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| DIVA-GIS and MaxEnt based diversity indices help in understanding trait and geographic diversity in maize in India | |
| 发表日期 | 2024 |
| ISSN | 0025-6153 |
| EISSN | 2279-8013 |
| 起始页码 | 67 |
| 结束页码 | 1 |
| 卷号 | 67期号:1 |
| 英文摘要 | A total of 62 diverse late maturing hybrids of maize (Zea mays L.) both from public and private sector were evaluated during Rainy (Kharif) 2018 across four diverse geographic locations (centres) of the peninsular region of India, viz., Coimbatore, Dharwad, Karimnagar and Hyderabad. The data, viz., plant height, cob height, days to 50% anthesis, days to 50% silking, days to 75% maturity and cob weight was analysed for diversity and richness indices using DIVA-GIS software. The objective was to identify the trait (s), which showed more diversity or richness among the hybrids and to identify the geographical region which was more efficient resolving the diversity and richness in the hybrids. Ecological niche modelling using Maximum Entropy method was analysed to identify the potential regions for growing the elite maize hybrids. The study was able to conclude that the trait plant height recorded maximum diversity index among all the traits, the Hyderabad location was most suitable for resolving diversity among the hybrids and also based on MaxEnt it was concluded that regions in the states of Andhra Pradesh, Assam, Gujarat, Karnataka, Kerala, Madhya Pradesh, Maharashtra, Odisha, Pondicherry, Tamil Nadu, Telangana and Tripura were the potential regions, under current climatic conditions, suitable for these hybrids under testing. |
| 英文关键词 | Diversity; richness; DIVA-GIS; MaxEnt; maize |
| 语种 | 英语 |
| WOS研究方向 | Agriculture ; Plant Sciences |
| WOS类目 | Agronomy ; Plant Sciences |
| WOS记录号 | WOS:001201694900003 |
| 来源期刊 | MAYDICA
 |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/296022 |
| 作者单位 | Indian Council of Agricultural Research (ICAR); ICAR - Indian Institute of Maize Research; Indian Council of Agricultural Research (ICAR); ICAR - National Bureau of Plant Genetics Resources; Tamil Nadu Agricultural University; Indian Council of Agricultural Research (ICAR); ICAR - Indian Institute of Maize Research; Indian Council of Agricultural Research (ICAR); ICAR - National Academy of Agricultural Research & Management |
| 推荐引用方式 GB/T 7714 | . DIVA-GIS and MaxEnt based diversity indices help in understanding trait and geographic diversity in maize in India[J],2024,67(1). |
| APA | (2024).DIVA-GIS and MaxEnt based diversity indices help in understanding trait and geographic diversity in maize in India.MAYDICA,67(1). |
| MLA | "DIVA-GIS and MaxEnt based diversity indices help in understanding trait and geographic diversity in maize in India".MAYDICA 67.1(2024). |
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