Nutritional diagnosis and yield estimation of apple trees using hyperspectral imaging
| Project/Area Number |
16K07968
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Agricultural environmental engineering/Agricultural information engineering
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| Research Institution | Hirosaki University |
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Principal Investigator |
YE Xujun 弘前大学, 農学生命科学部, 准教授 (10708168)
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| Co-Investigator(Kenkyū-buntansha) |
張 樹槐 弘前大学, 農学生命科学部, 教授 (90261429)
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| Research Collaborator |
ABE Shiori
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| Project Period (FY) |
2016-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥4,940,000 (Direct Cost: ¥3,800,000、Indirect Cost: ¥1,140,000)
Fiscal Year 2018: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2017: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2016: ¥2,600,000 (Direct Cost: ¥2,000,000、Indirect Cost: ¥600,000)
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| Keywords | ハイパースペクトルイメージング / リンゴ / 画像処理 / 栄養診断 / 収量推定・予測 / ハイパースペクトル画像計測 / 栄養評価 / 非破壊計測 / 可視化 / 果実判別 / 栄誉診断 |
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| Outline of Final Research Achievements |
This research placed emphasis on the development of evaluation methods and visualization techniques for the nutritional status of apple trees. Hyperspectral imagery was obtained and chemical analysis was performed to quantify the nitrogen and chlorophyll contents in apple leaves. Multiple linear regression (MLR) models for estimating the nitrogen and chlorophyll contents based on the reflectance spectrum of a few selected key wavelengths were established. Nitrogen distribution maps at both leaf and canopy levels were generated. Moreover, this research also verified the applicability of a newly developed smartphone-based rice scan device (Maxell Co., Ltd.) to the evaluation of nutritional status in apple leaves. An original leaf color index (LCI) based on RGB parameters obtained by the device, and an inexpensive and easy-to-use leaf color chart (LCC) were developed. These new approaches and tools may be potentially applied to precision nutrient management in apple orchard.
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| Academic Significance and Societal Importance of the Research Achievements |
ハイパースペクトル画像計測によるリンゴ樹体生育状況取得、様々なケモメトリックス解析とモデリング手法および画像処理も統合した技術開発である点に学術的意義がある。また、果樹園の精密管理の実現に資する栄養診断と収量予測技術の利活用により、樹体毎のニーズに応じた施肥作業による環境負荷の低減、樹体の生産持続性の向上および管理作業の省力化が図れる点で社会的意義が高い。
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Report
(4 results)
Research Products
(10 results)
