Precision Management Systems for Sustainable Orchards and Vineyards

Editors

Department of Agricultural, Food and Forest Sciences, University of Palermo, Viale delle Scienze, Edificio 4, Ingresso H, 90128 Palermo, Italy
Interests: water relations; carbon partitioning; deficit irrigation; fruit quality and production systems of tree crops
Special Issues, Collections and Topics in MDPI journals
Department of Agricultural, Food and Forest Sciences, University of Palermo, 90128 Palermo, Italy
Interests: Irrigation management; fruit production; fruit quality
Department of Agricultural, Food and Forest Sciences (SAAF), University of Palermo, Viale delle Scienze, 13, 90128 Palermo, Italy
Interests: viticulture; vine; grapevine varieties; orchard systems
Special Issues, Collections and Topics in MDPI journals

Topical Collection Information

Dear Colleagues,

Under a global climate change, plants will face increasing abiotic and biotic constraints. We are already experiencing 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 orchards and vineyards, aiming toward the highest production quality and efficiency possible. Only precise and efficient production processes will finally be sustainable. 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 orchard and vineyard management. For these reasons, the mission of a Special Issue collection such as this is to share knowledge and bring scientists from different disciplines to work together towards modern, efficient, and sustainable orchard and vineyard management systems, increasing the interest of researchers, and the awareness of farmers and consumers.

Dr. Riccardo Lo Bianco
Dr. Roberto Massenti
Dr. Antonino Pisciotta
Collection Editors

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Keywords

  • precision farming
  • proximal sensing
  • remote sensing
  • yield efficiency
  • sustainable fruit production
  • climate change
  • fruit tree and grapevine stress tolerance
  • tree crop environment adaptation
  • intensive growing systems
  • irrigation management
  • fertilization management
  • fruit quality
  • pruning and training forms
  • growth efficiency
  • planting systems

Published Papers (6 papers)

