NORMALIZED DIFFERENTIAL VEGETATIVE INDEX OF WINTER WHEAT, WINTER OIL SEED RAPE AND MAIZE DEPENDING ON THE DOSAGES OF NITROGEN FERTILIZERS AND NITRIFICATION INHIBITOR

Keywords: nitrification inhibitor, 3,4-dimethylpyrazole phosphate, urea-ammonia solution, normalized difference vegetation index, winter wheat, winter oil seed rape, maize.

Abstract

Purpose. To establish the relationship and the actual correlation between the level of normalized differential vegetative index and winter wheat, winter oil seed rape and maize yield under the condition of using different dosages of nitrogen fertilizers in the form of UAN-32 with the combined use of nitrification inhibitor. Methods. During 2018-2021, the research was conducted in the conditions of the research station of “Druzhba Nova” LLC, Varvynskyi district, Chernihiv region (a branch of the Kernel agricultural holding) on typical low-humus black soil. One-factor experiment. Control variant N10P30K40 (conditionally without nitrogen fertilizers). UAN-32 was applied at the normal rate according to the experimental variants, and the nitrification inhibitor 3,4 dimethylpyrazol phosphate was applied in spring, respectively, in the experimental variants on winter oil seed rape and mais as Control + N120+IN, Control + N130+IN, Control + N130 and on winter wheat as Control + N100+IN, Control + N120+IN, Control + N120. Normalized differential vegetation index (NDVI) was determined by the images from WorldView-2, WorldView-3, Geoeye-1 satellites (Maxar USA). Results. The level of NDVI in winter wheat, winter oil seed rape and corn increase as the applied nitrogen rates increase and the nitrification inhibitor is used. Thus, for winter wheat, on average for the three months of measurement June, July and August, such an increase for the 2018-2021 research years was 0.56-0.65 in 2018, 0.33-0.36 in 2019, 0.53-0.65 in 2020 and 0.30-0.33 in 2021. For corn 0.61-0.67; 0.58-0.62; 0.63-0.67 and 0.52-0.55, respectively. For winter oil seed rape, on average for the three months of measurement in April, May and June, such an increase for the 2018-2021 research years was 0.43-0.51 in 2018, 0.38-0.51 in 2020 and 0.36-0 ,40 in 2021. For all research years 2018-2021, an increase in the yield of winter wheat, winter oil seed rape, and corn according to the experiment variants with an increase in the nitrogen rate and the use of IN and a gradual decrease in yield with the maximum rate of nitrogen fertilizers but without the use of IN is monitored. Thus, for winter wheat, on average, over the 4 years of research 2018-2021, an increase in yield was recorded from the control Control variant N10P30K40 in 37.4 centner/ha to the Control + N100+IN in 62.7 centner/ha and Control + N120+IN in 63, 0 centner/ha and with a further decrease in yield on the experimental variant Control + N120 to 58.5 centner/ha. For winter oil seed rape, on average, over the 3 years of research 2018-2021, an increase in yield was recorded from the Control variant N10P30K40 from 24.8 centner/ha to the options Control + N120+IN in 30.6 centner/ha and Control + N130+IN in 31, 6 centner/ha and with a further decrease in yield on the experimental variant Control + N130 to 27.9 t/ha. And for corn, on average, over the 4 years of research 2018-2021, an increase in yield was recorded from the Control variant N10P30K40 from 81.4 centner/ha to the options Control + N120+IN in 97.5 centner/ha and Control + N130+IN in 95, 2 centner/ha and with a further decrease in yield on the experimental variant Control + N130 to 89.7 centner/ha. The correlation coefficient of NDVI with productivity on winter wheat was high at the level of 0.94-0.97 in July, it was high on winter oil seed rape at the level of 0.95-1.0 in April in all variants of the experiment with increased rates of nitrogen fertilizers using an inhibitor nitrification and without it. The correlation coefficient of NDVI with corn yield was positive but at a low level within the range of 0.42-0.55 only in June for all variants of the experiment. Conclusions. It was established that for all the research years 2018-2021, the highest level of NDVI, yield of winter wheat, winter oil seed rape and corn, and the correlation coefficient were in the variants of the experiment with an increased rate of nitrogen fertilizers and with the use of nitrification inhibitor. Thus, for winter wheat, on the variants Control + N100+IN, the NDVI was the highest in three months on average within the range of 0.33-0.65, and the yield was the highest within the range of 47.2-81.4 centner/ha. For winter oil seed rape and corn, on the variants Control + N120+IN and Control + N130+IN, the NDVI was the highest in the range of 0.39-0.51 and 0.55-0.67 on average over three months, and the yield was the highest in the range of 23,1-38.5 centner/ha and 82.7-111.9 centner/ha, respectively, for all 4 years of research 2018-2021. The correlation coefficient of NDVI with productivity was high in winter wheat at the level of 0.94-0.97 in July and winter oil seed rape at the level of 0.95-1.0 in April.

