大豆种子批次分类的机器学习

IF 0.9 4区农林科学 Q3 AGRICULTURAL ENGINEERING

Engenharia Agricola Pub Date : 2022-01-01 DOI:10.1590/1809-4430-eng.agric.v42nepe20210101/2022

G. I. Gadotti, C. Ascoli, Ruan Bernardy, R. D. C. M. Monteiro, R. D. Pinheiro

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引用次数: 5

摘要

种子萌发和活力评价是播种部门衡量不同种子批次的表现，提高储存和播种效率的重要手段。然而，通过分析各种测试来确定种子质量会产生大量信息，这使得人类几乎不可能进行快速有效的质量控制分析。因此，本研究的目的是利用机器学习技术对不同品种大豆种子的生理品质进行排序，以评估不同品种大豆种子的生理品质差异。选用3个品种，对65批的发芽、加速老化、四氮唑处理、出苗和1000粒重进行了分析。这些葡萄酒分两个阶段进行评估，一个是在收获后立即进行评估，另一个是在储存六个月后进行评估。使用随机森林、多层感知器、J48和回归分类器进行分类，并辅以特征重采样技术。随机森林和

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MACHINE LEARNING FOR SOYBEAN SEEDS LOTS CLASSIFICATION

The seed germination and vigor evaluation are essential for the sowing sector to measure the performance of different seed lots and improve the efficiency of storage and sowing processes. However, the analysis of various tests to determine seed quality generates a large amount of information, making it almost impossible for humans to perform a quick and effective quality control analysis. Therefore, the objective of this study was to evaluate the differences in the physiological quality of soybean seeds in different cultivars using machine learning techniques to rank the lots based on their quality. Three cultivars were used, and the analysis was germination, accelerated aging, tetrazolium treatment, seedling emergence, and 1000 seed weight from 65 lots were measured. The lots were evaluated in two phases, one immediately after harvest and the other after six months of storage. Random forest, multi-layer perceptron, J48, and classification via regression classifiers were used, aided by the feature resampler technique. Random forest and

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来源期刊

Engenharia Agricola AGRICULTURAL ENGINEERING-

CiteScore

1.90

自引率

20.00%

发文量

审稿时长

4-8 weeks

期刊介绍： A revista Engenharia Agrícola existe desde 1972 como o principal veículo editorial de caráter técnico-científico da SBEA - Associação Brasileira de Engenharia Agrícola. Publicar artigos científicos, artigos técnicos e revisões bibliográficas inéditos, fomentando a divulgação do conhecimento prático e científico na área de Engenharia Agrícola.