Predicting Loquat Quality Using Visible, Near Infrared Spectroscopy and Artificial Neural Network
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-68660-3_1
Reference27 articles.
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2. Gisbert, A.D., Romero, C., Martínez-Calvo, J., Leida, C., Llácer, G., Badenes, M.L.: Genetic diversity evaluation of a loquat (Eriobotrya japonica (Thunb) Lindl) germplasm collection by SSRs and S-allele fragments. Euphytica 168, 121–134 (2009). https://doi.org/10.1007/s10681-009-9901-z
3. Tian, S., Li, B., Ding, Z.: Physiological properties and storage technologies of loquat fruit. Fresh Prod. 1, 76–81 (2007)
4. Liu, C., Zheng, H., Sheng, K., Liu, W., Zheng, L.: Effects of melatonin treatment on the postharvest quality of strawberry fruit. Postharvest Biol. Technol. 139, 47–55 (2018). https://doi.org/10.1016/j.postharvbio.2018.01.016
5. Cai, J., Chen, T., Zhang, Z., Li, B., Qin, G., Tian, S.: Metabolic dynamics during loquat fruit ripening and postharvest technologies. Front. Plant Sci. 10 (2019). https://doi.org/10.3389/fpls.2019.00619
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