DIVA-GIS and MaxEnt based diversity indices help in understanding trait and geographic diversity in maize in India

DIVA-GIS and MaxEnt based diversity study

Authors

  • N. Sunil, N. Sunil,
  • N. Sivaraj
  • D. Bhadru
  • Kumari Vinodhana
  • R.M. Kachhapur
  • D. Sravani
  • B.Madhu
  • P. Ramesh
  • A. Dhandapani
  • Sujay Rakshit

Abstract

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.

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Published

2024-03-08

Issue

Vol. 67 No. 1

Section

Articles

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