Visible-near infrared spectral analysis for identification of physiological and genetic features in rice
デジタルデータあり（科学技術振興機構）
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J-STAGE
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- 資料種別
- 記事
- 著者・編者
- Hinako TakehisaIchiro NagaokaAkifumi IkehataYutaka Sato
- タイトル（掲載誌）
- Breeding science
- 巻号年月日等（掲載誌）
- 75(5):2025.12
- 掲載巻
- 75
- 掲載号
- 5
- 掲載ページ
- 349-357
- 掲載年月日（W3CDTF）
- 2025-12
- ISSN（掲載誌）
- 1344-7610
- ISSN-L（掲載誌）
- 1344-7610
- 出版事項（掲載誌）
- Kyoto : Japanese Society of Breeding
- 出版地（国名コード）
- JP
- 本文の言語コード
- eng
- NDLC
- 対象利用者
- 一般
- 所蔵機関
- 国立国会図書館
- 請求記号
- Z54-J372
- 連携機関・データベース
- 国立国会図書館 : 国立国会図書館雑誌記事索引
- 書誌ID（NDLBibID）
- 034474466
- 整理区分コード
- 632
- 要約等
- <p>Visible-near infrared hyperspectral analysis is widely used for plant characterization and evaluation of agricultural products and food quality. On the other hand, it has remained un-certain whether this technique has a sufficient potential for evaluation of biological complexity during the growth of crop plants. In the present study, using a spectrometer and hyperspectral camera placed in a laboratory environment, we carried out continuous hyperspectral profiling of leaves derived from four rice cultivars grown under two field conditions. Combined analysis with transcriptome data revealed that the hyperspectral profile had potential to predict the degree of expression of developmentally regulated genes. In addition, principal component analysis of hyperspectral imaging data made it possible to detect growth-stage dependent dynamics and to distinguish differences between subspecies as well as field conditions by selecting an adequate pretreatment method. Furthermore, we obtained hyperspectral data for brown rice grains of recombinant inbred lines derived from a cultivar with high temperature tolerance during the ripening stage and with a good grain appearance. We then performed quantitative trait locus analysis using the extracted principal component scores and trait values related to grain appearance to explore the possibility of using spectral analysis for genetic studies.</p>
- DOI
- 10.1270/jsbbs.25018
- オンライン閲覧公開範囲
- インターネット公開
- 連携機関・データベース
- 科学技術振興機構 : J-STAGE
- 要約等
- <p>Visible-near infrared hyperspectral analysis is widely used for plant characterization and evaluation of agricultural products and food quality. On the other hand, it has remained un-certain whether this technique has a sufficient potential for evaluation of biological complexity during the growth of crop plants. In the present study, using a spectrometer and hyperspectral camera placed in a laboratory environment, we carried out continuous hyperspectral profiling of leaves derived from four rice cultivars grown under two field conditions. Combined analysis with transcriptome data revealed that the hyperspectral profile had potential to predict the degree of expression of developmentally regulated genes. In addition, principal component analysis of hyperspectral imaging data made it possible to detect growth-stage dependent dynamics and to distinguish differences between subspecies as well as field conditions by selecting an adequate pretreatment method. Furthermore, we obtained hyperspectral data for brown rice grains of recombinant inbred lines derived from a cultivar with high temperature tolerance during the ripening stage and with a good grain appearance. We then performed quantitative trait locus analysis using the extracted principal component scores and trait values related to grain appearance to explore the possibility of using spectral analysis for genetic studies.</p>
- DOI
- 10.1270/jsbbs.25018
- 関連情報（URI）
- 参照
- Deciphering and Prediction of Transcriptome Dynamics under Fluctuating Field ConditionsRiceXPro Version 3.0: expanding the informatics resource for rice transcriptomeHigh-throughput phenotyping using digital and hyperspectral imaging-derived biomarkers for genotypic nitrogen responseTranscriptome and hyperspectral profiling allows assessment of phosphorus nutrient status in rice under field conditionsDynamics and genetic regulation of leaf nutrient concentration in barley based on hyperspectral imaging and machine learningRapid and Nondestructive Evaluation of Wheat Chlorophyll under Drought Stress Using Hyperspectral ImagingApplications of hyperspectral imaging in plant phenotypingR/qtl: QTL mapping in experimental crossesHyperspectral image analysis techniques for the detection and classification of the early onset of plant disease and stressHyperspectral Monitoring of Powdery Mildew Disease Severity in Wheat Based on Machine LearningVis/NIR hyperspectral imaging distinguishes sub-population, production environment, and physicochemical grain properties in riceInflorescence Meristem Identity in Rice Is Specified by Overlapping Functions of Three <i>AP1</i>/<i>FUL</i>-Like MADS Box Genes and <i>PAP2</i>, a <i>SEPALLATA</i> MADS Box GeneCoexpression Network Analysis of Macronutrient Deficiency Response Genes in RiceHyperspectral and genome-wide association analyses of leaf phosphorus status in local Thai indica riceGenetic studies for breeding of rice cultivars with superior grain appearance and lodging resistance from the rice cultivar ‘Emi-no-kizuna’Using VIS-NIR hyperspectral imaging and deep learning for non-destructive high-throughput quantification and visualization of nutrients in wheat grainsGenetic dissection of grain elements predicted by hyperspectral imaging associated with yield-related traits in a wild barley NAM populationEvaluation of Soybean Wildfire Prediction via Hyperspectral ImagingHyperspectral imaging for quantifying Magnaporthe oryzae sporulation on rice genotypesHyperspectral imaging-based classification of rice leaf blast severity over multiple growth stagesA natural variant of NAL1, selected in high-yield rice breeding programs, pleiotropically increases photosynthesis rateLack of Cytosolic Glutamine Synthetase1;2 Activity Reduces Nitrogen-Dependent Biosynthesis of Cytokinin Required for Axillary Bud Outgrowth in Rice SeedlingsIdentification of plant leaf phosphorus content at different growth stages based on hyperspectral reflectanceThe Development of Hyperspectral Distribution Maps to Predict the Content and Distribution of Nitrogen and Water in Wheat (Triticum aestivum)Field transcriptome revealed critical developmental and physiological transitions involved in the expression of growth potential in japonicariceThe interaction between nitrogen availability and auxin, cytokinin, and strigolactone in the control of shoot branching in rice (Oryza sativa L.)Maize Global Transcriptomics Reveals Pervasive Leaf Diurnal Rhythms but Rhythms in Developing Ears Are Largely Limited to the Core OscillatorEctopic Expression of KNOTTED1-Like Homeobox Protein Induces Expression of Cytokinin Biosynthesis Genes in RiceCytokinin Oxidase Regulates Rice Grain ProductionTranscriptome monitoring visualizes growth stage‐dependent nutrient status dynamics in rice under field conditionsHigh Throughput In vivo Analysis of Plant Leaf Chemical Properties Using Hyperspectral ImagingQuantitative trait loci analysis of grain appearance in Oryza sativa L. 'Emi-no-kizuna'
- 連携機関・データベース
- 国立情報学研究所 : CiNii Research
- 提供元機関・データベース
- Japan Link Center雑誌記事索引データベースCrossref
- 書誌ID（NDLBibID）
- 034474466