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Affiliation |
Faculty of Agriculture Department of Agricultural and Environmental Sciences |
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Assistant Professor |
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External Link |
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KIRIMURA Masaaki
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Degree 【 display / non-display 】
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博士(農学) ( 2006.3 鹿児島大学 )
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修士(農学) ( 2003.3 宮崎大学 )
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学士(農学) ( 2001.3 宮崎大学 )
Research Areas 【 display / non-display 】
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Environmental Science/Agriculture Science / Agricultural environmental engineering and agricultural information engineering
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Environmental Science/Agriculture Science / Horticultural science
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Life Science / Plant nutrition and soil science
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Environmental Science/Agriculture Science / Environmental agriculture
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Environmental Science/Agriculture Science / Landscape science
Papers 【 display / non-display 】
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Zushi K., Yamamoto M., Matsuura M., Tsutsuki K., Yonehana A., Imamura R., Takahashi H., Kirimura M.
Journal of the Science of Food and Agriculture 105 ( 2 ) 1159 - 1169 2024
Publishing type：Research paper (scientific journal) Publisher：Journal of the Science of Food and Agriculture
BACKGROUND: Strawberry is a rich source of antioxidants, including ascorbic acid (ASA) and polyphenols, which have numerous health benefits. Antioxidant content and activity are often determined manually using laboratory equipment, which is destructive and time-consuming. This study constructs a prediction model for antioxidant compounds utilizing machine learning (ML) and multiple linear regression based on environmental, plant growth and agronomic fruit quality-related parameters as well as antioxidant levels. These were studied in three farms at two-week intervals during two years of cultivation. RESULTS: During the ML model screening, artificial neural network (ANN)-boosted models displayed a moderate coefficient of determination (R2) at 0.68–0.78 and relative root mean square error (RRMSE) at 3.8–4.8% in polyphenols and total ASA levels, as well as a high R2 of 0.96 and low RRMSE at <3.0% in antioxidant activity. Additionally, we developed variable selection models regarding the antioxidant activity, and variables two and five (environmental parameters and leaf length, respectively) with high accuracy were selected. The linear regression analysis between the actual and predicted data of antioxidants in the ANN-boosted models revealed high fitness with all parameters in almost all training, validation and test sets. Furthermore, environmental parameters are essential in developing such reliable models. CONCLUSION: We conclude that ANN-boosted, stepwise and double-Lasso regression models can predict antioxidant compounds with enhanced accuracy, and the relevant parameters can be easily acquired on-site without the need for any specific equipment. © 2024 Society of Chemical Industry.
DOI： 10.1002/jsfa.13906
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Prediction of PPFD (photosynthetic photon flux density) under transparent CPV modules Reviewed
Toyoda T., Yajima D., Kirimura M., Araki K., Ota Y., Nagaoka A., Nishioka K.
AIP Conference Proceedings 2841 ( 1 ) 2023.9
Publishing type：Research paper (scientific journal) Publisher：AIP Conference Proceedings
Recently, the agro-photovoltaic (agri-photovoltaic) system is expected to penetrate the market due to its advantages in some crops and significant potential installation areas. In principle, the agro-photovoltaic system shares solar energy with PV and agriculture, and its appropriate and controlled distribution is the key for the economy. Accurate and reproducible optimization design is essential. Any PV modules can be used for the agro-photovoltaic system. The best may be the transparent CPV that uses direct sunlight to concentrate onto solar cells and diffused sunlight to illuminate the farming light through a transparent backplane. The diffused sunlight for typical CPV modules is not used for electricity generation, and the transparent CPV is utilized as the secondary light source to crops. The diffused sunlight does not create shadow and improves the inhomogeneity of PPFD (Photosynthetic Photon Flux Density) from the stripe of shadows by PV modules, thus improving the yield. This paper predicts PPFD by the transparent CPV modules and the effectiveness of its use for the agro-photovoltaic system.
