Eggplant (Solanum melongena L.) at the two-leaf stage were grafted on scarlet eggplant (Solanum integrifolium Poir.) by hand or a newly developed robot. The scion and rootstock were fixed with an elastic tube for hand grafting or with an adhesive and a hardener for robotic grafting. After acclimatization, the grafted plants were planted at the three- or 11-leaf stage in a glasshouse. Plants grafted by the robot showed a higher percentage of survival, and attained the three- and 11-leaf stages 8 days earlier on average than those grafted by hand. Stems were longer, and shoot fresh mass and fruit yield of plants were higher for the three-leaf-than for the 11-leaf-stage planting, irrespective of the grafting method. Such vigorous growth and high yield by robotic grafting were absent for the 11-leaf-stage planting but obvious for the three-leaf-stage planting.
Masayuki Oda, Kunihiko Okada, Hidekazu Sasaki, Shigeki Akazawa, and Masahiro Sei
T. Burks, F. Villegas, M. Hannan, S. Flood, B. Sivaraman, V. Subramanian, and J. Sikes
Automated solutions for fresh market fruit and vegetable harvesting have been studied by numerous researchers around the world during the past several decades. However, very few developments have been adopted and put into practice. The reasons for this lack of success are due to technical, economic, horticultural, and producer acceptance issues. The solutions to agricultural robotic mechanization problems are multidisciplinary in nature. Although there have been significant technology advances during the past decade, many scientific challenges remain. Viable solutions will require engineers and horticultural scientists who understand crop-specific biological systems and production practices, as well as the machinery, robotics, and controls issues associated with the automated production systems. Focused multidisciplinary teams are needed to address the full range of commodity-specific technical issues involved. Although there will be common technology components, such as machine vision, robotic manipula-tion, vehicle guidance, and so on, each application will be specialized, due to the unique nature of the biological system. Collaboration and technology sharing between commodity groups offers the benefit of leveraged research and development dollars and reduced overall development time for multiple commodities. This paper presents an overview of the major horticultural and engineering aspects of robotic mechanization for horticultural crop harvesting systems.
Z. Mganilwa, M. Nagata, H. Wang, and Q. Cao
Based on seedling properties and stage of growth for cucurbitaceous and solanaceous vegetables, separate robots are being marketed for each. Full automatic grafting robots are used for solanaceous vegetables like tomato and egg-plant employing ordinary splice method by making a diagonal cut through the hypocotyl of both the scion and the rootstock. However, cutting one piece of cotyledon diagonally from the rootstock does grafting of cucurbitaceous vegetables like cucumber, melon, and pumpkin. This method had the advantage of easy recovery and high survival rate of seedlings. Only semi-automatic robots are marketed for this kind of plants because a fixed cotyledon orientation is required for grafting operation. Both the scion and the rootstock are loaded manually to their corresponding feeding devices. To replace the manual loading operation, this study proposed a neural network based automatic seedling loading system. The system automatically estimates the quality and determines the cotyledon orientation of seedling for guiding the loading device of the grafting robot. As a first step toward solution, we report the development of a model for seedling quality estimation and orientation detection using image processing and neural network techniques. The model has a learning ability and can judge seedlings according to the training patterns. A seedling leaves feature extraction model of 10 characteristics was proposed and a three-layer neural network was constructed. The experimental results indicate that the seedling leaves orientation was accurately detected with an average error of 3 degrees within 360 degrees of freedom and the machine vision system could properly classify seedlings into three classes (A-good, B-fair, and C-bad) according to the training pattern.
