Non-destructive identification of single hard seed via multispectral imaging analysis in six legume species

Abstract

Background: Physical dormancy (hard seed) occurs in most species of Leguminosae family and has great consequences not only for ecological adaptation but also for agricultural practice of these species. A rapid, nondestructive and on-site screening method to detect hard seed within species is fundamental important for maintaining seed vigor and germplasm storage as well as understanding seed adaptation to various environment. In this study, the potential of multispectral imaging with object-wise multivariate image analysis was evaluated as a way to identify hard and soft seeds in Acacia seyal, Galega orientulis, Glycyrrhiza glabra, Medicago sativa, Melilotus officinalis, and Thermopsis lanceolata. Principal component analysis (PCA), linear discrimination analysis (LDA), and support vector machines (SVM) methods were applied to classify hard and soft seeds according to their morphological features and spectral traits. Results: The performance of discrimination model via multispectral imaging analysis was varied with species. For M. officinalis, M. sativa, and G. orientulis, an excellent classification could be achieved in an independent validation data set. LDA model had the best calibration and validation abilities with the accuracy up to 90% for M. sativa. SVM got excellent seed discrimination results with classification accuracy of 91.67% and 87.5% for M. officinalis and G. orientulis, respectively. However, both LDA and SVM model failed to discriminate hard and soft seeds in A. seyal, G. glabra, and T. lanceolate. Conclusions: Multispectral imaging together with multivariate analysis could be a promising technique to identify single hard seed in some legume species with high efficiency. More legume species with physical dormancy need to be studied in future research to extend the use of multispectral imaging techniques.

Cultivar Discrimination of Single Alfalfa (Medicago sativa L.) Seed via Multispectral Imaging Combined with Multivariate Analysis

“…Multispectral imaging technology integrates conventional imaging and spectroscopy information simultaneously, and is non-destructive, simple, rapid, and does not have the requirement of sample pre-treatment [ 9 , 10 ]. These merits make it suitable for seed purity testing and seed contamination determination.…”

Non-Destructive Identification of Naturally Aged Alfalfa Seeds via Multispectral Imaging Analysis

“…The multispectral imaging data was recorded in MSI VideometerLab4 (Videometer A/S, Herlev, Denmark), which contains 19 monochrome light-emitting diodes (LEDs) with non-uniform wavelength distribution, i.e., 375, 405, 430, 450, 470, 505, 525, 570, 590, 630, 645, 660, 700, 780, 850, 870, 890, 910, 940 and 970 nm. The LEDs flash continuously in a scan time of five seconds and produce a monochrome image at each wavelength [ 31 , 32 ]. Before the spectral information was collected, the 100 seeds in the five aging groups were numbered as 1~100, and each petri dish with 25 seeds was placed into the instrument for signal recording.…”

“…The 70% of the seeds in each sample harvest year were randomly selected as the training set and the other 30% were used for model testing. The classification performance of the model was evaluated by accuracy, sensitivity and specificity [ 31 ], with formula as followed. …”

The Use of Multispectral Imaging and Single Seed and Bulk Near-Infrared Spectroscopy to Characterize Seed Covering Structures: Methods and Applications in Seed Testing and Research

“…Hu et al [54] examined seeds of six species within the Fabaceae family with MSI for the detection of hard seeds. For each species, 400 seeds were examined 70:30 in training and testing set, respectively, and following image acquisition seeds were imbibed for germination.…”

“…In all three species studied, hard seeds showed a higher reflectance compared to non-hard seeds. Hu et al [54] used SVM analysis and found that wavelengths in the NIR-region, i.e., 970 nm (water) and 940 nm (lipids, were of highest importance in the separation of the two groups. However, for each species only one seed lot was represented in the analysis and there were proportionally fewer non-hard seeds which made the two groups unbalanced.…”