Alan Fernando Coelho Garcia, Ricardo Antonio Ayub, José Carlos Ferreira Da Rocha, Hugo Valadares Siqueira, Sergio Luiz Stevan
{"title":"Phenological Stages Analysis in Grapevines Using an Electronic Nose","authors":"Alan Fernando Coelho Garcia, Ricardo Antonio Ayub, José Carlos Ferreira Da Rocha, Hugo Valadares Siqueira, Sergio Luiz Stevan","doi":"10.1007/s40003-024-00730-w","DOIUrl":null,"url":null,"abstract":"<div><p>The vineyards present different phenological phases that comprise dormancy, bud break, and flowering buds going through different stages of development, such as inflorescence formation, flowering, fruit set, growth and fruit maturation. To control the quantity and quality of production, thinning is used in table grapes. The technique reduces berry number to improve fruit growth, but it is costly and in some cases impractical in the entire extension of an orchard. The right moment for execution and the intensity are complex issues that involve specific knowledge about the conditions of the vineyard. Therefore, phenological information that can help planning and decision-making about thinning is relevant and can improve the cost-effectiveness of the technique in viticulture. An electronic nose system was developed to collect and analyze compound volatile variations during the growing season, more specifically during the period of bud growth and ripening in three grape cultivars (BRS Vitória, Niagara Rosada, Bordô). The data were collected from October 2021 to February 2022. The research hypothesis is that the electronic nose can identify the general stage of plant development. To verify the hypothesis, a classification analysis was performed for each cultivar. The result showed that all models presented balanced accuracy above 85% for the cultivar BRS Vitória, above 92% for Niagara, and above 93% for Bordô, with better performance for models based on <i>K-nearest neighbors </i> (KNN), and <i>random forest</i>, than those based on <i>extreme learning machine</i> and <i>support vector machine</i>. In the total of 24 models, 9 for BRS Vitória, 9 for Niagara, and 11 for Bordô did not obtain error given the metrics used. It was observed that the normalization of the database is not necessary to improve the accuracy rates obtained, which obtained total rates using the KNN classifier. Regarding the research hypothesis, it is considered that the electronic nose is capable of distinguishing between the different stages proposed for each analyzed cultivar and between them. The results of this work indicate a potential use of the electronic nose to aid decision-making in vineyard activities.</p></div>","PeriodicalId":7553,"journal":{"name":"Agricultural Research","volume":"13 4","pages":"636 - 653"},"PeriodicalIF":1.4000,"publicationDate":"2024-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Agricultural Research","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s40003-024-00730-w","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AGRONOMY","Score":null,"Total":0}
引用次数: 0
Abstract
The vineyards present different phenological phases that comprise dormancy, bud break, and flowering buds going through different stages of development, such as inflorescence formation, flowering, fruit set, growth and fruit maturation. To control the quantity and quality of production, thinning is used in table grapes. The technique reduces berry number to improve fruit growth, but it is costly and in some cases impractical in the entire extension of an orchard. The right moment for execution and the intensity are complex issues that involve specific knowledge about the conditions of the vineyard. Therefore, phenological information that can help planning and decision-making about thinning is relevant and can improve the cost-effectiveness of the technique in viticulture. An electronic nose system was developed to collect and analyze compound volatile variations during the growing season, more specifically during the period of bud growth and ripening in three grape cultivars (BRS Vitória, Niagara Rosada, Bordô). The data were collected from October 2021 to February 2022. The research hypothesis is that the electronic nose can identify the general stage of plant development. To verify the hypothesis, a classification analysis was performed for each cultivar. The result showed that all models presented balanced accuracy above 85% for the cultivar BRS Vitória, above 92% for Niagara, and above 93% for Bordô, with better performance for models based on K-nearest neighbors (KNN), and random forest, than those based on extreme learning machine and support vector machine. In the total of 24 models, 9 for BRS Vitória, 9 for Niagara, and 11 for Bordô did not obtain error given the metrics used. It was observed that the normalization of the database is not necessary to improve the accuracy rates obtained, which obtained total rates using the KNN classifier. Regarding the research hypothesis, it is considered that the electronic nose is capable of distinguishing between the different stages proposed for each analyzed cultivar and between them. The results of this work indicate a potential use of the electronic nose to aid decision-making in vineyard activities.
期刊介绍:
The main objective of this initiative is to promote agricultural research and development. The journal will publish high quality original research papers and critical reviews on emerging fields and concepts for providing future directions. The publications will include both applied and basic research covering the following disciplines of agricultural sciences: Genetic resources, genetics and breeding, biotechnology, physiology, biochemistry, management of biotic and abiotic stresses, and nutrition of field crops, horticultural crops, livestock and fishes; agricultural meteorology, environmental sciences, forestry and agro forestry, agronomy, soils and soil management, microbiology, water management, agricultural engineering and technology, agricultural policy, agricultural economics, food nutrition, agricultural statistics, and extension research; impact of climate change and the emerging technologies on agriculture, and the role of agricultural research and innovation for development.