Relationship between NDVI, LST and simulated wheat yield with district wise reported yield: a case study of Bathinda, Punjab

Authors

  • ANJUSHA SANJAY GAWAI Department of Climate Change and Agricultural Meteorology, Punjab Agricultural University, Ludhiana
  • RAJ KUMAR PAL Department of Climate Change and Agricultural Meteorology, Punjab Agricultural University, Ludhiana
  • SONY BORA Department of Climate Change and Agricultural Meteorology, Punjab Agricultural Meteorology, Ludhiana
  • MANGSHATABAM ANNIE Department of Climate Change and Agricultural Meteorology, Punjab Agricultural University, Ludhiana-141004, Punjab

DOI:

https://doi.org/10.54386/jam.v26i3.2568

Keywords:

Land surface temperature, NDVI, CERES-wheat, Wheat yield

References

Kasampalis, D. A., Alexandridis, T. K., Deva, C., Challinor, A., Moshou, D. and Zalidis, G. (2018). Contribution of remote sensing on crop models: A Review. J. Imaging, 4: 52.

Kumar, D. A., Neelima, T. L., Srikanth, P., Devi, M. U., Suresh, K. and Murthy, C. S. (2022). Maize yield prediction using NDVI derived from Sentinal 2 data in Siddipet district of Telangana state. J. Agrometeorol., 24(2): 165-168. https://doi.org/10.54386/jam.v24i2.1635.

Kumar, K., Parihar, C. M., Sena, D. R., Godara, S., Patra, K., Sarkar, A. and Nayak, H. S. (2024). Modeling the growth, yield and N dynamics of wheat for decoding the tillage and nitrogen nexus in 8-years long-term conservation agriculture-based maize-wheat system. Front. Sustain. Food Syst., 8: 1-25.

Kumar, S. N., Aggarwal, P. K., Rani, D. S., Saxena, R., Chauhan, N. and Jain, S. (2014). Vulnerability of wheat production to climate change in India. Clim. Res., 59(3): 173-187.

Lobell, D. B., Sibley, A. and Ivan, O. J. (2012). Extreme heat effects on wheat senescence in India. Nat. Clim. Change, 2(3): 186-189.

Myneni, R. B., Hoffman, S., Knyazikhin, Y., Privette, J., Glassy, J., Tian, Y., Wang, Y., Song, X., Zhang, Y. and Smith, G. (2002). Global products of vegetation leaf area and fraction absorbed par from year one of MODIS data. Remote Sens. Environ., 83: 214–231.

Pal, R. K. and Yadav, B. K. (2018). Effect of soil variability on seed cotton yield using CROPGRO-cotton model for Bathinda district of Punjab. Prog. Res., 4: 339-42.

Pal, R. K., Rawat, K. S., Singh, J. and Murty, N. S. (2015). Evaluation of CSM-CERES-wheat in simulating wheat yield and its attributes with different sowing environments in Tarai region of Uttarakhand. J. Appl. Nat. Sci., 7: 404-09.

Pandey, Vyas. (2023). Climate variability, trends, projections and their impact on different crops: A case study of Gujarat, India. J. Agrometeorol., 25(2): 224–238. https://doi.org/10.54386/jam.v25i2.2151

Panek, E., and Gozdowski, D. (2020). Analysis of relationship between cereal yield and NDVI for selected regions of Central Europe based on MODIS satellite data. Remote Sens. Appl. Soc. Environ., 17: 100286.

Rezaei, E. E., Siebert, S., Manderscheid, R., Müller, J., Mahrookashani, A. and Ehrenpfordt, B. (2018). Quantifying the response of wheat yields to heat stress: the role of the experimental setup. Field Crop Res., 217: 93–103.

Shahhosseini, M., Martinez-Feria, R. A., Hu, G. and Archontoulis, S. V. (2019). Maize yield and nitrate loss prediction with machine learning algorithms. Environ. Res. Lett., 14:124026.

Singh, S., Amarinder, S. R., Prabhjyot, K. and Gurbax S. (2022). Assessing impact of temperature change on phenology and grain yield of wheat by using infocrop model. Agric. Res. J., 59 (6): 1151-1158.

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Published

01-09-2024

How to Cite

GAWAI , A. S., PAL, R. K., BORA, S., & ANNIE, M. (2024). Relationship between NDVI, LST and simulated wheat yield with district wise reported yield: a case study of Bathinda, Punjab. Journal of Agrometeorology, 26(3), 374–376. https://doi.org/10.54386/jam.v26i3.2568

Issue

Vol. 26 No. 3 (2024): September

Section

Short Communication

Categories

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Copyright (c) 2024 ANJUSHA SANJAY GAWAI , RAJ KUMAR PAL, SONY BORA, MANGSHATABAM ANNIE

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