Predicting the probability of occurrence of floral malformation in mango (Mangifera indica L) under climate change scenario

Authors

  • Usha K Division of Fruits and Horticulture Technology, Indian Agricultural Research Institute, New Delhi, India
  • Nagaraja A Division of Fruits and Horticulture Technology, Indian Agricultural Research Institute, New Delhi, India
  • Sahoo R N Division of Agricultural Physics, Indian Agricultural Research Institute, New Delhi, India
  • Singh B Centre for Environment Science and Climate Resilient Agriculture, Indian Agricultural Research Institute, New Delhi, India
  • Naresh Kumar S Centre for Environment Science and Climate Resilient Agriculture, Indian Agricultural Research Institute, New Delhi, India

Keywords:

weather surface, spatial interpolation, mapping malformation, climate change logistic quadratic model

Abstract

Malformation is a serious threat to mango cultivation in various Countries. The analysis of the potential impacts of climate change on mango malformation disease is essential for developing strategies to control malformation. The prediction of mango malformation occurrence was therefore undertaken by two approaches. In the first method, weather surfaces were generated using spatial interpolation technique (Kriging) for four weather s viz., Tmax, Tmin, relative humidity and wind speed. The zonation was done using the threshold values conducive for Fusarium mangiferae growth and proliferation. The second method was statistical approach, using logistic quadratic model for predicting the probabilities of susceptible mango malformation areas in India. The results revealed that the spatial zonation of areas with mango malformation occurrence is higher for individual weather variable. However, when both temperature and relative humidity were used in combination, the area was considerably reduced. The study was also useful in classifying the area spatially using the threshold value for occurrence and non-occurrence of mango malformation. In case of logit model, the model was well fitted for predicting the probability of mango malformation occurrence. The model predicted high probability of mango malformation occurrence in Delhi, Uttar Pradesh and Haryana followed by Gujarat, Punjab and Jharkhand.

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References

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Published

2022-04-15

How to Cite

[1]
U. K, N. A, S. R N, S. B, and N. K. S, “Predicting the probability of occurrence of floral malformation in mango (Mangifera indica L) under climate change scenario”, Int. J. Phytol. Res., vol. 2, no. 2, pp. 06–13, Apr. 2022.

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