Works matching DE "RICE yields"
Results: 2122
Integrating quantified risk in efficiency analysis: evidence from rice production in East and Southern Africa.
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- Agrekon, 2017, v. 56, n. 4, p. 383, doi. 10.1080/03031853.2017.1387580
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Genetic and epistatic effects for grain quality and yield of three grain-size QTLs identified in brewing rice (Oryza sativa L.).
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- Molecular Breeding, 2020, v. 40, n. 9, p. N.PAG, doi. 10.1007/s11032-020-01166-0
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Overexpression of TCP transcription factor OsPCF7 improves agronomic trait in rice.
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- Molecular Breeding, 2020, v. 40, n. 5, p. 1, doi. 10.1007/s11032-020-01129-5
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Genetic improvement of panicle-erectness japonica rice toward both yield and eating and cooking quality.
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- Molecular Breeding, 2020, v. 40, n. 5, p. 1, doi. 10.1007/s11032-020-01127-7
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Identification and fine mapping of a major QTL, qHD19, that plays pleiotropic roles in regulating the heading date in rice.
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- Molecular Breeding, 2020, v. 40, n. 3, p. 1, doi. 10.1007/s11032-020-1109-x
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Characterization and fine-mapping of qHd2-1, a minor quantitative locus that affects heading date under long-day conditions in rice (Oryza sativa L.).
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- Molecular Breeding, 2020, v. 40, n. 3, p. 1, doi. 10.1007/s11032-020-1107-z
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Molecular mechanisms underlying plant architecture and its environmental plasticity in rice.
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- Molecular Breeding, 2019, v. 39, n. 12, p. 1, doi. 10.1007/s11032-019-1076-2
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LONG GRAIN 1: a novel gene that regulates grain length in rice.
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- Molecular Breeding, 2019, v. 39, n. 9, p. N.PAG, doi. 10.1007/s11032-019-1032-1
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Identification and fine mapping of qGN1c, a QTL for grain number per panicle, in rice (Oryza sativa).
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- Molecular Breeding, 2019, v. 39, n. 9, p. N.PAG, doi. 10.1007/s11032-019-1039-7
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Erect panicle architecture contributes to increased rice production through the improvement of canopy structure.
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- Molecular Breeding, 2019, v. 39, n. 9, p. N.PAG, doi. 10.1007/s11032-019-1037-9
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Breeding lines of the Indian mega-rice variety, MTU 1010, possessing protein kinase OsPSTOL (Pup1), show better root system architecture and higher yield in soils with low phosphorus.
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- Molecular Breeding, 2018, v. 38, n. 12, p. 1, doi. 10.1007/s11032-018-0903-1
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Identification and fine mapping of qWBPH11 conferring resistance to whitebacked planthopper (Sogatella furcifera Horvath) in rice (Oryza sativa L.).
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- Molecular Breeding, 2018, v. 38, n. 7, p. 1, doi. 10.1007/s11032-018-0846-6
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Breeding value estimation of the application of IPA1 and DEP1 to improvement of Oryza sativa L. ssp. japonica in early hybrid generations.
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- Molecular Breeding, 2014, v. 34, n. 4, p. 1933, doi. 10.1007/s11032-014-0150-z
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Genome-wide profiling of changes in gene expression in response to infection of the japonica rice variety Yunyin by Magnaporthe oryzae.
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- Molecular Breeding, 2014, v. 34, n. 4, p. 1965, doi. 10.1007/s11032-014-0155-7
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Dynamic quantitative trait locus analysis of seed dormancy at three development stages in rice.
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- Molecular Breeding, 2014, v. 34, n. 2, p. 501, doi. 10.1007/s11032-014-0053-z
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Rice LIM protein OsPLIM2a is involved in rice seed and tiller development.
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- Molecular Breeding, 2014, v. 34, n. 2, p. 569, doi. 10.1007/s11032-014-0058-7
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Over-expression of a fungal NADP(H)-dependent glutamate dehydrogenase PcGDH improves nitrogen assimilation and growth quality in rice.
