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Prior to analysis, to prevent memory issues, dynamic data were cropped to extract images of 28×28×18 cm located around the heart using fixed cropping parameters.
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Temporal patterns of normalized differential vegetation index (NDVI) depend on and result from the complex relationship between NDVI and cropping practice parameters associated with a pixel.
The pad and crop parameters determine the output size.
The present work confirms the estimation abilities of fuzzy subtractive clustering in potato crop parameters estimation.
Significant variations in all the crop parameters were observed after cutting the crop and consequently made the problem more critical.
In agricultural engineering the potential of laser rangefinders for measuring crop parameters is nearby unexploited.
We observed crop parameters as well as landscape parameters in the areas surrounding fields in addition to temporal aspects.
The crop parameters exhibited short ranges of influence and about one third of their variability was unexplained.
These crop parameters are easily assessable through microwave remote sensing and therefore they can form the basis for prediction of pest remotely.
In the present paper, a subtractive based fuzzy inference system is introduced to estimate the potato crop parameters like biomass, leaf area index, plant height and soil moisture.
Information about site-specific crop parameters such plant height, coverage, and biomass density is important for optimising crop management and harvesting processes.
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