DOI： 10.1063/5.0146145
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Yajima, Daisuke Toyoda, Teruya Kirimura, Masaaki Araki, Kenji Ota, Yasuyuki Nishioka, Kensuke
Energies 16 ( 7 ) 3261 - 3261 2023.4
Language：Japanese Publishing type：Research paper (scientific journal) Publisher：Energies
Climate change and increasing food demand are global issues that require immediate attention. The agrivoltaic system, which involves installing solar panels above farmland, can simultaneously solve climate and food issues. However, current systems tend to reduce agricultural production and delay the harvest period due to shading by the solar panels. A delayed harvest period impacts the income of farmers who wish to sell produce at specific times. Incorporating a model that calculates the amount of electricity generated by solar irradiation, this study establishes a model to estimate the correct start date of cultivation for solar panel covered crops to ensure the correct harvest date and determines the expected income of farmers by calculating agricultural production and power generation. Using taro cultivation in Miyazaki Prefecture as a case study, the model estimated that the start date of cultivation should be brought forward by 23 days to ensure the ideal harvest period and agricultural production. This would prevent an opportunity loss of USD 16,000 per year for a farm area of 10,000 m2. Furthermore, an additional income of USD 142,000 per year can be expected by adjusting shading rates for the cultivation and non-cultivation periods.
DOI： 10.3390/en16073261
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Yajima D., Toyoda T., Kirimura M., Araki K., Ota Y., Nishioka K.
Cleaner Engineering and Technology 12 100594 - 100594 2023.2
Language：Japanese Publishing type：Research paper (scientific journal) Publisher：Cleaner Engineering and Technology
Climate change and increasing food production due to population growth are global challenges that need immediate attention. The introduction of renewable energy to mitigate climate change and the requirement of adequate land to increase food production are generally mutually exclusive. However, an agrivoltaic system generates renewable electricity and produces agricultural products from a common piece of land, thus increasing the land productivity. In addition, this system contributes to local production, thus reducing the CO2 emissions from logistics. Photovoltaic arrays in previous studies were designed by calculating the irradiance in W/m2, even in recent studies. A careful design of the farmland's illumination must be developed for effective agriculture. The simulations must be scaled based on photosynthetic photon flux density rather than irradiance commonly applied in photovoltaic technology simulations. This study focused on the photosynthetic photon flux density and employed an all-climate solar spectrum model to calculate the photosynthetic photon flux density accurately on farmland partially shaded by solar panels and supporting tubes. This study described an algorithm for estimating the photosynthetic photon flux density values under solar panels. The calculated data were validated using the photosynthetic photon flux density sensors. To calculate the photosynthetic photon flux density under the solar panels, it is essential to weigh the direct and diffused components shaded by the solar panels separately because they have different spectrums. A method to quantify the shading was explored here by solar panels and their supporting tubes for the direct and diffused component as the sun moves. The calculation formula was established by defining the sun's moves and the positions of solar panels and their supporting tubes in terms of elevation and azimuth angles from the observation point. It was found that the waveform based on the calculation formula for the photosynthetic photon flux density under the solar panels reproduced the same tendency as the measured photosynthetic photon flux density. To evaluate this trend numerically, the measured and calculated photosynthetic photon flux densities were compared using the standard residuals. Generally, the similarity of the two values is confirmed by a standard residual value between −3 and 3. The result of this study showed that the standard residual values were negative in more frequencies except for the zero photosynthetic photon flux density at night. This indicates that the calculated photosynthetic photon flux density tends to be higher than the measured photosynthetic photon flux density. The peak frequency of the standard residuals was between −6 and −3. This difference probably occurred because the established calculation formula targets the shading provided by the solar panels and supporting tubes but does not cover the shading provided by the other system structures. The calculation formula enables farmers to evaluate the economic efficiency of the system before introducing it using measured solar irradiation data at the target farmlands by introducing published neighborhood solar irradiation data and considering, in advance, measures to avoid the effects of shading on agricultural production. The next study will be to improve the accuracy of the calculation formula by increasing the number of days and develop a method that leads to the best practices of agricultural production and solar power generation by introducing the system.
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Tissue-dependent seasonal variation and predictive models of strawberry firmness Reviewed
Zushi, K., Yamamoto, M., Matsuura, M., Tsutsuki, K., Yonehana, A., Imamura, R., Takahashi, H., Kirimura, M.
