Models for economic evaluation of multi-purpose apple harvest platform and software development

Abstract

An increasing number of U.S. apple growers are now interested in using harvest platforms to increase harvest productivity, expand labor pool, and alleviate tough working conditions. To maximize benefits, functions of thinning, pruning & training, and infield sorting have been or are to be incorporated into harvest platforms. Though growers are most concerned with economic benefits, few cost-benefit studies had been conducted on different platforms. In the meantime, economic analysis procedure is complex and each analysis is for one specific machine (not for general purposes). No software has been developed as a general and ready-to-use tool for growers and researchers for the platform economic analysis. In this study, platforms, both available on the marketplace and developed in lab as pilot trials, were reviewed. Costs and benefits models were then established, based on which multipurpose apple harvest platform economic evaluation software (iMPAHP) was developed (capable of evaluating a wide variety of apple harvest platforms). A case study (machine cost of $100 000, accommodating 6 workers, processing apple incidence of 10% with 90% sort-out rate, and harvest, thinning, and pruning & training productivity increase by 40%, 50%, and 60%, respectively) based on iMPAHP demonstrated that infield sorting, harvest, thinning, and pruning and training accounted for 48.4%, 23.9%, 14.3%, and 13.4% of the total benefits, respectively. In the case that the platform was in all-four-purpose-application, the net present value (NPV) analysis of a 10-year investment showed a positive return of $60 547. However, without infield sorting function, the NPV resulted in a negative value, indicating a loss for the machine investment. Though incorporating the modular infield sorting system certainly increased the overall machine investment by $30 000, the benefits outweighed the costs.

A Survey of Robotic Harvesting Systems and Enabling Technologies

“…conditions of farmers and agricultural workers that are generally linked to various musculoskeletal disorders [2][3][4]. Application of robotic solutions regarding crop monitoring and harvesting is considered to have significant beneficial effects on production profits [5], enabling faster and easier automated harvest and increasing crop quality and yield. Thus, the development of robotic technologies and their application in agriculture is becoming a growing topic of interest and consideration [6], with an increasing amount of research work being noticed in the last decades.…”

“…wheat and rice [18]. A brief review concerning various apple harvesting platforms is presented in [5] that additionally develops a software tool for their economic evaluation, while several literature studies on agricultural robotic systems are investigated including the AgROS emulation tool [19], classifying them with regard to their analysis approach and farming operations.…”

Artificial neural network-based repair and maintenance cost estimation model for rice combine harvesters

“…Existing R&M cost estimation techniques are categorized into two groups: mathematical and ANN models. The first group consists of: (a) the American Society of Agricultural Engineers (ASAE) standards [2,4,5,[8][9][10][11][12][13][14] , and (b) curve fitting methods [15][16][17][18][19][20][21] . The mathematical models require a substantial amount of data for accurate estimation.…”

Robotic Tree-Fruit Harvesting With Telescoping Arms: A Study of Linear Fruit Reachability Under Geometric Constraints

“…However, the necessity of multiple pickings and the mass removal process which leaves either too many overripe or under-ripe fruit, or both, prevented the commercial adoption of such systems for fresh market harvest. Next, orchard platforms/ harvest aids were developed by researchers [13] [14] and commercial companies [15] [16] [17] that reduce worker movement between ladders and bins by positioning the worker and bin on a raised platform. Research done on worker productivity using platforms in narrow-inclined trellises showed a 44% increase over conventional hand harvesting [18], whereas research done in open vase training systems resulted in no improvement [19].…”