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Predicting physiological traits in wheat landraces using hyperspectral reflectance

By: Contributor(s): Material type: ArticleArticleLanguage: English Publication details: Mexico : CIMMYT, 2016.Subject(s): In: Proceedings of the 2nd International TRIGO Wheat Yield Potential p. 96-101Summary: This study investigates if the models predicting Vcmax, Vcmax25, J, Narea, SPAD, LMA, and Vcmax25/Narea with hyperspectral reflectance and partial least square regression (PLSR) can be used in wheat landraces other than those used to train the model. The set of genotypes consisted of 230 wheat landraces and 5 elite wheat genotypes. Reflectance and SPAD were measured in the first survey. From this, 21 wheat landraces and 2 elite wheat genotypes were measured for reflectance, SPAD, J800, LMA, and Narea in a second survey. Previously constructed models using hyperspectral reflectance were able to make useful predictions for J800 and more accurate predictions for SPAD, LMA, and N area.
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This study investigates if the models predicting Vcmax, Vcmax25, J, Narea, SPAD, LMA, and Vcmax25/Narea with hyperspectral reflectance and partial least square regression (PLSR) can be used in wheat landraces other than those used to train the model. The set of genotypes consisted of 230 wheat landraces and 5 elite wheat genotypes. Reflectance and SPAD were measured in the first survey. From this, 21 wheat landraces and 2 elite wheat genotypes were measured for reflectance, SPAD, J800, LMA, and Narea in a second survey. Previously constructed models using hyperspectral reflectance were able to make useful predictions for J800 and more accurate predictions for SPAD, LMA, and N area.

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