Prediction Model of the Key Components for Lodging Resistance in Rapeseed Stalk Using Near-Infrared Reflectance Spectroscopy (NIRS)

Abstract

The chemical composition of rape stalk is the physiological basis for its lodging resistance. By taking the advantage of NIRS, we developed a rapid method to determine the content of six key composition without crushing the stalk. Rapeseed stalks in the mature stage of growth were collected from three cultivation modes over the course of 2 years. First, we used the near-infrared spectroscope to scan seven positions on the stalk samples and took their average to form the spectral data. The stalks were then crushed and sieved; then the ratio of carbon and nitrogen, ratio of acid-insoluble lignin and lignin, and the content of soluble sugar and cellulose were determined using the combustion method, weighing method, and colorimetric method, respectively. The partial least squares regression (PLSR) method was used to establish a prediction model between the spectral data and the chemical measurements, and all models were evaluated by an internal interaction verification and an external independent test set sample. To improve the accuracy of the model and reduce the computing time, some optimization methods have been applied. Some outliers were removed, and then the data were preprocessed to determine the best spectral information band and the optimal principal component number. The results showed that elimination of outliers effectively improved the precision of the prediction model and that no spectral pretreatment method exhibited the highest prediction accuracy. In summary, the NIRS-based prediction model could facilitate the rapid nondestructive detection in the key components of rapeseed stalk.

Modelling the impact of cabbage stem flea beetle larval feeding on oilseed rape lodging risk

“…28,[41][42][43] Lignin, cellulose, hemicellulose and chitin are known to impact the elastic modulus, therefore affecting the flexural rigidity of the basal stem. 44,45 Silicon is an important structural component related to stem strength, and the application of silicon could increase the content of lignin in sclerenchyma cells, consequently improving stem strength in OSR crops. 46 Further studies should investigate cell wall structure in crops affected by CSFB to understand whether increased lodging risk is related to both physiological and biochemical changes.…”

“…Several studies have identified relationships between root characteristics and lodging risk. 26,[43][44][45][46][47][48] To understand the potential impact of CSFB on root anchorage further, inoculation experiments with different larval populations could be used to measure the impact of larvae on rooting traits.…”

“…Whilst this indicates that CSFB tunnelling predominantly leads to physiological impacts, there are several biochemical factors that could also be impacted, including lignin biosynthesis, cellulose biosynthesis and silica uptake 28,41–43 . Lignin, cellulose, hemicellulose and chitin are known to impact the elastic modulus, therefore affecting the flexural rigidity of the basal stem 44,45 . Silicon is an important structural component related to stem strength, and the application of silicon could increase the content of lignin in sclerenchyma cells, consequently improving stem strength in OSR crops 46 .…”

“…The impact of CSFB tunnelling on OSR stem lodging has been presented here, but it is also plausible that injury caused to the plant from adult CSFB feeding may compromise root development, which could reduce root anchorage strength, and thus increase lodging risk further. Several studies have identified relationships between root characteristics and lodging risk 26,43–48 . To understand the potential impact of CSFB on root anchorage further, inoculation experiments with different larval populations could be used to measure the impact of larvae on rooting traits.…”

Prediction of chemical compositions of crushed maize used in meat animal ration using near infrared spectroscopy and multivariate analysis

“…The intensive production system depends on balanced compound diets where feed cost represents 65-70% of the total production cost of livestock farming. However, proper attention should be given to evaluate the nutritional quality of feed ingredients in order to supply the adequate amount of balanced diet for animals to maximize the effective production cost (Panda et al, 2014;Kuai et al, 2019).…”