyyon, Israel
[2] Hebrew Univ Jerusalem, Robert H Smith Fac Agr Food & Environm, Dept Plant Sci, Rehovot, Israel
[3] Tel Aviv Univ, Dept Ind Engn, POB 39040, IL-6997801 Tel Aviv, Israel
[4] Agr Res Org, Inst Agr Engn, Volcani Inst, IL-7528809 Rishon Leziyyon, Israel
关键词
Grape; Cold storage; Temperature interruption; First-In-First-Out (FIFO); First-In-First-Expired (FEFO); Modeling; RACHIS;
D O I
10.1016/j.postharvbio.2024.113013
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Although the optimal storage conditions for grapes are well-established, deviations can occur in commercial settings. Our goal was to study the extent to which these deviations will affect grape properties, and if this can be effectively modeled. In the first year, we focused on how constant temperature shifts affect grape properties; in the second, on how temperature interruptions in the first period of storage influence fruit quality. The main features quantified were weight loss, rachis browning, decay, firmness, bleaching, and cracking. With respect to a 2% threshold of decay, 0 degrees C enabled storage for 9 weeks, 3 degrees C for 6 weeks, and 6 degrees C for 3 weeks, all plus 3 d of shelf life, suggesting that storage temperature can be modified according to storage duration. Notably, temperature interruptions in the initial storage period demonstrated that the temperature of the interruption has a more significant impact on fruit quality than the duration of the interruption, particularly for weight loss and decay. Feature-importance analysis identified storage time as the primary factor influencing postharvest quality, but it highlighted the role of additional features as well. Dynamic models such as XGBoost consistently outperformed linear regression models in predicting both acceptance and rachis browning scores, but the latter had better R2 values. Results suggest that deviations from optimal storage conditions should be considered in future quality predictions and logistics management of grapes.
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页数:12
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