Evaluation of the effect of moisture content on cereal grains by digital image analysis

By A. R. Tahir, Suresh Neethirajan, Digvir S. Jayas, M. Shahin, S. Symons, N. White. 2007

62 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Nutrition and Dietetics, Plant Science

View Paper: https://www.semanticscholar.org/paper/201fb87c9cb13a6f1f265b2ebfe423facbe3dc51

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1. Jaemyung Shin
2. Jian Jin
3. Md. Sultan Mahmud
4. Young K. Chang
5. Tanzeel U. Rehman
6. D. Saha
7. Rohit Sharma

Citations in the corpus

• Current and future applications of statistical machine learning algorithms for agricultural machine vision systems (2019, methodology): “The combination of colour, shape and textural features was used to quantify the effect of different moisture levels on the appearance and grain kernel morphology (Tahir et al., 2007).”