Dataset Information

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

ABSTRACT: Rapid and accurate discrimination of alfalfa cultivars is crucial for producers, consumers, and market regulators. However, the conventional routine of alfalfa cultivars discrimination is time-consuming and labor-intensive. In this study, the potential of a new method was evaluated that used multispectral imaging combined with object-wise multivariate image analysis to distinguish alfalfa cultivars with a single seed. Three multivariate analysis methods including principal component analysis (PCA), linear discrimination analysis (LDA), and support vector machines (SVM) were applied to distinguish seeds of 12 alfalfa cultivars based on their morphological and spectral traits. The results showed that the combination of morphological features and spectral data could provide an exceedingly concise process to classify alfalfa seeds of different cultivars with multivariate analysis, while it failed to make the classification with only seed morphological features. Seed classification accuracy of the testing sets was 91.53% for LDA, and 93.47% for SVM. Thus, multispectral imaging combined with multivariate analysis could provide a simple, robust and nondestructive method to distinguish alfalfa seed cultivars.

SUBMITTER: Yang L

PROVIDER: S-EPMC7698633 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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

Yang Lingjie L Zhang Zuxin Z Hu Xiaowen X

Sensors (Basel, Switzerland) 20201118 22

Rapid and accurate discrimination of alfalfa cultivars is crucial for producers, consumers, and market regulators. However, the conventional routine of alfalfa cultivars discrimination is time-consuming and labor-intensive. In this study, the potential of a new method was evaluated that used multispectral imaging combined with object-wise multivariate image analysis to distinguish alfalfa cultivars with a single seed. Three multivariate analysis methods including principal component analysis (PC ...[more]

PMID: 33217897

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Project description:BackgroundNucleorhabdoviruses possess bacilliform particles which contain a single-stranded negative-sense RNA genome. They replicate and mature in the nucleus of infected cells. Together with viruses of three other genera of the family Rhabdoviridae, they are known to infect plants and can be transmitted by arthropod vectors, during vegetative propagation, or by mechanical means. In 2010, an alfalfa (Medicago sativa) plant showing virus-like symptoms was collected from Stadl-Paura, Austria and sent to Julius Kühn Institute for analysis.MethodsElectron microscopy (EM) of leaf extracts from infected plants revealed the presence of rhabdovirus-like particles and was further used for ultrastructural analyses of infected plant tissue. Partially-purified preparations of rhabdovirus nucleocapsids were used for raising an antiserum. To determine the virus genome sequence, high throughput sequencing (HTS) was performed. RT-PCR primers were designed to confirm virus infection and to be used as a diagnostic tool.ResultsEM revealed bacilliform virions resembling those of plant-infecting rhabdoviruses. HTS of ribosomal RNA-depleted total RNA extracts revealed a consensus sequence consisting of 13,875 nucleotides (nt) and containing seven open reading frames (ORFs). Homology and phylogenetic analyses suggest that this virus isolate represents a new species of the genus Nucleorhabdovirus (family Rhabdoviridae). Since the virus originated from an alfalfa plant in Austria, the name alfalfa-associated nucleorhabdovirus (AaNV) is proposed. Viroplasms (Vp) and budding virions were observed in the nuclei of infected cells by EM, thus confirming its taxonomic assignment based on sequence data.ConclusionsIn this study, we identified and characterised a new nucleorhabdovirus from alfalfa. It shared only 39.8% nucleotide sequence identity with its closest known relative, black currant-associated rhabdovirus 1. The virus contains an additional open reading frame (accessory gene) with unknown function, located between the matrix protein and the glycoprotein genes. Serological and molecular diagnostic assays were designed for future screening of field samples. Further studies are needed to identify other natural hosts and potential vectors.

Project description:Alfalfa (Medicago sativa) is the most widely grown and most important forage crop in the world. However, alfalfa is susceptible to waterlogging stress, which is the major constraint for its cultivation area and crop production. So far, the molecular mechanism of alfalfa response to the waterlogging is largely unknown. Here, comparative transcriptome combined with proteomic analyses of two cultivars (M12, tolerant; M25, sensitive) of alfalfa showing contrasting tolerance to waterlogging were performed to understand the mechanism of alfalfa in response to waterlogging stress. Totally, 748 (581 up- and 167 down-regulated) genes were differentially expressed in leaves of waterlogging-stressed alfalfa compared with the control (M12_W vs. M12_CK), whereas 1193 (740 up- and 453 down-regulated) differentially abundant transcripts (DATs) were detected in the leaves of waterlogging-stressed plants in comparison with the control plants (M25_W vs. M25_CK). Furthermore, a total of 187 (122 up- and 65 down-regulated) and 190 (105 up- and 85 down-regulated) differentially abundant proteins (DAPs) were identified via isobaric tags for relative and absolute quantification (iTRAQ) method in M12_W vs. M12_CK and M25_W vs. M25_CK comparison, respectively. Compared dataset analysis of proteomics and transcriptomics revealed that 27 and eight genes displayed jointly up-regulated or down-regulated expression profiles at both mRNA and protein levels in M12_W vs. M12_CK comparison, whereas 30 and 27 genes were found to be co-up-regulated or co-down-regulated in M25_W vs. M25_CK comparison, respectively. The strongly enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways for co-up-regulated genes at mRNA and protein levels in M12_W vs. M12_CK comparison were 'Amino sugar and nucleotide sugar metabolism', 'Arginine and proline metabolism' and 'Starch and sucrose metabolism', whereas co-up-regulated protein-related pathways including 'Arginine and proline metabolism' and 'Valine, leucine and isoleucine degradation' were largely enriched in M25_W vs. M25_CK comparison. Importantly, the identified genes related to beta-amylase, Ethylene response Factor (ERF), Calcineurin B-like (CBL) interacting protein kinases (CIPKs), Glutathione peroxidase (GPX), and Glutathione-S-transferase (GST) may play key roles in conferring alfalfa tolerance to waterlogging stress. The present study may contribute to our understanding the molecular mechanism underlying the responses of alfalfa to waterlogging stress, and also provide important clues for further study and in-depth characterization of waterlogging-resistance breeding candidate genes in alfalfa.

Dataset Information

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

Publications

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

Similar Datasets

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