Ripeness Classification of Astringent Persimmon Using Hyperspectral Imaging Technique

By Xuan Wei, Fei Liu, Zhengjun Qiu, Yongni Shao, Yong He. Food and Bioprocess Technology, 2014

104 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Plant Science

View Paper: https://www.semanticscholar.org/paper/7274a5dc72957cbb8e625fef7caa23e843953264

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. Sergio Cubero
2. Fei Liu
3. Chu Zhang
4. Hao Jiang
5. José Blasco
6. P. Talens
7. Sandra Munera
8. Nuria Aleixos

In Plant Science

1. Chu Zhang
2. Hao Jiang
3. Fei Liu
4. José Blasco
5. P. Talens
6. Sandra Munera
7. Nuria Aleixos
8. Sergio Cubero

Citations in the corpus

• Application of Near-Infrared Hyperspectral Imaging with Variable Selection Methods to Determine and Visualize Caffeine Content of Coffee Beans (2016, methodology): “In recent years, hyperspectral imaging technique has been used in food (Wei et al. 2014), agricultural (Zhang and He 2013), pharmaceutical (Roggo et al.”
• Astringency assessment of persimmon by hyperspectral imaging (2017, methodology): “The results were not as good as 311 the prediction results of Wei et al. (2014), who achieved an R 2 value of 0.91, but they 312 worked with non-treated fruit having higher firmness differences between the harvest and 313 the marketing.”