@inproceedings{0b54f8acd2f441ab8b5f778fafea4cf5,
title = "Automated machine for thinning lettuce - Development and evaluation",
abstract = "Despite the tremendous advances made in agricultural mechanization, the precise task of thinning lettuce seedlings is still performed by crews of workers using hand hoes in commercial field production. Finding laborers to perform this physically demanding work is becoming increasingly difficult. The objectives of this project were to 1) develop an automated machine for thinning lettuce to improve labor resource use efficiency and 2) evaluate the performance of the machine as compared to conventional methods. The prototype machine was developed to thin lettuce seedlings nominally planted 2 inches apart to the desired final plant spacing of 10-11 inches. The device is principally comprised of a machine vision system for detecting lettuce seedlings and their location and a system for intermittently delivering an herbicidal spray to kill plants. When tested at a travel speed of 1.5 mph, automated machine thinning performance in terms of plant spacing, plant spacing uniformity, number of live plants per acre and time required for a hand laborer to remove plants missed during thinning was not significantly different from hand thinning when plants were thinned using sulfuric acid (10% v/v), paraquat (1.3 pt a.i./acre) or vinegar (20% v/v) (P = 0.05). Automated machine thinning performance after hand weeding was also not significantly from hand thinning in terms of plant spacing, COV in plant spacing and plant stand when plants were sprayed with any of the five chemicals tested. Based on these results, it was concluded that the automated machine was able to reliably control spray delivery such that plants were selectively thinned to the desired final plant spacing. Yields were not significantly affected when plants were thinned using the automated machine with any of the herbicidal spray solutions tested indicating that the machine was able to deliver herbicidal spray with sufficient accuracy that seedlings are not injured. Further machine development is needed so that a unit more suitable for commercial production can be tested on a large scale to confirm these results and to determine whether such a system is viable for use in commercial production.",
keywords = "Automated, Lettuce, Machine, Machine vision, Performance testing, Plant recognition, Precision, Seedlings, Thinning",
author = "Siemens, {Mark C.} and Ryan Herbon and Gayler, {Ronald R.} and Nolte, {Kurt D.} and Davie Brooks",
year = "2012",
language = "English (US)",
isbn = "9781622762088",
series = "American Society of Agricultural and Biological Engineers Annual International Meeting 2012, ASABE 2012",
publisher = "American Society of Agricultural and Biological Engineers",
pages = "3221--3234",
booktitle = "American Society of Agricultural and Biological Engineers Annual International Meeting 2012, ASABE 2012",
note = "American Society of Agricultural and Biological Engineers Annual International Meeting 2012 ; Conference date: 29-07-2012 Through 01-08-2012",
}