Exploring the use of near infrared reflectance spectroscopy to predict minerals in straw

Monitoring cotton (Gossypium hirsutum L.) leaf ion content and leaf water content in saline soil with hyperspectral reflectance

“…Wavelengths with high R 2 values can be useful for predicting ion contents. Bands with strong correlations were consistent with spectral regions associated with mineral and leaf water content reported by others [Aldana et al, 1995;Cozzolino and Moron, 2004;Huang et al, 2009;Tian et al, 2001]. The visible region from 350 to 700 nm showed a weak correlation with leaf ion contents and RWC.…”

Rapid Diagnosis of Nutrient Elements in Fingered Citron Leaf Using Near Infrared Reflectance Spectroscopy

“…These associations may lead to the assumption that NIRS can be considered as a tool to estimate the mineral contents in plants. Near infrared regions had considerable influence on the spectra due to the strong relationship between minerals and other constituents, mainly with O-H overtones (water) and with C-H combination tones (organic functional groups) (Cozzolino and Moron 2004;Garnsworthy et al, 2001;Huang et al 2009;Ko et al, 2004). However, compared with determining organics, the correlation coefficient, RSQ values, of measuring minerals are lower (in general, compare larger than 0.9 to less than 0.8) because low concentrations and a narrow range are generally observed for mineral concentrations, which could render RSQ values misleading (Clark et al, 1989;Nie et al, 2009).…”

“…According to Huang et al (2009), correlation coefficient (RSQ) for prediction of minerals increased with the mean of mineral concentration. This indicates that stronger responses may be interpreted from spectra with higher concentration of minerals and thus provide better correlations.…”

“…Thus, it is difficult to predict trace elements when concentration is less than 100 mg kg −1 . However, NIRS models about macro elements are better predictors (Huang et al, 2009;Petisco et al, 2005;Smith et al, 2001). Figure 1 shows the scatter plots of the predictions from the NIR spectra for N, P, Fe, and Mn by using an independent test set (n = 38).…”

Determination of Total Ash and Acid-insoluble Ash of Chinese Herbal Medicine Prunellae Spica by Near Infrared Spectroscopy

“…20) Huang et al reported that NIRS could be utilized for the prediction of K, Ca, Mg in dried milled straw and Mg in cut straw. 21) Good results were also obtained in prediction of minerals in legumes, alfalfa and woody plant. 22 24) It is reported that NIRS can measure these mineral constituents owing to the correlation between the minerals and the organic components, either through associations with organic molecules, chelates or forming salts which aŠects hydrogen bonding in samples.…”