Scientia Horticulturae 307 111535 - 111535 2023.1
Authorship：Last author Language：Japanese Publishing type：Research paper (scientific journal) Publisher：Scientia Horticulturae
Firmness is an important quality factor in strawberries. We investigated the tissue-dependent seasonal variation in strawberry firmness in epidermis, cortex, and pith tissues, and also developed statistical predictive models for the seasonal changes in firmness using environmental conditions and fruit properties. The experiment was conducted at three locations (sites A, B, and C) and in different harvesting seasons from winter (December) to spring (May) during 2 years. The fruit properties, including the total soluble solids (TSS), acidity, and fruit surface color decreased toward the end of the season (from winter to spring), with fruit harvested in April and May having the lowest values at all research sites. Similarly, the epidermis firmness decreased 0.73-fold toward the end of the season at all the research sites. The cortex firmness of site A showed a marked decrease of 0.64-fold toward the end of the season, but that of sites B and C remained at constant levels. The pith firmness tended to be higher for fruit harvested in December than in other months. We tested the training dataset using the stepwise multiple linear regression analysis to construct the statistical predictive models of firmness. The goodness-of-fit of the firmness predictive models, shown by the adjusted square correlation coefficient, was 0.47–0.54 in the model using the input data for daily mean environmental conditions several days before harvest as well as fruit properties, including fruit weight, color, and TSS. Additionally, in the regression analysis between predicted and actual values, the predictive models demonstrated accurate high performance with a low predictive error (0.06 as relative root mean square error). Thus, we concluded that strawberry firmness shows seasonal variation within the epidermis and pith tissues, and that their predictive models were of adequate accuracy and usefulness without the need for time-consuming, costly measurement equipment.
Books 【 display / non-display 】
MISC 【 display / non-display 】
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Control of Nutrient Solutions in Hydroponics for Plant Factory Invited
Masaaki Kirimura
Science and Industry 84 ( 3 ) 103 - 112 2010.3
Language：Japanese Publishing type：Article, review, commentary, editorial, etc. (scientific journal)
Presentations 【 display / non-display 】
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ズッキーニの着果率改善に向けた花粉稔性に関する研究
大西冬花，沖野圭志朗，霧村雅昭
一般社団法人高等教育コンソーシアム宮崎令和5年度公募型卒業研究テーマ成果発表会 2024.2.27
Event date： 2024.2.27
Language：Japanese Presentation type：Poster presentation
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イチゴの健全苗育成および養液栽培のための閉鎖型･養液栽培システムの検討－多芽体培養した個体の順化条件の検討－
加藤彰太，野﨑克弘，黒木尚，沖野圭志朗，霧村雅昭
一般社団法人高等教育コンソーシアム宮崎令和5年度公募型卒業研究テーマ成果発表会 2024.2.27
Event date： 2024.2.27
Language：Japanese Presentation type：Poster presentation
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イチゴ栽培に適した無機固形培地の検討
堀井彩香，野﨑克弘，黒木尚，沖野圭志朗，霧村雅昭
一般社団法人高等教育コンソーシアム宮崎令和5年度公募型卒業研究テーマ成果発表会 2024.2.27
Event date： 2024.2.27
Language：Japanese Presentation type：Poster presentation
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電熱ヒーターを用いた株元加温によるナスの促成栽培における経済性の評価
前田教行，鳥原亮，中谷勝彦，斉藤孝博，渡邊尚哉，霧村雅昭
日本農業気象学会九州支部2023年大会 2023.12.8
Event date： 2023.12.7 - 2023.12.8
Language：Japanese Presentation type：Oral presentation (general)
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LED植物工場におけるワサビ栽培の最適条件の検討 －品種と明期の違いが生育に及ぼす影響－
秋吉慧悟，並木郁斗，北村浩康，霧村雅昭
日本生物環境工学会2023年豊橋大会 2023.9.13
Event date： 2023.9.12 - 2023.9.15
Language：Japanese Presentation type：Poster presentation
Awards 【 display / non-display 】
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日本生物環境工学会論文賞
2024.9 日本生物環境工学会 Correlation network analysis visually identifies interactions of antioxidant compounds with plant growth, leaf photosynthetic performance, and agronomic quality in strawberry.
Kazufumi ZUSHI, Kan TSUTSUKI, Hiromi TAKAHASHI, Masaaki KIRIMURA
Award type：Award from Japanese society, conference, symposium, etc.
