Fruit tree yield estimation method and device

Abstract

The invention relates to the field of agricultural information technology, and discloses a fruit tree yield estimation method and a fruit tree yield estimation device. The method comprises the steps of: S101, obtaining a crown image of a single fruit tree in a mature stage and position data of the fruit tree; S102, identifying number of fruits in the image according to color and shape characteristics of the fruits; S103, computing fruit yield data of the single fruit tree; S104, generating a yield statistical chart according to the position data of the fruit tree and the computed fruit yield data of the single fruit tree. By using the fruit tree yield estimation method and device provided by the invention, professional devices and technical staffs are not needed, method is simple, economic cost is low, repeatability is high; furthermore, the method focuses on the single fruit tree instead of a whole planting area, thus being more suitable for scattered farmers, and convenient for the farmers to rapidly adjust management strategies according to actual situations.

Description

technical field [0001] The invention relates to the field of agricultural information technology, in particular to a method and device for estimating fruit tree yield. Background technique [0002] China's apple planting area and output rank first in the world, and it is also the largest apple consumer. However, the orchard management level is relatively backward, and it is mostly restricted by artificial management and natural climate, so the annual apple output is very unstable. Sexuality, and further cause fluctuations in market supply and fruit farmers' income. If the grower can estimate the apple output through some relatively simple methods during the apple growth process, and adjust the production management and sales strategy in time according to the estimated output, it can effectively save the input of production materials, increase the income of the grower, and achieve economic benefits. A win-win with eco-efficiency. However, the current two mainstream methods ...

AI Technical Summary

Problems solved by technology

Therefore, the existing mainstream methods all require the guidance of professional technicians and the support of professional equipment. The materials required for production estimation need to be repeatedly invested, and the cost is relatively high. The operation steps are cumbersome and the prediction period is relatively long, which is not conducive to Popularization and application among ordinary growers

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