Sweet Corn Yield Simulation Using Normalized Difference Vegetation Index and Leaf Area Index

• Autorzy: Lykhovyd Pavlo

Identyfikatory

DOI

10.12911/22998993/118274

• Języki publikacji: EN

Abstrakty

EN

The authors determined the accuracy and reliability of yielding models by using the values of two differently obtained indices – the leaf area index (LAI) obtained through direct surface measurements, and the normalized difference vegetation index (NDVI) obtained through spatial remote sensing of crops. The study based on the drip-irrigated sweet corn yielded the data obtained in the field experiment held in the semi-arid climate on darkchestnut soil in the South of Ukraine. The suitability of the LAI and NDVI for the simulation of sweet corn yields was estimated by the regression analysis of the yielding data by correlation (R) and determination (R²) coefficients. Additionally, mathematical models for the crop yields estimation based on the regression analysis were developed. It was determined that LAI is a more suitable index for the crop yield prediction: the R² value was 0.92 and 0.94 against 0.85 for the NDVI-based models.I It was determined that it is better to use the LAI values obtained at the stage of flowering, when R² averaged to 0.94, and the NDVI-based models does not depend on the crop stage (the R² was 0.85 both for the flowering and ripening stages of the plant development). The combined NDVI-LAI model showed that there is no necessity in the complication of the LAI-based model through introduction of the remotely sensed index because of insignificant improvement in the performance (R² was 0.94 and 0.92).

Słowa kluczowe

EN

direct measurement; mathematical model; regression analysis; remote sensing; sweet corn; yield prediction

• Wydawca: Polskie Towarzystwo Inżynierii Ekologicznej ; Lublin University of Technology
• Czasopismo: Journal of Ecological Engineering
• Rocznik: 2020
• Tom: Vol. 21, nr 3
• Strony: 228--236
• Opis fizyczny: Bibliogr. 27 poz., tab.

Twórcy

autor

Lykhovyd Pavlo

• Department of Scientific and Innovative Activity, Transfer of Technologies and Intellectual Property, Institute of Irrigated Agriculture of NAAS, Naddniprianske, 73483, Kherson, Ukraine

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).