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学術研究者支援奨励賞
2024.8 株式会社九電工 バイオマス発電の燃料に適したソルガムの地域性を考慮した品種選抜
霧村雅昭
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令和5年度公募型卒業研究テーマ成果発表会ベストポスター賞
2024.4 一般社団法人高等教育コンソーシアム宮崎 ズッキーニの着果率改善に向けた花粉稔性に関する研究
大西冬花，沖野圭志朗，霧村雅昭
Award type：Award from Japanese society, conference, symposium, etc.
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ベストポスター賞
2022.12 日本生物環境工学会九州支部2022年熊本大会 LED植物工場産レタスの品種と包装，貯蔵温度の違いが品質に及ぼす影響
柳沢美遥，永田奏絵，迫 里沙，圖師一文，霧村雅昭
Award type：Award from Japanese society, conference, symposium, etc.
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ベストポスター賞
2022.12 日本生物環境工学会九州支部2022年熊本大会 ウスベニアオイとゼニアオイの栽培に適した光条件の検討
永田奏絵，柳沢美遥，迫 里沙，霧村雅昭
Award type：Award from Japanese society, conference, symposium, etc.
Grant-in-Aid for Scientific Research 【 display / non-display 】
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栽培履歴が野菜貯蔵中の機能性成分含量に及ぼす影響と変動予測モデルの構築
Grant number：21H02319 2021.04 - 2025.03
独立行政法人日本学術振興会 科学研究費補助金 基盤研究(B)
圖師 一文、
Authorship：Coinvestigator(s)
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営農型太陽光発電のシステムおよび作型の最適化アルゴリズムの構築
Grant number：19K06338 2019.04 - 2023.03
科学研究費補助金 基盤研究(C)
Authorship：Principal investigator
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有機物由来培養液を用いた養液栽培の実用化に関する研究
Grant number：26740051 2014.04 - 2018.03
科学研究費補助金 若手研究(B)
Authorship：Principal investigator
本研究では今後需要の拡大が見込まれる一方，栽培方法が確立されていない有機物由来液肥を用いた養液栽培について行う．特に，培養液の成分組成の調整方法やpH 管理方法など，培養液管理に関する基本的な問題を解決することで，未利用資源を有効活用した持続可能な養液栽培の実用化に取り組む．また，天然鉱物由来肥料は採取時に環境負荷が伴うため，本研究では用いない．
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メタン発酵消化液の有効利用による資源循環型農業および水浄化システムの構築
Grant number：16380223 2004.04 - 2008.03
科学研究費補助金 基盤研究(B)
Authorship：Coinvestigator(s)
バイオガスプラントから発生する消化液の用途は様々であるが，主として1）転作水田の有効利用2)畑地用飼料生産への利用，3）放牧草地への利用, 4）野菜，果樹，園芸への利用が考えられる．これらの農産物生産へ有効利用するためには，消化液を液肥として直接利用するだけではなく，作物に応じた養分調節，固形化，肥効調節等を通じて，消化液利用が汎用的かつ簡便で，環境問題（硝酸による地下水汚染，亜酸化窒素およびメタン等の環境に対する有害ガス）が解決可能な消化液の形態の開発と消化液浄化システムの開発が必要である．本研究では，特に水田で栽培する飼料作物および、ブルーベリー栽培システムに対して，消化液の施用方法（適量，施用時期，施用形態）を求めるとともに，環境への影響把握（地下水の硝酸汚染、亜酸化窒素ガスの発生量）および窒素，リン循環の視点から，各システムにおける環境保全・資源循環機能を明らかにする．
Available Technology 【 display / non-display 】
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植物工場・養液栽培に適した栽培管理技術に関する研究
農地での食料とエネルギーの生産を両立するハイブリッド農業に関する研究
農林畜産廃棄物利用による資源循環型農業システムの構築Home Page： 施設園芸学研究室
Related fields where technical consultation is available：LEDの植物栽培への利用、植物工場の生産性の向上、営農型太陽光発電に適した作物の検討、新しい作型の検討、未利用資源の液肥利用、汚水の浄化
Message：栽培環境の計測と制御、生育調査、データ解析により野菜の生育改善や未利用資源の有効活用に関する研究に取り組むことができます。