ISSN 2284-7995, ISSN Online 2285-3952


Published in Scientific Papers. Series "Management, Economic Engineering in Agriculture and rural development", Vol. 21 ISSUE 4
Written by Daniel DICU, Radu BERTICI, Mihai HERBEI, Florin SALA

The study used imaging analysis to monitor and predict production in sunflower culture under farm specific crop technology. The studied plot was located in the area of Cornesti, Timis County, Romania. Satellite images (Landsat 8) with a resolution of 30 m were taken, at 6 moments (T) between April and September, 2020. NDVI and NBR indices were calculated from the image analysis. The variation of the values of the indices calculated in relation to the time (days) for the studied period was faithfully described by spline models, with the values of the errors calculated ε = 0.0069in the case of NDVI and ε = 0.18945 in the case of NBR. The interdependent relationship found between the NDVI and NBR indices was described by a polynomial equation of degree 3, under conditions of R2=0.986, p=0.0015. Prediction of sunflower production (YP) based on the values of NDVI and NBR indices was possible under statistical safety conditions (R2=0.998, p<0.001). The variation of the prediction error, resulted from calculus, was between -0.331 kg ha--1 in the case of T4 indices (July 28) and 42.722 kg ha-1 in the case of T6 indices (September 6). The Similarity and Distance Indices (SDI) was used to evaluate the similarity of the vegetation stages on sunflower crop in relation to the moment of the image captures, based on NDVI and NBR indices. The highest degree of similarity was identified between moments T2 and T3 (images from May), in which case SDI = 0.05285. The study provided useful information on the temporal variability of sunflower crop and production prediction in relation to agricultural technology and is the basis of agricultural crop management models.

[Read full article] [Citation]

The publisher is not responsible for the opinions published in the Volume. They represent the authors’ point of view.

© 2019 To be cited: Scientific Papers. Series “Management, Economic Engineering in Agriculture and Rural Development“.

Powered by INTELIDEV