Estimation of proximate, fatty acid, mineral content and proline level in Amaranth using near infrared reflectance spectroscopy

Abstract

For successful development of new amaranth varieties, it is important to find inexpensive and rapid analysis methods for the measurement of proximate, fatty acid, mineral content, and proline level in seeds. In this study, calibration equations in NIR spectroscopy were developed to estimate for the fatty acid, mineral content and proline level of amaranth using the modified partial least squares (MPLS) regression method. The calibrations estimated by NIR spectroscopy were consistent with the correlations between reference values at external validation. The equations developed were evaluated based on the relative estimate determination results for external validation (RPDv). The equations for total protein (RPDv = 2.967), fat (RPDv = 4.396), Zn (RPDv = 3.668), proline (RPDv = 6.692), oleic acid (RPDv = 3.366) and linoleic acid (RPDv = 2.086) showed high accuracy, while the equations for ash (RPDv = 1.675) and Fe (RPDv = 1.565) showed relatively high accuracy. When calculated with the same validation factors, the level of Ca (RPDv = 0.268), palmitic acid (RPDv = 1.434), stearic acid (RPDv = 0.949), linolenic acid (RPDv = 1.244) and arachidic acid (RPDv = 0.402) were lower than the estimated value. Protein, oil, ash, Fe, Zn, proline, oleic acid and linoleic acid can be used as reliable users, while equations developed for Ca, palmitic acid, stearic acid, linolenic acid and arachidic acid can be reliably used to screen samples for amaranth breeding programmes.