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| 008 | 230419s2023 si | o |||| 0|eng d | ||
| 020 | _a9789811974984 | ||
| 024 | 7 |
_a10.1007/978-981-19-7498-4 _2doi |
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_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC |
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| 050 | 4 |
_aSB123 _b2023 EB |
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_aTranslating Physiological Tools to Augment Crop Breeding _cedited by Mamrutha Harohalli Masthigowda, Krishnappa Gopalareddy, Rinki Khobra, Gyanendra Singh, Gyanendra Pratap Singh |
| 250 | _a1st ed. 2023. | ||
| 264 | 1 |
_aSingapore _bSpringer Nature Singapore _c2023 |
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| 300 | _a1 recurso en línea | ||
| 336 |
_atexto _btxt _2rdacontent |
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| 337 |
_aelectrónico _bc _2rdamedia |
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| 338 |
_arecurso electrónico _bcr _2rdacarrier |
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| 505 | 0 | _a1. Importance of integrating physiological breeding to augment crop breeding -- 2. Stacking of complex traits through physiological pre breeding -- 3. Strategies to develop heat and drought tolerant wheat varieties following physiological breeding -- 4. Developing crop varieties by physiological breeding for improving plant nutrition -- 5. Role of Transpiration in Regulating Leaf Temperature and its Application in Physiological Breeding -- 6. Photosynthesis as a trait for improving yield potential in crops -- 7. Cuticular waxes and its application in crop improvement -- 8. Radiation use efficiency (RUE)-target for improving yield potential: Current status and future prospect -- 9. Application of Stable Isotopes in Crop Improvement -- 10. Root phenotyping for improved resource use efficiency in crops -- 11. Root system architecture and phenotyping for improved resource use efficiency in crops -- 12. Harnessing Root associated traits and Rhizosphere efficiency for Crop improvement -- 13. High throughput phenomics of crops for water and nitrogen stress -- 14. Metabolomics as a selection tool for abiotic stress tolerance in crops -- 15. Remote Sensing Algorithms and their Applications in Plant Phenotyping -- 16. Endophyte mediated crop improvement: Manipulation of abiotic stress‐specific traits -- 17. Impact of high temperature stress on selected food grain crops -- 18. Morpho-physiological basis of finger millet to withstand climatic extremes: A special reference to drought -- 19. Comprehending the physiological efficiency of millets under abiotic stress -- 20. Role of Next-generation sequencing in trait identification, genetic mapping, and crop improvement -- 21. Application of Artificial Intelligence and Machine Learning in Agriculture. | |
| 520 | _aThis book covers different physiological processes, tools, and their application in crop breeding. Each chapter emphasizes on a specific trait/physiological process and its importance in crop, their phenotyping information and how best it can be employed for crop improvement by projecting on success stories in different crops. It covers wide range of physiological topics including advances in field phenotyping, role of endophytic fungi, metabolomics, application of stable isotopes, high throughput phenomics, transpiration efficiency, root phenotyping and root exudates for improved resource use efficiency, cuticular wax and its application, advances in photosynthetic studies, leaf spectral reflectance and physiological breeding in hardy crops like millets. This book also covers the futuristic research areas like artificial intelligence and machine learning. This contributed volume compiles all application parts of physiological tools along with their advanced research in these areas, which is very much need of the hour for both academics and researchers for ready reference. This book will be of interest to teachers, researchers, climate change scientists, capacity builders, and policy makers. Also, the book serves as additional reading material for undergraduate and graduate students of agriculture, physiology, botany, ecology, and environmental sciences. National and international agricultural scientists will also find this a useful resource. | ||
| 988 | _aSpringer_BiomedLife_2023 | ||
| 650 | 7 |
_2embne _9168923 _aPlantas _xReproducción |
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| 856 | 4 | 0 |
_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-19-7498-4 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid) |
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| 998 |
_b03/2024 _dz _eu _zSI |
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