Chemometric tools for NIRS and NIR hyperspectral imaging

Nowadays in agriculture, new analytical tools based on spectroscopic technologies are developed. Near Infrared Spectroscopy (NIRS) is a well known technology in the agricultural sector allowing the acquisition of chemical information from the samples with a large number of advantages, such as: easy to use tool, fast and simultaneous analysis of several components, non-polluting, non-invasive and non destructive technology, and possibility of online or field implementation. Recently, NIRS system was combined with imaging technologies creating the Near Infrared Hyperspectral Imaging system (NIR-HSI). This technology provides simultaneously spectral and spatial information from an object. The main differences between NIR-HSI and NIRS is that many spectra can be recorded simultaneously from a large area of an object with the former while with NIRS only one spectrum was recorded for analysis on a small area. In this work, both technologies are presented with special focus on the main spectrum and images analysis methods. Several qualitative and quantitative applications of NIRS and NIR-HSI in agricultural products are listed. Developments of NIRS and NIR-HSI will enhance progress in the field of agriculture by providing high quality and safe agricultural products, better plant and grain selection techniques or compound feed industry’s productivity among others.Peer reviewe

A review of optical nondestructive visual and near-infrared methods for food quality and safety

This paper is a review of optical methods for online nondestructive food quality monitoring. The key spectral areas are the visual and near-infrared wavelengths. We have collected the information of over 260 papers published mainly during the last 20 years. Many of them use an analysis method called chemometrics which is shortly described in the paper. The main goal of this paper is to provide a general view of work done according to different FAO food classes. Hopefully using optical VIS/NIR spectroscopy gives an idea of how to better meet market and consumer needs for high-quality food stuff.©2013 the Authors. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.fi=vertaisarvioitu|en=peerReviewed

Using infrared spectroscopy to evaluate physiological ageing in stored potatoes (Solanum tuberosum)

The potato tuber is one of world’s largest food crops and in most growing regions is only harvested once a year. A proportion of tubers must therefore be stored efficiently to ensure there are enough provisions to last until the next harvest. Dormancy break during storage causes reduced tuber quality and potentially considerable losses. The aim of this work has been to determine whether Vis/NIR Spectroscopy can be used to monitor tuber dormancy, and further, to predict the onset of sprouting within a potato tuber. Small changes in Chlorophyll (Chl) production can be tracked in the tissue under the surface skin of a potato tuber, using a Vis/NIR spectrometer equipped with a fibre-optic probe. A static experimental setup yielded precise measurements of these subtle changes when the tuber was stimulated with light, long before visible greening occurred. It was found that there is a greater capacity for Chl production around the apical buds or “eyes” of a tuber compared with the surrounding tissue. These results held true for several cultivars from multiple harvests over the four years of the project. The technique however is very sensitive to the exact positioning of the tuber-probe alignment, due to the highly localised area of increased activity in the Chl production under an eye and the shape of the tuber itself. Although Chl is not produced in tubers whilst kept in cold dark storage, a tuber’s capacity to produce Chl once removed was found to change over the course of long-term storage. This behaviour was well fitted by a generalised logistic function. Prediction of the onset of dormancy break could be made from the shape of the curve from individual tuber batches. A proviso throughout is that sufficient tubers need to be analysed to obtain a meaningful batch average. The large tuber-to-tuber variance in behaviour remains the greatest challenge to translating this work into real world settings