Special Issue "Precision Management of Fruit Trees"

A special issue of Horticulturae (ISSN 2311-7524). This special issue belongs to the section "Fruit Production Systems".

Deadline for manuscript submissions: 20 May 2022.

Special Issue Editors

Prof. Dr. Riccardo Lo Bianco
E-Mail Website
Guest Editor
Department of Agricultural, Food and Forest Sciences, University of Palermo Viale delle Scienze, Edificio 4, Ingresso H, 90128 Palermo, Italy
Interests: fruit tree physiology; water relations; carbon metabolism; source–sink relations; carbon partitioning; tree fruit production; planting systems; deficit irrigation management; crop load and fruit quality
Special Issues, Collections and Topics in MDPI journals
Dr. Antonino Pisciotta
E-Mail Website
Guest Editor
Department of Agricultural, Food and Forest Sciences, University of Palermo Viale delle Scienze, Edificio 4, Ingresso H, 90128 Palermo, Italy
Interests: viticulture, water relations; source–sink relations, table grapes; grapevine varieties; precision viticulture
Special Issues, Collections and Topics in MDPI journals
Dr. Luigi Manfrini
E-Mail Website
Guest Editor
Department of Agricultural and Food Sciences – DISTAL - Alma Mater Studiorum, University of Bologna, Viale Fanin, 46, 40127 Bologna, Italy
Interests: application of new technologies and precision management techniques; effects of the environment on fruit tree physiology; developing new management strategies to improve orchards’ sustainability, maintaining a high level of quality and yields
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Under a global climate change, plants will be facing increasing abiotic and biotic constraints. We have to expect a rise in average daily temperatures, atmospheric CO2 concentration, soil salinity in some areas, and water stress by drought or floods. Climate change can significantly alter plant functioning and productivity, affecting crop management sustainability and ultimately the whole food economy. Today’s technological advancements offer an excellent opportunity for the precise management of fruit trees aiming at the highest production quality and efficiency. New generation sensors exist and can be further implemented for the precise management of a number of operations both in the field (irrigation, nutrition, pest control, pruning, harvesting, etc.) and during post-harvest processing.

Further investigations and good knowledge sharing across the areas of horticulture, basic plant physiology, and engineering are required in order to improve fruit tree management by optimizing water, nutrients, and chemical inputs. Precise and automated systems will have to represent the future for a modern and sustainable fruit production. This Special Issue aims to stimulate and collect these kinds of studies, keeping in mind that precision management must represent the basis for an efficient and sustainable fruit production under a changing environment.

Prof. Dr. Riccardo Lo Bianco
Dr. Antonino Pisciotta
Dr. Luigi Manfrini
Guest Editors

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. Horticulturae 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

  • crop load
  • deficit irrigation
  • mineral nutrition
  • fruit quality
  • light interception
  • planting systems
  • rootstocks
  • training forms
  • yield efficiency
  • water use efficiency

Published Papers (4 papers)

