Cultivars identification of oat (Avena sativa L.) seed via multispectral imaging analysis

Abstract

Cultivar identification plays an important role in ensuring the quality of oat production and the interests of producers. However, the traditional methods for discrimination of oat cultivars are generally destructive, time-consuming and complex. In this study, the feasibility of a rapid and nondestructive determination of cultivars of oat seeds was examined by using multispectral imaging combined with multivariate analysis. The principal component analysis (PCA), linear discrimination analysis (LDA) and support vector machines (SVM) were applied to classify seeds of 16 oat cultivars according to their morphological features, spectral traits or a combination thereof. The results demonstrate that clear differences among cultivars of oat seeds could be easily visualized using the multispectral imaging technique and an excellent discrimination could be achieved by combining data of the morphological and spectral features. The average classification accuracy of the testing sets was 89.69% for LDA, and 92.71% for SVM model. Therefore, the potential of a new method for rapid and nondestructive identification of oat cultivars was provided by multispectral imaging combined with multivariate analysis.

Evaluation of oat (Avena sativa L.) populations for autumn sowing production in Southwest China

“…Utilizing this brief period for sowing forage crops could relieve the shortage by providing an alternative growing region, particularly during the winter and early spring seasons when livestock consumption demands are at their highest and the lower light intensity limits the growth of food crops (Xu et al, 2021). Oat ( Avena sativa L.) is one of the world's most cultivated cool‐season forage cereal crops and provides a vital source of livestock feed (Fu et al, 2023). The widespread popularity of oats as a source of high‐quality forage can largely be attributed to their tolerance to cold, drought, and barren soils (Usman et al, 2018), as well as their high forage yield, good nutritional value, palatability, and digestibility (Kanwal et al, 2022).…”

“…sowing forage crops could relieve the shortage by providing an alternative growing region, particularly during the winter and early spring seasons when livestock consumption demands are at their highest and the lower light intensity limits the growth of food crops (Xu et al, 2021). Oat (Avena sativa L.) is one of the world's most cultivated cool-season forage cereal crops and provides a vital source of livestock feed (Fu et al, 2023).…”

Integrating optical imaging techniques for a novel approach to evaluate Siberian wild rye seed maturity

“…For example, feature filtering algorithms such as minimal joint mutual information maximization (JMIM) ( Kursa, 2018 ), information gain ( Zawadzki and Kosinski, 2019 ), and Gini impurity ( Bommert et al., 2020 ) have been shown to effectively reduce the dimensionality of high-dimensional data. However, current researches were mainly on individual datasets ( França-Silva et al., 2020 ; Fu et al., 2023 ), while little research has been reported on the use of feature filtering algorithms on multi-source fused data.…”

Grassland, forage, and turfgrass science in China

“…Oat is one of the world's most cultivated cool-season forage cereal crops and provides a vital source of livestock feed (Fu et al, 2023). In this issue, Yuan et al (2024) In semi-arid and arid areas in Northwest China, shrubs are grown to reduce soil erosion, combat desertification, provide ecological protection, and enhance livestock production.…”

“…Oat is one of the world's most cultivated cool‐season forage cereal crops and provides a vital source of livestock feed (Fu et al, 2023). In this issue, Yuan et al (2024) studied variations of seed number and seed size in 23 oat ( Avena sativa L.) cultivars and concluded that the double‐seed spikelet number is a key ear characteristic when breeding high‐yielding cultivars.…”