Supervised Multivariate Analysis of Hyper-spectral NIR Images to Evaluate the Starch Index of Apples

Author:

Menesatti Paolo,Zanella Angelo,D’Andrea Stefano,Costa Corrado,Paglia Graziella,Pallottino Federico

Publisher

Springer Science and Business Media LLC

Subject

Industrial and Manufacturing Engineering,Process Chemistry and Technology,Safety, Risk, Reliability and Quality,Food Science

Reference27 articles.

1. Blanpied, G. D., & Silsby, K. J. (1992). Predicting harvest date windows for apples. Cornell Cooperative Extension Publication. Information Bulletin, 221, 1–12.

2. BonifaziSerrantiMenesatti, G.S.P. (2005). Hyperspectral imaging based techniques in ornamental stone characterization. In Y.-R. Chen (Ed.), Proceedings of the SPIE (The International Society for Optical Engineering) on Optical Sensors and Sensing Systems for Natural Resources and Food Safety and Quality, Vol. 5996 (pp. 203–214). Bellingham, WA: SPIE (International Society for Optical Engineering).

3. Brookfield, P., Murphy, P., Harker, R., & MacRae, E. (1997). Starch degradation and starch pattern indices; interpretation and relationship to maturity. Postharvest Biology and Technology, 1(I), 23–30. doi: 10.1016/S0925-5214(97)01416-6 .

4. Costa, C., Aguzzi, J., Menesatti, P., Antonucci, F., Rimatori, V., & Mattoccia, M. (2008b) Shape analysis of different populations of Ruditapes decussatus and R. philippinarum in relation to their geographical structure. Journal of Zoology. doi: 10.1111/j.1469-7998.2008.00469.x .

5. Costa, C., Angelini, C., Scardi, M., Menesatti, P. & Utzeri, C. (2008c) Using image analysis on the ventral colour pattern in Salamandrina perspicillata (Savi, 1821) (Amphibia, Salamandridae) to discriminate among populations. Accepted by Biological Journal of the Linnean Society, in press.

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