Using Near-Infrared Spectroscopy in Agricultural Systems

Abstract

This chapter provides a review on the state of art of the use of the visible near-infrared (vis-NIR) spectroscopy technique to determine mineral nutrients, organic compounds, and other physical and chemical characteristics in samples from agricultural systemssuch as plant tissues, soils, fruits, cocomposted sewage sludge and wastes, cereals, and forage and silage. Currently, all this information is needed to be able to carry out the appropriate fertilization of crops, to handle agricultural soils, determine the organoleptic characteristics of fruit and vegetable products, discover the characteristics of the various substrates obtained in composting processes, and characterize byproducts from the industrial sector. All this needs a large number of samples that must be analyzed; this is a time-consuming work, leading to high economic costs and, obviously, having a negative environmental impact owing to the production of noxious chemicals during the analyses. Therefore, the development of a fast, environmentally friendly, and cheaper method of analysis like vis-NIR is highly desirable. Our intention here is to introduce the main fundamentals of infrared reflectance spectroscopy, and to show that procedures like calibration and validation of data from vis-NIR spectra must be performed, and describe the parameters most commonly measured in the agricultural sector.

Near-Infrared Spectroscopy in Bio-Applications

“…The method accurately predicted the raw material content in several commercially available products and identified products that did not contain crude Echinacea material as well. Analysis of chemical compositions and various other properties of plants is often the main aim of various applications in agro-food sector [81]. The potential of NIR hyperspectral imaging is increasing with new approaches to process and analyze spectral images.…”

“…Analysis of chemical compositions and various other properties of plants is often the main aim of various applications in agro-food sector [ 81 ]. The potential of NIR hyperspectral imaging is increasing with new approaches to process and analyze spectral images.…”

A Regional Legacy Soil Dataset for Prediction of Sand and Clay Content with Vis-Nir-Swir, in Southern Brazil

“…For clay, MSC and NBR achieved the best performance with the SVM, GPR, and PLS models. These preprocessing techniques are normalization procedures commonly used to compensate for baseline shift and multiplicative effects in the spectral data, which are induced by physical effects such as particle size (Martens and Naes, 1992;Rinnan et al, 2009;García-Sánchez et al, 2017). The MSC, which attempts to eliminate the effects of the spectrum by linearizing each spectrum by the average spectrum of the sample, is the most popular normalization technique (Martens and Naes, 1992).…”

Phylogeography and rhizobia-legume genotypic interactions in common bean (Phaseolus vulgarisL.) and chickpea (Cicer arietinumL.) in Ethiopia

“…Nitrogen concentration in plant shoots was estimated using near-infrared spectroscopy (NIRS) method at Nutrition Lab at International Livestock Research Institute (ILRI), Ethiopia, following the standard protocols (Unkovich et al 2008;García-Sánchez et al 2017). Plant shoot samples were oven dried at 70 O C for 48 hours and powdered using mortar and pestle to pass through a 1 mm mesh.…”

“…The prepared samples were again oven dried at 40 O C for overnight and stored in a desiccator containing a silica gel before scanning the samples using an automated NIRS spectrometer. Ten percent of the samples were purposely selected by considering all the genotypes and subjected to Kjeldahl wet-chemical analysis method to determine plant total nitrogen and used to calibrate the NIRS method (Unkovich et al 2008;García-Sánchez et al 2017).…”