Advances in Non-Destructive Early Assessment of Fruit Ripeness towards Defining Optimal Time of Harvest and Yield Prediction-A Review.
Advances in Non-Destructive Early Assessment of Fruit Ripeness towards Defining Optimal Time of Harvest and Yield Prediction-A Review.
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DOI：
10.3390/plants7010003
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发表时间：
2018-01-10
期刊：
影响因子：
--
通讯作者：
Bishop G
中科院分区：
文献类型：
--
作者：
Li B;Lecourt J;Bishop G
为日益增加的世界人口提供全球粮食安全，不仅需要增加可持续的粮食生产，而且需要大幅度减少收获前后的浪费。水果收获的时机对于减少供应链中的沿着浪费和提高消费者的水果质量至关重要。通过非破坏性技术对水果成熟度的早期田间评估和对收获日期和产量的预测有可能彻底改变农业实践，使消费者能够吃到最美味和最新鲜的水果。各种非破坏性技术已被应用于估计成熟度或成熟度，但并非所有这些都适用于原位（田间或温室）评估。本文主要介绍了目前国内外在采前田间检测中应用最广泛的无损检测方法，包括色度学、可见光成像、光谱学和光谱成像等。还讨论了用于评估成熟度的机器学习和回归模型。
Global food security for the increasing world population not only requires increased sustainable production of food but a significant reduction in pre- and post-harvest waste. The timing of when a fruit is harvested is critical for reducing waste along the supply chain and increasing fruit quality for consumers. The early in-field assessment of fruit ripeness and prediction of the harvest date and yield by non-destructive technologies have the potential to revolutionize farming practices and enable the consumer to eat the tastiest and freshest fruit possible. A variety of non-destructive techniques have been applied to estimate the ripeness or maturity but not all of them are applicable for in situ (field or glasshouse) assessment. This review focuses on the non-destructive methods which are promising for, or have already been applied to, the pre-harvest in-field measurements including colorimetry, visible imaging, spectroscopy and spectroscopic imaging. Machine learning and regression models used in assessing ripeness are also discussed.
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影响因子：
6
作者：
Camps, C.;Christen, D.
通讯作者：
Christen, D.
影响因子：
5.1
作者：
Chia, Kim Seng;Rahim, Herlina Abdul;Rahim, Ruzairi Abdul
通讯作者：
Rahim, Ruzairi Abdul
DOI：
10.13031/2013.27827
发表时间：
1995-01-01
期刊：
TRANSACTIONS OF THE ASAE
影响因子：
--
作者：
CHOI, K;LEE, G;BUNN, JM
通讯作者：
BUNN, JM
影响因子：
7.4
作者：
Centner, V;Massart, DL;Sterna, C
通讯作者：
Sterna, C
影响因子：
6.1
作者：
Clement, Alain;Dorais, Martine;Vernon, Marcia
通讯作者：
Vernon, Marcia