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- Molecular Breeding, 2014, v. 34, n. 2, p. 335, doi. 10.1007/s11032-014-0037-z
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The effects of the photoperiod-insensitive alleles, se13, hd1 and ghd7, on yield components in rice.
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- Molecular Breeding, 2014, v. 33, n. 4, p. 813, doi. 10.1007/s11032-013-9994-x
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Identification of quantitative trait loci for grain size and the contributions of major grain-size QTLs to grain weight in rice.
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- Molecular Breeding, 2013, v. 31, n. 2, p. 451, doi. 10.1007/s11032-012-9802-z
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Expression of Arabidopsis DREB1C improves survival, growth, and yield of upland New Rice for Africa (NERICA) under drought.
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- Molecular Breeding, 2013, v. 31, n. 2, p. 255, doi. 10.1007/s11032-012-9785-9
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A large-effect QTL for rice grain yield under upland drought stress on chromosome 1.
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- Molecular Breeding, 2012, v. 30, n. 1, p. 535, doi. 10.1007/s11032-011-9642-2
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Growth characteristics and endosperm structure of superior and inferior spikelets of indica rice under high-temperature stress.
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- Biologia Plantarum, 2016, v. 60, n. 3, p. 532, doi. 10.1007/s10535-016-0606-6
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Inter-relationship between intercepted radiation and rice yield influenced by transplanting time, method, and variety.
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- International Journal of Biometeorology, 2019, v. 63, n. 3, p. 337, doi. 10.1007/s00484-018-01667-w
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Evaluation of multiple linear, neural network and penalised regression models for prediction of rice yield based on weather parameters for west coast of India.
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- International Journal of Biometeorology, 2018, v. 62, n. 10, p. 1809, doi. 10.1007/s00484-018-1583-6
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Boron application improves yield of rice cultivars under high temperature stress during vegetative and reproductive stages.
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- International Journal of Biometeorology, 2018, v. 62, n. 8, p. 1375, doi. 10.1007/s00484-018-1537-z
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Relationship between rice yield and climate variables in southwest Nigeria using multiple linear regression and support vector machine analysis.
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- International Journal of Biometeorology, 2018, v. 62, n. 3, p. 459, doi. 10.1007/s00484-017-1454-6
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Recent changes of rice heat stress in Jiangxi province, southeast China.
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- International Journal of Biometeorology, 2017, v. 61, n. 4, p. 623, doi. 10.1007/s00484-016-1239-3
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Monsoon variability, crop water requirement, and crop planning for kharif rice in Sagar Island, India.
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- International Journal of Biometeorology, 2015, v. 59, n. 12, p. 1891, doi. 10.1007/s00484-015-0995-9
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Identification of climate-resilient integrated nutrient management practices for rice-rice cropping system-an empirical approach to uphold food security.
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- International Journal of Biometeorology, 2015, v. 59, n. 1, p. 65, doi. 10.1007/s00484-014-0825-5
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A NOVEL APPROACH USING MACHINE LEARNING TO DETECT AND CLASSIFY RICE PLANT DISEASES.
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- i-Manager's Journal on Artificial Intelligence & Machine Learning (JAIM), 2024, v. 2, n. 1, p. 50, doi. 10.26634/jaim.2.1.20288
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Assessing the climate change and its impact on rice yields of Haridwar district using PRECIS RCM data.
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- Climatic Change, 2018, v. 148, n. 1/2, p. 265, doi. 10.1007/s10584-018-2176-4
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Climate change impacts on regional rice production in China.
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- Climatic Change, 2018, v. 147, n. 3/4, p. 523, doi. 10.1007/s10584-018-2151-0
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Spatial modelling of rice yield losses in Tanzania due to bacterial leaf blight and leaf blast in a changing climate.