References

1. Chen Z., et al. Monitoring and management of agriculture with remote sensing. In: Liang, S. (Ed.), Advanсes in Remote Sensing. Springer Science + Business Media B.V., 2008. P.397–421.
2. Gitelson A.A., Kaufman Y.J., Merzlyak M.N. Use of a green channel in remote sensing of global vegetation from EOS-MODIS. Remote Sensing of Environment, 1996. 58 (3). P. 289-298.
3. Boogaard H.L., et al. Description of the MARS Crop Yield Forecasting System (MCYFS).METAMP-1/3. Alterra and VITO, Wageningen and Mol. 2002.
4. Hatfield J.L., Gitelson A.A., Schepers J.S., Walthall C.L. Application of spectral remote sensing for agronomic decisions. Agronomy Journal, 2008. V.100 (1). P.121-127.
5. Tucker C.J. Red and photographic infrared linear combinations for monitoring vegetation. Rem. Sens. Environ. 1979. No.8 (2), 127–150. https://doi.org/10.1016/0034- 4257(79)90013-0.
6. Myneni R.B., Hall F.G., Sellers P.J., Marshak A.L. The interpretation of spectral vegetation indexes. IEEE Transactions on Geoscience and Remote Sensing, 1995. V.33 (2). P.481-486.
7. Satira O., Berberoglu S. Crop yield prediction under soil salinity using satellite derivedvegetation indices. Field Crops Research. 2016. V.192. P. 134–143.
8. Тараріко О.Г., Сиротенко О.В., Ільєнко Т.В., Величко, В.А. Космічний моніторинг посушливих явищ. Вісник аграрної науки. 2012. Вип.№10. С. 16-20.
9. Jiang Z., Huete A.R. Global intercomparison of three NDVI datasets for 1981–2001. Remote Sensing of Environment, 2006. V.101 (2). P.366-379.
10. Pettorelli N., et al. Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends in Ecology & Evolution, 2005. Vol. 20 (9). P.503-510.
11. Ozesmi S.L., Bauer M.E. Satellite remote sensing of wetlands. Wetl. Ecol. Manag. 2002. No.10 (5). P.381–402. ttps://doi.org/10.1023/a:1020908432489.
12. Ghosh S., Mishra D.R., Gitelson A.A. Long-term monitoring of biophysical characteristics of tidal wetlands in the northern Gulf of Mexico – a methodological approach using MODIS. Rem. Sens. Environ. 2016. No.173, P.39–58. https://doi.org/10.1016/j. rse.2015.11.015.
13. Zhanga J., et al. Monitoring plant diseases and pests through remote sensing technology: A review. Computers and Electronics in Agriculture, 2019. V.165. P. 6-11.
14. Nilsson H.E. Remote sensing and image analysis in plant pathology. Annual Review Phytopathology. 1995. V.33. P. 489–528.
15. Huang J., Chen D, Cosh M.H. Sub-pixel reflectance unmixing in estimating vegetation water content and dry biomass of corn and soybeans cropland using normalized difference water index (NDWI) from satellites. Int. J. Remote Sens. 2009. V. 30 (8). P. 2075–2104.
16. Панченко Л.С., Букін Є.В., Комарова Л.А. Желтоножський В. А. Еколого-економічний аналіз використання азотних добрив у виробництві кукуру- дзи в Україні. Аграрний вісник Дніпропетровської області. 2018. Т.1. №64. С. 67-72.
17. Sulik J.J., Long D.S. Spectral indices for yellow canola flowers. Int. J. Remote Sens. 2015. Vol.36. P. 2751–2765.
18. Han J., Wei C., Chen Y., Weiwei L. Mapping Above- Ground Biomass of Winter Oilseed Rape Using High Spatial Resolution Satellite Data at Parcel Scale under Waterlogging Conditions. Int. J. Remote Sens. 2017. Vol.9 (3). P. 17.
19. Zhang W., Wang X., Zhang Y. Effect of nitrogen application rate on yield and nitrogen use efficiency of maize in Northeast China. Frontiers in Plant Science. 2016. V.7. P.1-12.
20. Ma B. L., Dwyer L. M. Nitrogen management for improving corn yield and nitrogen use efficiency in cool, humid regions. Agronomy Journal. 2015. V.107 (2). P.779-788.
21. Fernández M. C, Rubio G. Root morphological traits related to phosphorus-uptake efficiency of soybean, sunflower, and maize. Journal of Plant Nutrition and Soil Science. 2015. V.178. P. 807–815.
22. Legg J. O., Allison F. E. A tracer study of nitrogen balance and residual nitrogen availability with 12 soils. Soil Sei. Soc. Amer. Proc. 1967. V.31 (3). P. 403–406. 23. Vitousek P. M., et al. Human alteration of the global nitrogen cycle: sources and consequences. Ecological Applications. 1997. V.7 (3). P. 737-750.
24. Xu G., Fan X., Miller A. J. Plant nitrogen assimilation and use efficiency. Annual Review of Plant Biology. 2012. Vol. 63. P. 153–182.
25. Kumar K., еt al. Nitrification inhibitors from the soil environment and their potential use for enhancing crop production. Applied Microbiology and Biotechnology. 2017. V.101 (1). P.13-25.
26. Abalos D., et al. Meta-analysis of the effect of urease and nitrification inhibitors on crop productivity and nitrogen use efficiency. Agric. Ecosyst. Environ. 2014. No.189, P.136–144. doi:10.1016/j.agee.2014.03.036
27. Chunlian Q., еt al. How inhibiting nitrification affects nitrogen cycle and reduces environmental impacts of anthropogenic nitrogen input. Global Change Biology. 2015. No.21 (1249–1257), 3–5. doi: 10.1111/gcb.12802
28. Zerulla, W., еt al. (2001). 3,4-Dimethylpyrazole phosphate (DMPP) – a new nitrification inhibitor for agriculture and horticulture. Biol Fertil Soils. 2001. V.34 (79-84), P.1–4.
29. Commission regulation (EU) № 1257/2014 amending Regulation (EC) No. 2003/2003 of the European Parliament and of the Council relating to fertilizers for the purposes of adapting Annexes I and IV. 2014. P. 12.
Published
2024-10-29
Section
MELIORATION, ARABLE FARMING, HORTICULTURE