Analysis of some parameters influencing moisture quantity measurements in wheat with NIR technique

Mesić, Mirko; Ćorluka, Venco; Valter, Zdravko

doi:10.1109/icecom.2005.204959

Cited by 5 publications

(1 citation statement)

References 9 publications

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“…As a matter of fact, information about sample constituents can be recovered from the analysis of a diffused light spectrum. In particular, in the NIR spectral region, OH functional groups exhibit absorption peaks at 1200, 1450, and 1940 nm [4,5,[17][18][19]. Therefore, information about sample moisture content can theoretically be derived by analyzing the light diffusion spectrum in this NIR region.…”

Section: Measuring Principlementioning

confidence: 99%

Design and Performance of a Near-Infrared Spectroscopy Measurement System for In-Field Alfalfa Moisture Measurement

et al. 2022

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Near-infrared spectroscopy (NIRS) is widely used in fruit and vegetable quality evaluations, usually after harvesting. In particular, the moisture content is a key parameter for determining product quality; processing phase, e.g., drying process; and economical value. NIRS methods are well-established for laboratory practices where the specimens are properly prepared and measurement conditions are well controlled. On the other hand, it is known that in-field NIRS measurements present several difficulties, as many influencing variables, such as mechanical vibrations, electrical and optical disturbances, and dust or dirt in general, can affect the spectral measurement. In this paper, we propose the design and present the prototype of a NIRS-based measuring system for the rapid determination of the moisture content of bales. The new system uses of a halogen lamp illumination unit to recover water absorption spectral data in the range of 900–1700 nm. The compact stainless steel body makes the instrument portable and easy to transport for rapid in-field MC measurements. The prototype system was characterized and its performance extensively evaluated in a laboratory environment. Finally, a preliminary test was carried out, where the moisture contents of 12 freshly harvested crops samples were measured using the partial least squares (PLSs) regression method. The obtained results show that our prototype system can estimate the alfalfa moisture content information with a coefficient of determination R2 of 0.985 and a root mean square relative error of estimation of 7.1%.

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