2023

14 pages, 4352 KiB  
Article
Metamitron Thinning Efficacy of Apple Fruitlets Is Affected by Different Rates, Timings and Weather Factors in New York State
by Luis Gonzalez Nieto, Poliana Francescatto, Bruno Carra and Terence Lee Robinson
Horticulturae 2023, 9(11), 1179; https://doi.org/10.3390/horticulturae9111179 - 28 Oct 2023
Viewed by 847
Abstract
Precision chemical thinning is the most common method of thinning apple fruitlets because it requires little time and is cost-effective. The aims of the current study were I.- to investigate the effect of the application of metamitron at different rates on ‘Gala’ apples; [...] Read more.
Precision chemical thinning is the most common method of thinning apple fruitlets because it requires little time and is cost-effective. The aims of the current study were I.- to investigate the effect of the application of metamitron at different rates on ‘Gala’ apples; II.- to determine which fruit diameters were most sensitive to metamitron spray at several rates (between 180 and 500 ppm); and III- to identify the key environmental factors that explain Metamitron efficacy on a year-to-year basis. Eighteen trials were conducted over seven seasons, from 2015 to 2022 in ‘Gala’ apple orchards in Geneva (New York State). Metamitron was applied at different rates between 180 and 500 ppm, and the timing of the application was between petal fall (4.5 mm) and 18.5 mm fruit size. In each of the studies and years, the effect of meteorological parameters was evaluated. Our results suggest that a linear rate effect was observed in all trials, but that there were differences between the slopes of the regression every year because chemical thinning efficacy was variable year to year. The maximum metamitron efficacy was between 9.5 and 11 mm king fruit diameter; however, metamitron showed thinning efficacy at all phenological stages, from petal fall to 18.5 mm in ‘Gala’ apples. Our results suggest that the important meteorological factors affecting thinning efficacy were temperature and solar radiation on the day of application and for the next 6 days. The solar radiation after application of metamitron was the most important meteorological factor. Fruit drop caused by metamitron increased with low solar radiation. The minimum and maximum temperatures were also important factors in determining metamitron efficacy. A high minimum temperature (during the night) increased the fruit drop caused by metamitron and the maximum temperature during the day showed a negative correlation with the efficacy of metamitron. Full article
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15 pages, 3124 KiB  
Article
Foliar Mn and Zn Treatments Improve Apple Tree Nutrition and Help to Maintain Favorable Soil pH
by Andrei I. Kuzin, Natalia Ya. Kashirskaya, Alexei E. Solovchenko, Alexei V. Kushner, Anna M. Kochkina, Ludmila V. Stepantzova and Vyacheslav N. Krasin
Horticulturae 2023, 9(10), 1144; https://doi.org/10.3390/horticulturae9101144 - 18 Oct 2023
Cited by 2 | Viewed by 1079
Abstract
The foliar application of micronutrients can improve primary nutrient uptake. As a result, foliar treatments can reduce fertilizer application rates and help to maintain the natural health of soil. Here, we report on the tentative implementation of this approach in an apple orchard [...] Read more.
The foliar application of micronutrients can improve primary nutrient uptake. As a result, foliar treatments can reduce fertilizer application rates and help to maintain the natural health of soil. Here, we report on the tentative implementation of this approach in an apple orchard located in a temperate climate (JSC “Dubovoye” 52°36′57.1″ N 40°17′04.1″ E; planted in 2002 according to the 6 × 4 m or 417 trees ha–1 cultivar (cv.) Bogatyr grafted on B118 (Budagovskii 118). Manganese treatments augmented foliar nitrogen content and, in certain seasons, foliar phosphorus, whereas zinc treatments enhanced foliar potassium. Low-rate chemical fertilizers application (once in 5 years) on the background of initial high-rate organic fertilization (60 t ha–1 manure) allowed us to retain the optimal soil pH in the experimental orchard. Full article
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19 pages, 8029 KiB  
Article
Detection by Sensitive Real-Time Reverse Transcription Loop-Mediated Isothermal Amplification of Olive Leaf Yellowing Associated Virus and Its Incidence in Italy and Spain
by Andrea Giovanni Caruso, Sofia Bertacca, Arianna Ragona, Graziella Agrò, Maria Isabel Font-San-Ambrosio, Ana Alfaro-Fernández, Rocío Estévez Sánchez, Stefano Panno and Salvatore Davino
Horticulturae 2023, 9(6), 702; https://doi.org/10.3390/horticulturae9060702 - 15 Jun 2023
Cited by 2 | Viewed by 1300
Abstract
Olive trees (Olea europea L.) are constantly threatened by many viruses, such as the olive leaf yellowing-associated virus (OLYaV), that belong to the Olivavirus genus, family Closteroviridae. In this work, the OLYaV incidence in different regions of Italy and Spain, which [...] Read more.
Olive trees (Olea europea L.) are constantly threatened by many viruses, such as the olive leaf yellowing-associated virus (OLYaV), that belong to the Olivavirus genus, family Closteroviridae. In this work, the OLYaV incidence in different regions of Italy and Spain, which represent the two most important European areas for olive production, was evaluated through the development of a real-time reverse transcription-loop-mediated isothermal amplification (RT-LAMP) for reliable and sensitive OLYaV detection. The specificity and accuracy of the developed real-time RT-LAMP assay were determined; the assay showed that potential cross-reactivity with other viruses belonging to the Closteroviridae family was excluded. The LAMP assay detected OLYaV with a higher sensitivity than conventional end-point RT-PCR, detecting a total of 1.34 × 10−2 genome copies. A total of 80 and 120 plants of different olive cultivars from Spain (Comunitat Valenciana, Andalusia) and Italy (Sicily, Calabria, Apulia, Lazio, and Umbria) regions were tested, respectively. The percentage of infected plants was 46.25% and 30% for Spain and Italy, respectively, while the most susceptible cultivars were “Serrana Espadán” and “Villalonga” from Comunitat Valenciana and Andalusia regions (Spain) and “Ogliarola barese” from Apulia region (Italy). In addition, the survey demonstrated that the real-time RT-LAMP showed good sensitivity for OLYaV-positive sample detection, especially on asymptomatic olive trees. For this reason, the developed assay could be very suitable for phytopathological laboratories as a reliable and efficient method for a rapid and sensitive routine test on olive samples. Full article
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24 pages, 1937 KiB  
Article
Growing Degree Day Targets for Fruit Development of Australian Mango Cultivars
by Marcelo H. Amaral, Cameron McConchie, Geoffrey Dickinson and Kerry B. Walsh
Horticulturae 2023, 9(4), 489; https://doi.org/10.3390/horticulturae9040489 - 13 Apr 2023
Cited by 2 | Viewed by 1457
Abstract
