Applicability of near‐infrared reflectance spectroscopy (NIRS) for determination of crude protein content in cowpea (Vigna unguiculata) leaves

Abstract

There is uncertainty on how generally applicable near-infrared reflectance spectroscopy (NIRS) calibrations are across genotypes and environments, and this study tests how well a single calibration performs across a wide range of conditions. We also address the optimization of NIRS to perform the analysis of crude protein (CP) content in a variety of cowpea accessions (n = 561) representing genotypic variation as well as grown in a wide range of environmental conditions in Tanzania and Uganda. The samples were submitted to NIRS analysis and a predictive calibration model developed. A modified partial least-squares regression with cross-validation was used to evaluate the models and identify possible spectral outliers. Calibration statistics for CP suggests that NIRS can predict this parameter in a wide range of cowpea leaves from different agro-ecological zones of eastern Africa with high accuracy (R2cal = 0.93; standard error of cross-validation = 0.74). NIRS analysis improved when a calibration set was developed from samples selected to represent the range of spectral variability. We conclude from the present results that this technique is a good alternative to chemical analysis for the determination of CP contents in leaf samples from cowpea in the African context, as one of the main advantages of NIRS is the large number of compounds that can be measured at once in the same sample, thus substantially reducing the cost per analysis. The current model is applicable in predicting the CP content of young cowpea leaves for human nutrition from different agro-ecological zones and genetic materials, as cowpea leaves are one of the popular vegetables in the region.

A near-infrared reflectance spectroscopic method for the direct analysis of several fodder-related chemical components in drumstick (Moringa oleifera Lam.) leaves

“…The spectral shape was similar to that obtained by Chen et al, who used the same instrument to evaluate sheepgrass quality [18]. FD is useful in resolving overlapping bands and minimizing the effect of particle size [21,28,29]. SG can wipe out high frequency information, enhance signal to noise ratio and retain useful information.…”

“…The technique is based on the unique near-infrared (NIR) absorption properties of the major chemical components of a sample. NIRS has been used for more than 40 years [15,16], and the combination of NIRS and chemometric techniques has allowed the development of numerous models for the rapid analysis of forage crops, including soybean [17], sheepgrass [18], maize [19,20], and cowpea leaves [21]. Most calibration models have focused on organic matter such as crude protein, fat, and fiber [17,22].…”

Cowpea (Vigna unguiculata L. Walp), a renewed multipurpose crop for a more sustainable agri‐food system: nutritional advantages and constraints

“…With respect to the value of cowpea seeds as a source of proteins, values in the range 203–394 g kg −1 have been reported, which with the exception of soybean protein, is close to the content of the major and under‐utilised legumes . On the other hand, cowpea leaves, which constitute an under‐utilised vegetative part of this legume, compare well with cowpea seeds, with a protein content ranging from 215 to 437 g kg −1 …”

A simple and nondestructive approach for the analysis of soluble solid content in citrus by using portable visible to near‐infrared spectroscopy

“…Visible to near-infrared spectroscopy (Vis/NIRS) is a simple, fast, and nondestructive analytical technique, which is widely used in the analysis of complex samples in food (Towett et al, 2013;Zhu, Chen, Wu, Xing, & Yuan, 2018), agriculture (Tardaguila, Fernández-Novales, Gutiérrez, & Paz Diago, 2017), and medicine industries (Li, Du, Cai, & Shao, 2012). In recent years, the development trend of Vis/NIRS instruments is miniaturization and low manufacturing cost.…”