Effect of particle size and spectral sub-range within the UV-VIS-NIR range using diffuse reflectance spectra on multivariate models in evaluating the severity of fusariosis in ground wheat

UV reflectance in crop remote sensing: Assessing the current state of knowledge and extending research with strawberry cultivars

Remote sensing of spectral reflectance is a crucial parameter in precision agriculture. In particular, the visual color produced from reflected light can be used to determine plant health (VIS-IR) or attract pollinators (Near-UV). However, the UV spectral reflectance studies largely focus on non-crop plants, even though they provide essential information for plant-pollinator interactions. This literature review presents an overview of UV-reflectance in crops, identifies gaps in the literature, and contributes new data based on strawberry cultivars. The study found that most crop spectral reflectance studies relied on lab-based methodologies and examined a wide spectral range (Near UV to IR). Moreover, the plant family distribution largely mirrored global food market trends. Through a spectral comparison of white flowering strawberry cultivars, this study discovered visual differences for pollinators in the Near UV and Blue ranges. The variation in pollinator visibility within strawberry cultivars underscores the importance of considering UV spectral reflectance when developing new crop breeding lines and managing pollinator preferences in agricultural fields.

Near-infrared spectroscopy as a potential tool with radial basis function for measurement of residual acrylamide in organic polymer

Poly(acrylamide-co-diallyldimethylammonium chloride) (PDA), which is usually prepared by free radical polymerization of acrylamide monomer (AM) onto the cationic monomer dimethyl diallyl ammonium chloride (DMDAAC), has been widely applied to wastewater treatment; however, the free-radical polymerization is always incomplete with residual AM remaining in the PDA. The residual AM affects the PDA's performance while also posing as a potential threat to human health; therefore, during preparation of the PDA, the rapid detection of the residual AM plays an important role in controlling the residual AM while improving the PDA's performance. The objective of this study was to explore the possibilities for applying near-infrared (NIR) spectroscopy as a potential tool for detecting the residual AM in combination with a statistical tool. In this study, the radial basis function (RBF) network model as the statistical tool was combined with NIR spectroscopy for detection of the residual AM. The experimental results showed that five wavelengths in the NIR spectroscopy were the most important characteristic adsorption peaks, particular at 971.95 and 1077 nm. The simulation of the RBF model presented higher performance with R2-value greater than 0.98, RMSEC and RMSEP less than 7.22 x 10(-5) and coefficient of variation (CV) of the predicted residual AM less than 10%, which demonstrated the feasibility of the NIR spectroscopy being a rapid detection tool for prediction of the residual AM using the RBF model. Wavelet de-nosing was used for removing the interference/noise in the NIR spectroscopy and improved the generalization ability of the RBF model.