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Research

Article
Estimation of Vegetative Growth in Strawberry Plants Using Mobile LiDAR Laser Scanner
Horticulturae 2022, 8(2), 90; https://doi.org/10.3390/horticulturae8020090 - 19 Jan 2022
Viewed by 116
Abstract
Monitoring of plant vegetative growth can provide the basis for precise crop management. In this study, a 2D light detection and ranging (LiDAR) laser scanner, mounted on a linear conveyor, was used to acquire multi-temporal three-dimensional (3D) data from strawberry plants (‘Honeoye’ and [...] Read more.
Monitoring of plant vegetative growth can provide the basis for precise crop management. In this study, a 2D light detection and ranging (LiDAR) laser scanner, mounted on a linear conveyor, was used to acquire multi-temporal three-dimensional (3D) data from strawberry plants (‘Honeoye’ and ‘Malling Centenary’) 14–77 days after planting (DAP). Canopy geometrical variables, i.e., points per plant, height, ground projected area, and canopy volume profile, were extracted from 3D point cloud. The manually measured leaf area exhibited a linear relationship with LiDAR-derived parameters (R2 = 0.98, 0.90, 0.93, and 0.96 with number of points per plant, volume, height, and projected canopy area, respectively). However, the measuring uncertainty was high in the dense canopies. Particularly, the canopy volume estimation was adapted to the plant habitus to remove gaps and empty spaces in the canopy point cloud. The parametric values for maximum point to point distance (Dmax) = 0.15 cm and slice height (S) = 0.10 cm resulted in R² = 0.80 and RMSPE = 26.93% for strawberry plant volume estimation considering actual volume measured by water displacement. The vertical volume profiling provided growth data for cultivars ‘Honeoye’ and ‘Malling Centenary’ being 51.36 cm³ at 77 DAP and 42.18 cm3 at 70 DAP, respectively. The results contribute an approach for estimating plant geometrical features and particularly strawberry canopy volume profile based on LiDAR point cloud for tracking plant growth. Full article
(This article belongs to the Special Issue Precision Management of Fruit Trees)
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Article
Light Quality Environment and Photomorphological Responses of Young Olive Trees
Horticulturae 2021, 7(10), 369; https://doi.org/10.3390/horticulturae7100369 - 06 Oct 2021
Cited by 1 | Viewed by 931
Abstract
Tree densities have increased greatly in olive orchards over the last few decades. In many annual crop species, increased density reduces the horizontal red/far-red (R/FR) and blue/green (B/G) ratios during canopy development even before direct shading occurs, and such changes are known to [...] Read more.
Tree densities have increased greatly in olive orchards over the last few decades. In many annual crop species, increased density reduces the horizontal red/far-red (R/FR) and blue/green (B/G) ratios during canopy development even before direct shading occurs, and such changes are known to alter plant morphology. This study with olive trees evaluated: (1) whether the leaf area index (LAI) of neighboring trees modifies the light quality environment prior to a tree being directly shaded and (2) the potential morphological responses of three olive cultivars to changes in light quality. Increasing LAI using different spatial arrangements of potted, three-year-old trees reduced the horizontal R/FR ratio more than that of the B/G ratio. Cultivar-specific responses to low R/FR ratio were observed for individual leaf area and aboveground/belowground biomass ratio using laterally positioned FR mirrors or green fences. No statistically significant responses were detected in response to green vegetation fences that reduced both horizontal R/FR and B/G ratios, but a cluster analysis grouped together the overall morphological responses to both FR mirrors and green fences. These results in olive trees suggest that cultivar differences in response to light quality may be relevant for understanding adaptation to dense orchards and identifying cultivars best suited to them. Full article
(This article belongs to the Special Issue Precision Management of Fruit Trees)
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Article
High-Resolution UAV Imagery for Field Olive (Olea europaea L.) Phenotyping
Horticulturae 2021, 7(8), 258; https://doi.org/10.3390/horticulturae7080258 - 21 Aug 2021
Viewed by 539
Abstract
Remote sensing techniques based on images acquired from unmanned aerial vehicles (UAVs) could represent an effective tool to speed up the data acquisition process in phenotyping trials and, consequently, to reduce the time and cost of the field work. In this study, we [...] Read more.
Remote sensing techniques based on images acquired from unmanned aerial vehicles (UAVs) could represent an effective tool to speed up the data acquisition process in phenotyping trials and, consequently, to reduce the time and cost of the field work. In this study, we assessed the ability of a UAV equipped with RGB-NIR cameras in highlighting differences in geometrical and spectral canopy characteristics between eight olive cultivars planted at different planting distances in a hedgerow olive orchard. The relationships between measured and estimated canopy height, projected canopy area and canopy volume were linear regardless of the different cultivars and planting distances (RMSE of 0.12 m, 0.44 m2 and 0.68 m3, respectively). A good relationship (R2 = 0.95) was found between the pruning mass material weighted on the ground and its volume estimated by aerial images. NDVI measured in February 2019 was related to fruit yield per tree measured in November 2018, whereas no relationships were observed with the fruit yield measured in November 2019 due to abiotic and biotic stresses that occurred before harvest. These results confirm the reliability of UAV imagery and structure from motion techniques in estimating the olive geometrical canopy characteristics and suggest further potential applications of UAVs in early discrimination of yield efficiency between different cultivars and in estimating the pruning material volume. Full article
(This article belongs to the Special Issue Precision Management of Fruit Trees)
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Article
Reliability of a Handheld Bluetooth Colourimeter and Its Application to Measuring the Effects of Time from Harvest, Row Orientation and Training System on Nectarine Skin Colour
Horticulturae 2021, 7(8), 255; https://doi.org/10.3390/horticulturae7080255 - 19 Aug 2021
Cited by 1 | Viewed by 474
Abstract
This work aimed to (i) determine the reliability of a portable Bluetooth colourimeter for fruit colour measurements; (ii) characterise the changes in quantitative skin colour attributes in a nectarine cultivar in response to time from harvest; and (iii) determine the influence of row [...] Read more.
This work aimed to (i) determine the reliability of a portable Bluetooth colourimeter for fruit colour measurements; (ii) characterise the changes in quantitative skin colour attributes in a nectarine cultivar in response to time from harvest; and (iii) determine the influence of row orientation and training system on nectarine skin colour. The skin colour attributes measured with the colourimeter, namely L*, a* and b*, were calibrated and validated against a reference spectrophotometer. C* and h° were obtained from a* and b*. Skin colour was measured in situ from 42 days before to 6 days after harvest on ‘Majestic Pearl’ nectarines subjected to different row orientations and training systems. Validation models showed high reliability of colour estimations. The trends of colour attributes over time were characterised by cubic regression models, with h° proving to be the best parameter to describe changes of colour over time, with a clear link to the maturation process. No significant effects of row orientation and training system on skin colour were observed at harvest. Overall, the device proved reliable for fruit colour detection. Results of this study highlight the potential of h° as a quantitative index to monitor ripening prior to harvest in ‘Majestic Pearl’ nectarines. Full article
(This article belongs to the Special Issue Precision Management of Fruit Trees)
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