The commercial greenhouse operation, with a controlled and structured environment and a large number of highly repetitive tasks, offers many advantages for automation relative to other segments of agriculture. Benefits and incentives to automate are significant and include improving the safety of the work force and the environment, along with ensuring sufficient productivity to compete in today's global market. The use of equipment and computers to assist production also may be particularly important in areas where labor costs and/or availability are a concern. However, automation for greenhouse systems faces very significant challenges in overcoming nonuniformity, cultural practice, and economic problems. As a case study, a robotic workcell for processing geranium cuttings for propagation has been developed. The robot grasps randomly positioned cuttings from a conveyor, performs leaf removal, trims the stems, and inserts the cuttings into plug trays. While the system has been shown to process effectively many plants automatically, the robot is not equipped to handle successfully the wide variety of cuttings that a trained worker handles with aplomb. A key challenge in greenhouse automation will be to develop productive systems that can perform in a reliable and cost-effective way with highly variable biological products.
Yael Edan and James E. Simon
The spatial distribution patterns of five melon cultivars (Cucumis melo L. var. reticulatus) were evaluated by measuring XY coordinates of ripe fruit locations in the field. Fruit ripeness distribution over time was also evaluated for three cultivars by measuring the number of ripe fruit, fruit mass, and location over time. Spatial distribution curves for distances between fruit clusters and individual fruit from cluster centroids varied between clusters and were derived for each cultivar from the best fit curves based on chi-square analysis from the two-dimensional spatial fruit distribution. These equations can be used for predicting actual fruit locations in the field. Ripeness distribution patterns indicated that, while the exact duration of the effective harvesting period is cultivar-dependent, the ripeness trend for each of the cultivars was similar. Spatial distribution patterns vary among melon cultivars and must be recognized in the design of automated harvesting systems.
Availability and capability of labor have become dominating factors affecting agriculture's productivity and sustainability. Agricultural mechanization can substitute for human and animal physical power and improve operational uniformity. Automation complements mechanization by implementing the capabilities of automatic perception, reasoning, communication, and task planning. Fixed automation is traditionally cost-effective for mass production of standard items. In addition, flexible automation responds to make-to-order batch processing. The appropriateness of each automation type depends on the situation at hand. Because of their vast memory and high calculation speed, computers are highly effective for rapid information processing. Incorporating state-of-the-art hardware and software, computers can generate status reports, provide decision support, gather sensor signals, and/or instruct machines to perform physical work. It is no surprise, therefore, that computerization is essential to the evolutionary process, from mechanization through fixed automation to flexible automation. Fundamentals of agricultural mechanization, automation, and computerization applied to greenhouse production are discussed. Recent research activities conducted at Rutgers Univ. are presented for illustrative purposes.
Michael G. Bausher
Growing transplants that can withstand the rigors of open-field production is imperative for the successful adoption of grafting in large-scale commercial fields and especially for those who seek to adopt this technology as an alternative to soil fumigation. This study examines the relationship of tensile strength to graft angle and plant survival. Tomato (Solanum lycopersicum) seedlings of ‘FL-47’ and ‘Rutgers’ were used as scions on ‘Roma’ rootstock under greenhouse and healing chamber conditions. Scions were grafted at angles of 20°, 45°, and 70°. After a period of 10 days, the plants were severed near ground level and subjected to pull force analysis. Pull force of the graft increased significantly with the increased graft angle. Pull force between the 20° vs. 70° angles increased significantly as well as those of 45° vs. 70° grafts (P ≤ 0.001). Increase in graft angle resulted in greater survival of grafted plants from 79% (20°), 81% (45°), and 92% (70°). Fifteen commercial rootstocks grafted at 70° had survival percentage rates between 97% and 100%. These studies demonstrate that the angle can significantly impact graft integrity and plant survival.
Chieri Kubota, Michael A. McClure, Nancy Kokalis-Burelle, Michael G. Bausher, and Erin N. Rosskopf
production of grafted seedlings. Semi- or fully-automated grafting robots were invented by several agricultural machine industries ( Kurata, 1994 ) and some models are available in East Asia, Europe, and more recently in the United States. According to
Myles Lewis, Chieri Kubota, Russell Tronstad, and Young-Jun Son
grafting robots). The capital/facility items that we consider are found in the later section of capital costs. Each item has a typical “useful life” according to the available guidelines of the IRS (2012) . For example, farm buildings such as a headhouse