A Framework for Identification of Healthy Potted Seedlings in Automatic Transplanting System Using Computer Vision

Automatic transplanting of seedlings is of great significance to vegetable cultivation factories. Accurate and efficient identification of healthy seedlings is the fundamental process of automatic transplanting. This study proposed a computer vision-based identification framework of healthy seedlings. Vegetable seedlings were planted in trays in the form of potted seedlings. Two-color index operators were proposed for image preprocessing of potted seedlings. An optimal thresholding method based on the genetic algorithm and the three-dimensional block-matching algorithm (BM3D) was developed to denoise and segment the image of potted seedlings. The leaf area of the potted seedling was measured by machine vision technology to detect the growing status and position information of the potted seedling. Therefore, a smart identification framework of healthy vegetable seedlings (SIHVS) was constructed to identify healthy potted seedlings. By comparing the identification accuracy of 273 potted seedlings images, the identification accuracy of the proposed method is 94.33%, which is higher than 89.37% obtained by the comparison method.

Development of a picking and dropping mechanism for protray grown vegetable seedlings

In India, manual transplanting of vegetable seedlings was the commonly adopted method for raising vegetable crops, but it is laborious, time-consuming and costly. Therefore, mechanical transplanters are developed to overcome the problems in manual transplanting. The present work was to develop multiple seedlings picking and transferring mechanism for protray grown vegetable seedlings. Tomato (Solanum lycopersicum), chilli (Capsicum annuum) and brinjal (Solanum melongena) seedlings were raised in portrays with coir pith as a growth media and used for transplanting operation. The mechanism was to pick seven numbers of seedlings in one row at a time and transfer them into lateral conveying system, which could deliver the seedlings one by one on to the ground at regular interval. Programmable Logic Controller was used to controlling entire operations of seedlings picking and dropping. At the time of evaluation, a totally 196 number of seedlings were used with 98 cell protray. From the test results, the success rate of 89.28 per cent, missing seedling of 3.57 per cent, damaged seedling of 4.08 per cent, seedling delivering failure of 3.06 per cent were recorded for tomato seedlings. Similarly, in chilli and brinjal the success rate of 95.40 and 91.83 per cent, the missing seedling of 2.04 and 2.55 per cent, damaged seedling of 1.53 and 3.06 per cent and seedling delivering failure of 1.02 and 2.55 per cent respectively were observed. Transplanting frequency of developed mechanism was 2520 seedlings h-1. As a whole, this work was able to develop a working model of vegetable seedling transplanting mechanism, which can eject seven seedlings at a time from portray cell and transfer them into the slotted conveyor.