2021 Fiscal Year Final Research Report

Development of non-destructive measuring device of potassium concentration for nephritic patient to eat fresh vegetable with confidence

Research Project

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Project/Area Number	19K06312
Research Category	Grant-in-Aid for Scientific Research (C)
Allocation Type	Multi-year Fund
Section	一般
Review Section	Basic Section 41040:Agricultural environmental engineering and agricultural information engineering-related
Research Institution	Niigata University
Principal Investigator	Nakano Kazuhiro 新潟大学, 自然科学系, フェロー (70188994)
Co-Investigator(Kenkyū-buntansha)	大橋慎太郎新潟大学, 自然科学系, 准教授 (70452076) 滝沢憲一新潟経営大学, 観光経営学部, 准教授 (60730132) 窪田陽介福島大学, 食農学類, 准教授 (40535267)
Project Period (FY)	2019-04-01 – 2022-03-31
Keywords	慢性腎臓病 / カリウム含有量 / 野菜サラダ / 非破壊測定 / 可視・近赤外分光法 / ハイパースペクトル画像
Outline of Final Research Achievements	Potassium is a crucial indicator for patients with chronic kidney disease (CKD) to pay attention in daily intake. In this study, the Visible/near-infrared) spectroscopy and Hyperspectral imagfng (HSI) technology to develop non-destructive measurement systems for high accuracy detection and prediction of potassium concentration in fresh lettuce. As the results, exceUent prediction of green leaves was obtained by interactance measurement with R2=O.93, while the transmission spectra of petioles provided optimal prediction with R2=O.92. The feasibility of Vis/NIR spectroscopy combined with the nonlinear RBF neural network showed two single-variety leaves were measured by green leaves and petioles. Fresh lettuce samples showed R2 of 0.86 and 0.88 for green leaves and petioles, respectively. The distribution map of potassium concentration by using hyperspectral imaging in fresh lettuce was successfully produced through the difference of colors.
Free Research Field	農業システム工学
Academic Significance and Societal Importance of the Research Achievements	新しい国民病とも言われている腎臓病の患者は，カリウム濃度の高い生野菜の摂取を制限されている。本研究では特に野菜サラダとして喫食したい代表的野菜であるレタスについて，まずカリウム濃度分布の非破壊測定技術の開発について検討した。その結果，リーレタスの葉身と葉柄など部位別にカリウム濃度は大きく異なり，それらを迅速・非破壊・高精度に測定できる手法が開発された。さらに，ハイパースペクトル画像とＡＩの応用により，レタス内カリウム濃度分布の測定と表示が可能となった。