The present application belongs to the technical field of intelligent
agriculture, and discloses a monitoring method for a fruit bottom colorizing and light reflecting film, comprising the following steps: S1, forming a grid map for an
orchard; S2, collecting fruit bottom images to obtain array type multi-angle image data; S3, performing edge
processing on the image data to form fruit images; S4, performing fruit surface
color analysis on the fruit images to form color
feature data; S5, performing edge and dispersion analysis on
dark color patches in the
color analysis process to form
lesion feature data; S6, inputting the color
feature data and the
lesion feature data of S4 and S5 into a preset fruit maturity and
lesion grade
library to obtain preliminary maturity and sunscald grades; S7, performing feature weighting judgment to output maturity grades and / or sunscald lesion probabilities; S8, if the lesion probability is greater than a preset threshold, automatically recording a
collection time stamp, a lesion probability value, an image slice and a
map location, and triggering an early warning of adjusting the light reflecting film to weaken the radiant light; if the lesion probability is less than or equal to the preset threshold, normally recording data.