Spring is bright and blooming, and this year’s flower fields are no longer filled with breeders. Remote sensing drones have successfully completed the labor-saving seed testing of 430 peaches in Fengxian, 620 pears in Yangdu, Haining, and 430 rapeseed communities in Liangzhu, Hangzhou during the flowering season. The drone images and analysis results are synchronized to the digital platform – the “Precision Identification and Intelligent Application Platform for Crop Phenotypes”. Breeding personnel can complete traceability queries with just the movement of their fingers.
Flowering period is one of the most important phenological periods of crops. Especially for fruit trees, the flowering period is a crucial period for selecting pollinated varieties, providing important basis for water and fertilizer management, and improving fruit setting rate and yield. In hybrid breeding, flowering period is important phenotypic information and has important guiding significance for pollination breeding. The so-called seed testing is to investigate the variety characteristics of flowering plants.
In the past, traditional flowering survey mainly relied on manual on-site judgment and recording, which was time-consuming, laborious, and highly subjective. For breeders who usually need to carry out hybridization work during the flowering period, flowering investigation is a very heavy task.
The digital agriculture Research Institute of Zhejiang Academy of Agricultural Sciences focused on the UAV remote sensing platform around the demand of flowering test.
They have developed algorithms for drone image flower/bud recognition and flowering rate evaluation, and constructed a highly integrated and efficient flowering monitoring system that integrates “collection transmission processing”. At the same time, according to the needs of breeding personnel, a high-efficiency and high-throughput field phenotype collection platform based on RTK precise positioning drones has been constructed, achieving automated and rapid collection of phenotype information for breeding units such as communities and individual plants.
The unmanned aerial vehicle (UAV) automated flowering seed testing technology can significantly reduce the time for manual field surveys and improve the efficiency of data collection in breeding work.
Taking the investigation of pear germplasm resources as an example, after completing the preliminary flight mission, aerial photography of 800 pear trees can be completed in about an hour each time, and data analysis can be completed in 15 minutes to obtain the flower index of each pear tree. The entire process only requires one person to participate, and the operation is simple and highly efficient. Significantly reducing the pressure on breeding personnel.
In addition, this technology can not only evaluate the flowering rate, but also further analyze and extract a series of flowering traits such as flower color, opening/withering rate, and cluster shape.
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