A forward estimate of mango (Mangifera indica L.) harvest timing is required for farm management (e.g., for organization of harvest labour and marketing). This forward estimate can be based on accumulated growing degree days (GDD) from an early stage of flowering to [...] Read more.
A forward estimate of mango (Mangifera indica L.) harvest timing is required for farm management (e.g., for organization of harvest labour and marketing). This forward estimate can be based on accumulated growing degree days (GDD) from an early stage of flowering to fruit harvest maturity, with fruit maturity judged on a destructive assessment of flesh colour and dry matter content. The current study was undertaken to improve GDD targets for Australian mango cultivars, to improve estimation of harvest maturity, and to document a methodology recommended for future work characterizing fruit maturation GDD for other mango cultivars. An alternate algorithm on GDD calculation involving use of a function that penalizes high temperatures as well as low temperatures was demonstrated to better predict harvest maturity in warmer climates. Across multiple locations and seasons, the required heat units (GDD, Tb = 12 °C, TB = 32 °C; where TB is upper base temperature of 32 °C and Tb is lower base temperature of 12 °C) to achieve maturity from asparagus stage of flowering was documented as 2185, 1728, and 1740 for the cultivars Keitt, Calypso and Honey Gold, respectively. GDD difference between the asparagus and two-thirds floral opening stages of flowering was 188 ± 18 for Calypso, 184 ± 12 for Honey Gold, 238 ± 21 for Keitt and 175 ± 10 for KP. Colour specifications for a colour card set suitable for maturity assessment of all cultivars was also proposed. A flesh colour harvest maturity card specification of 9 was proposed for the cultivar Honey Gold and 13 for the cultivar Keitt. Full article
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36 pages, 5810 KiB  
Review
Technologies and Innovative Methods for Precision Viticulture: A Comprehensive Review
by Massimo Vincenzo Ferro and Pietro Catania
Horticulturae 2023, 9(3), 399; https://doi.org/10.3390/horticulturae9030399 - 19 Mar 2023
Cited by 5 | Viewed by 4064
Abstract
The potential of precision viticulture has been highlighted since the first studies performed in the context of viticulture, but especially in the last decade there have been excellent results have been achieved in terms of innovation and simple application. The deployment of new [...] Read more.
The potential of precision viticulture has been highlighted since the first studies performed in the context of viticulture, but especially in the last decade there have been excellent results have been achieved in terms of innovation and simple application. The deployment of new sensors for vineyard monitoring is set to increase in the coming years, enabling large amounts of information to be obtained. However, the large number of sensors developed and the great amount of data that can be collected are not always easy to manage, as it requires cross-sectoral expertise. The preliminary section of the review presents the scenario of precision viticulture, highlighting its potential and possible applications. This review illustrates the types of sensors and their operating principles. Remote platforms such as satellites, unmanned aerial vehicles (UAV) and proximal platforms are also presented. Some supervised and unsupervised algorithms used for object-based image segmentation and classification (OBIA) are then discussed, as well as a description of some vegetation indices (VI) used in viticulture. Photogrammetric algorithms for 3D canopy modelling using dense point clouds are illustrated. Finally, some machine learning and deep learning algorithms are illustrated for processing and interpreting big data to understand the vineyard agronomic and physiological status. This review shows that to perform accurate vineyard surveys and evaluations, it is important to select the appropriate sensor or platform, so the algorithms used in post-processing depend on the type of data collected. Several aspects discussed are fundamental to the understanding and implementation of vineyard variability monitoring techniques. However, it is evident that in the future, artificial intelligence and new equipment will become increasingly relevant for the detection and management of spatial variability through an autonomous approach. Full article
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17 pages, 9683 KiB  
Article
Evaluation of Multispectral Data Acquired from UAV Platform in Olive Orchard
by Pietro Catania, Eliseo Roma, Santo Orlando and Mariangela Vallone
Horticulturae 2023, 9(2), 133; https://doi.org/10.3390/horticulturae9020133 - 19 Jan 2023
Cited by 4 | Viewed by 1521
Abstract
Precision agriculture is a management strategy to improve resource efficiency, production, quality, profitability and sustainability of the crops. In recent years, olive tree management is increasingly focused on determining the correct health status of the plants in order to distribute the main resource [...] Read more.
Precision agriculture is a management strategy to improve resource efficiency, production, quality, profitability and sustainability of the crops. In recent years, olive tree management is increasingly focused on determining the correct health status of the plants in order to distribute the main resource using different technologies. In the olive grove, the focus is often on the use of multispectral information from UAVs (Unmanned Aerial Vehicle), but it is not known how important spectral and biometric information actually is for the agronomic management of the olive grove. The aim of this study was to investigate the ability of multispectral data acquired from a UAV platform to predict nutritional status, biometric characteristics, vegetative condition and production of olive orchard as tool to DSS. Data were collected on vegetative characteristics closely related to vigour such as trunk cross-sectional area (TCSA), Nitrogen concentration of the leaves, canopy area and canopy volume. The production was collected for each plant to create an accurate yield map. The flight was carried out with a UAV equipped with a multispectral camera, at an altitude of 50 m and with RTK correction. The flight made it possible to determine the biometric condition and the spectral features through the normalized difference vegetation index (NDVI). The NDVI map allowed to determine the canopy area. The Structure for Motion (SfM) algorithm allow to determine the 3D canopy volume. The experiment showed that the NDVI was able to determine with high accuracy the vegetative characteristic as canopy area (r = 0.87 ***), TCSA (r = 0.58 ***) and production (r = 0.63 ***). The vegetative parameters are closely correlated with the production, especially the canopy area (r = 0.75 ***). Data clustering showed that the production of individual plants is closely dependent on leaf nitrogen concentration and vigour status. Full article
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