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Indian Journal of Agricultural Research

Application of a Visible/Near-infrared Spectrometer in Identifying Flower and Non-flower Buds on ‘Fuji’ Apple Trees

DOI: 10.18805/IJARe.A-655    | Article Id: A-655 | Page : 214-219
Citation :- Application of a Visible/Near-infrared Spectrometer in Identifying Flower and Non-flower Buds on ‘Fuji’ Apple Trees.Indian Journal of Agricultural Research.2022.(56): 214-219
Alisher Botirov, Songhao An, Osamu Arakawa, Shuhuai Zhang oarakawa@hirosaki-u.ac.jp
Address : Faculty of Agriculture and Life Science, Hirosaki University, Hirosaki, Aomori 036-8560, Japan.
Submitted Date : 18-05-2021
Accepted Date : 4-09-2021
First Online:

Abstract

Background: Forecasting bud physiologic conditions can help ‘Fuji’ apple farmers manage their orchards more efficiently. Being able to determine the nature of a bud before bud burst is one such forecast that could be of use to these ‘Fuji’ growers. The aim of this research project was to determine if a device, a visible/near-infrared spectrometer, could be employed to determine whether a bud is a flower or non-flower bud without destroying the bud. 
Methods: Experiments were conducted on buds taken from a ‘Fuji’ apple tree, beginning on January 29 through to March 31, 2021, three days before bud burst. The data from the visible/near-infrared spectrometer clarified whether a bud was a flower or a non-flower bud. The Spectro data Classification Learner App proved to be an accurate classification method to analyze flower and non-flower bud Spectro data.
Result: Three days before bud burst, the chlorophyll content levels of the non-flower buds were markedly higher (P≤0.05) than those of the flower bud, which explains why the visible border of the near-infrared spectrometer might have been changed by the chlorophyll content of buds. The visible and near-infrared bands of the buds showed that the Spectro data of the non-flower buds were higher than those of the flower buds when measurements were made three days before bud burst. Three days before bud burst Cubic KNN of KNN classifier analyzed flower and non-flower buds smoothly. Spectro data were labeled as accuracy 75.9%, sensitivity 86% and specificity 67%. The results that were obtained suggest that farmers could use a visible/near-infrared spectrometer to identify flower and non-flower buds in their orchards, without damaging the buds, three days before bud burst.

Keywords

Bud burst Chlorophyll content Classifier learner app Non-destructive method

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