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- Climatic Change, 2016, v. 135, n. 3/4, p. 569, doi. 10.1007/s10584-015-1580-2
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Response of rice production to elevated [CO] and its interaction with rising temperature or nitrogen supply: a meta-analysis.
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- Climatic Change, 2015, v. 130, n. 4, p. 529, doi. 10.1007/s10584-015-1374-6
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Temperature variations and rice yields in China: historical contributions and future trends.
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- Climatic Change, 2014, v. 124, n. 4, p. 777, doi. 10.1007/s10584-014-1136-x
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Impact assessment of climate change, carbon dioxide fertilization and constant growing season on rice yields in China.
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- Climatic Change, 2014, v. 124, n. 4, p. 763, doi. 10.1007/s10584-014-1129-9
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An assessment of regional vulnerability of rice to climate change in India.
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- Climatic Change, 2013, v. 118, n. 3/4, p. 683, doi. 10.1007/s10584-013-0698-3
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Impacts of a nuclear war in South Asia on rice production in Mainland China.
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- Climatic Change, 2013, v. 116, n. 2, p. 357, doi. 10.1007/s10584-012-0475-8
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Rice.
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- Nature, 2014, v. 514, n. 7524, p. S49, doi. 10.1038/514S49a
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SYSTEMATIC LITERATURE REVIEW: WILLINGNESS TO PAY FOR CONSUMERS TO ORGANIC RICE.
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- Jurnal Ekonomi dan Bisnis Airlangga, 2022, v. 33, n. 1, p. 21, doi. 10.20473/jeba.V33I12023.21-29
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Effect of multi-step soaking process on head rice yield of parboiled paddy.
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- Iran Agricultural Research, 2021, v. 40, n. 1, p. 93, doi. 10.22099/IAR.2021.39453.1426
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FARM LEVEL ALLOCATIVE EFFICIENCY OF RICE PRODUCTION IN LGA’S OF NIGER STATE, NIGERIA.
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- Achievers Journal of Scientific Research (AJOSR), 2024, v. 6, n. 1, p. 67
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Evaluating and Adapting Climate Change Impacts on Rice Production in Indonesia: A Case Study of the Keduang Subwatershed, Central Java.
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- Environments (2076-3298), 2021, v. 8, n. 11, p. 1, doi. 10.3390/environments8110117
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The big five in the world of plants - the species that have changed the course of history.
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- Polish Journal of Agronomy, 2021, v. 47, p. 68, doi. 10.26114/pja.iung.456.2021.47
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Weed communities and their negative impact on rice yield in no-input paddy fields in the northern part of Japan.
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- Biological Agriculture & Horticulture, 2017, v. 33, n. 4, p. 215, doi. 10.1080/01448765.2017.1299641
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Soil physical properties and grain yields of lowland rice in response to sawah preparation intensities and soil amendment types.
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- Biological Agriculture & Horticulture, 2016, v. 32, n. 3, p. 192, doi. 10.1080/01448765.2016.1152507
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Influence of Saccharomyces cerevisiae on gas exchange and yield attributes in rice under drought conditions.
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- Biological Agriculture & Horticulture, 2014, v. 30, n. 1, p. 52, doi. 10.1080/01448765.2013.845608
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Microbial enrichment of vermicompost prepared from different plant biomasses and their effect on rice (Oryza sativa L.) growth and soil fertility.
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- Biological Agriculture & Horticulture, 2012, v. 28, n. 4, p. 241, doi. 10.1080/01448765.2012.738556
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Arsenic levels in rice brands sold in Kampala: an experimental study to show the modifying effect of boiling, soaking and washing.
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- Journal of Food Safety & Hygiene, 2023, v. 9, n. 3, p. 162
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The effect of different growing environments on seedling development in transplanting paddy production.
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- Anadolu Journal of Agricultural Sciences / Anadolu Tarım Bilimleri Dergisi, 2021, v. 36, n. 3, p. 386, doi. 10.7161/omuanajas.908234
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