Special Issue "Mechanical Harvesting Technology in Orchards"

A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Agricultural Technology".

Deadline for manuscript submissions: 15 April 2022.

Special Issue Editor

Dr. Rafael-Ruben Sola-Guirado
E-Mail Website
Guest Editor
Department of Mechanics, University of Cordoba, 14014 Cordoba, Spain
Interests: engineering systems; mechanical harvesting; mechanization; fruit orchards

Special Issue Information

Dear Colleagues,

Harvesting is one of the most important operations in a crop. Part of this is due to the fact that this operation has traditionally had a high manual component. In some countries, the concept of mechanisation of this operation has been strongly introduced, and in others, it has been tackled to a lesser degree. This paradigm shift began with the introduction of the tractor, which led to the development of specific implements or equipment for the operation. Subsequently, a variety of devices and machinery were developed for harvesting and logistics. In parallel, numerous studies have been carried out to characterise the behaviour of machines and plants, and the phenomena resulting from their interaction. At present, new advances are being made in the field of robotisation of this operation—all this with a development that is linked to new emerging technologies and new techniques that can be adapted to improve mechanisation. In any case, research applied to the study and improvement of mechanised harvesting is key to the competitiveness and survival of many crops, and this must be carried out taking into account the machinery–orchards binomial. In this Special Issue, we hope to bring together those advances and research that deal with mechanised orchard harvesting.

Dr. Rafael-Ruben Sola-Guirado
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agriculture is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • machine
  • robotics
  • harvester
  • automation
  • precision agriculture
  • mechanization
  • vibration detachment
  • damage
  • field capacity
  • sensor

Published Papers (3 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Article
Mechanized Blueberry Harvesting: Preliminary Results in the Italian Context
Agriculture 2021, 11(12), 1197; https://0-doi-org.brum.beds.ac.uk/10.3390/agriculture11121197 - 27 Nov 2021
Viewed by 274
Abstract
This study reports some preliminary results on mechanical blueberry harvesting for the fresh market of cv. Cargo® in the Piedmont region (northwest Italy). The investigated area is one of the most productive areas of Italy, which specializes in fresh blueberry production. The [...] Read more.
This study reports some preliminary results on mechanical blueberry harvesting for the fresh market of cv. Cargo® in the Piedmont region (northwest Italy). The investigated area is one of the most productive areas of Italy, which specializes in fresh blueberry production. The automatization of harvesting operations could represent a competitive advantage for the area’s blueberry supply chain but could limit the quality of fresh-picked berries. A prototype machine and a commercial harvester (Easy Harvester®) were compared with manual picking, considering the harvesting efficiency, labor productivity, harvesting cost and farm rentability. In this context, the labor cost for manual harvesting exceeds EUR 2.00 per kg of saleable product. The prototype allowed a 39% cost reduction, and the Easy Harvester® reduced it by about half. Nevertheless, these positive performances do not consider the reduction in the net sale price of EUR 0.40 due to the selection costs in the warehouse. In this study, we highlight that the transition to mechanical harvesting requires the transformation of several farming and packhouse operations, such as new crop varieties, field configurations and cultivation techniques. However, a possible technical improvement of the Easy Harvester® could represent an opportunity for Italian farms in the planning of berry production and marketing, involving all of the supply chain actors. Further research on the use of mechanization in the sector must continue and be supported. Full article
(This article belongs to the Special Issue Mechanical Harvesting Technology in Orchards)
Show Figures

Figure 1

Article
Sugar Beet Damage Detection during Harvesting Using Different Convolutional Neural Network Models
Agriculture 2021, 11(11), 1111; https://0-doi-org.brum.beds.ac.uk/10.3390/agriculture11111111 - 09 Nov 2021
Viewed by 348
Abstract
Mechanical damages of sugar beet during harvesting affects the quality of the final products and sugar yield. The mechanical damage of sugar beet is assessed randomly by operators of harvesters and can depend on the subjective opinion and experience of the operator due [...] Read more.
Mechanical damages of sugar beet during harvesting affects the quality of the final products and sugar yield. The mechanical damage of sugar beet is assessed randomly by operators of harvesters and can depend on the subjective opinion and experience of the operator due to the complexity of the harvester machines. Thus, the main aim of this study was to determine whether a digital two-dimensional imaging system coupled with convolutional neural network (CNN) techniques could be utilized to detect visible mechanical damage in sugar beet during harvesting in a harvester machine. In this research, various detector models based on the CNN, including You Only Look Once (YOLO) v4, region-based fully convolutional network (R-FCN) and faster regions with convolutional neural network features (Faster R-CNN) were developed. Sugar beet image data during harvesting from a harvester in different farming conditions were used for training and validation of the proposed models. The experimental results showed that the YOLO v4 CSPDarknet53 method was able to detect damage in sugar beet with better performance (recall, precision and F1-score of about 92, 94 and 93%, respectively) and higher speed (around 29 frames per second) compared to the other developed CNNs. By means of a CNN-based vision system, it was possible to automatically detect sugar beet damage within the sugar beet harvester machine. Full article
(This article belongs to the Special Issue Mechanical Harvesting Technology in Orchards)
Show Figures

Figure 1

Article
Comparison of a Lightweight Experimental Shaker and an Orchard Tractor Mounted Trunk Shaker for Fresh Market Citrus Harvesting
Agriculture 2021, 11(11), 1092; https://0-doi-org.brum.beds.ac.uk/10.3390/agriculture11111092 - 04 Nov 2021
Viewed by 300
Abstract
A designed lightweight experimental shaker successfully used to collect ornamental oranges has been tested to harvest fresh market citrus. The aim of this study was to evaluate the removal efficiency and operational times of this experimental device compared to an orchard trunk shaker. [...] Read more.
A designed lightweight experimental shaker successfully used to collect ornamental oranges has been tested to harvest fresh market citrus. The aim of this study was to evaluate the removal efficiency and operational times of this experimental device compared to an orchard trunk shaker. Three different collecting systems were studied. ‘Caracara’ citrus trees were tested. Removal efficiency, vibration parameters, fruit and tree damages, and fruit quality were measured. A high-speed camera was used to record operational times and determine cumulative removal percentage over vibration time. The canvases on the ground reduced the severe fruit damages but were not useful to protect against light damages. The experimental shaker produced a higher percentage of slightly damaged oranges. No significant differences in removal efficiency were found between the two harvesting systems. However, removal efficiency using the experimental device could be reduced by 40 percent and working time increase by more than 50 percent when access to the main branches was difficult. In agreement with previous results, the curve representing the branch cumulative removal percentage in time followed a sigmoidal pattern. A model was built showing that during the first 5 s more than 50 percent of the fruits were detached. Full article
(This article belongs to the Special Issue Mechanical Harvesting Technology in Orchards)
Show Figures

Figure 1

Back to TopTop