A developed Near Infrared Reflectance Spectroscopy (NIRS) calibration equation was used for determining provitamin A carotenoids contents of different trials of fresh yellow root cassava genotypes using a total of 50 cassava genotypes scanned twice by NIRS from 400 nm to 2498 nm. The NIRS calibration equations were used to predict the β-cryptoxanthin, 13-cis β-carotene, trans β-carotene, 9-cis β -carotene, total β-carotene and total carotenoid concen- trations of the samples. The predicted values for total carotenoids (TC-pred) ranged from 3.93 µg g–1 to 10.51 µg g–1 with mean of 7.07 ± 2.55 µg g–1 for International Collaborative Trials (ICT), 7.97–11.03 µg g–1 fresh weight with mean of 9.40 ± 0.76 µg g–1 for yellow root trial 8 (Multi-location Uniform Yield Trial) and 6.38–10.44 µg g–1 with mean of 8.74 ± 1.07 µg g–1 for yellow root trial 9 (Multilocation Advanced Yield Trial). Total carotenoids results using refer- ence spectrophotometric method (TC-spec) ranged from 2.57 µg g–1 to 9.97 µg g–1 with mean of 5.66 ± 2.99 µg g–1 for ICT, 6.55–8.74 µg g–1 with mean of 7.74 ± 0.64 µg g–1 for yellow root trial 8 and 4.22–11.00 µg g–1 with mean of 7.57 ± 1.54 µg g–1 for yellow root trail 9. There is significant (P ≤ 0.001) positive cor- relation (r = 0.55) between TC-pred by NIRS and TC-spec. Also, significant (P ≤ 0.001) positive correlation (r = 0.52) exist between trans β-carotene predicted by NIRS and high-performance liquid chromatography reference. The developed NIRS calibration equations could be used to predict total carotenoids and trans β-carotene content of yellow root cassava and serve as rapid and cost-effective screening method for large cassava sample sets
CITATION STYLE
Alamu, E., Maziya-Dixon, B., Zum Felde, T., Kulakow, P., & Parkes, E. (2019). Application of near infrared reflectance spectroscopy in screening of fresh cassava (Manihot esculenta crantz) storage roots for provitamin A carotenoids. In Proceedings of the 18th International Conference on Near Infrared Spectroscopy (pp. 91–97). IM Publications Open LLP. https://doi.org/10.1255/nir2017.091
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