Evaluation of Over-The-Row Harvester Damage in a Super-High-Density Olive Orchard Using On-Board Sensing Techniques

New super-high-density (SHD) olive orchards designed for mechanical harvesting using over-the-row harvesters are becoming increasingly common around the world. Some studies regarding olive SHD harvesting have focused on the effective removal of the olive fruits; however, the energy applied to the canopy by the harvesting machine that can result in fruit damage, structural damage or extra stress on the trees has been little studied. Using conventional analyses, this study investigates the effects of different nominal speeds and beating frequencies on the removal efficiency and the potential for fruit damage, and it uses remote sensing to determine changes in the plant structures of two varieties of olive trees (‘Manzanilla Cacereña’ and ‘Manzanilla de Sevilla’) planted in SHD orchards harvested by an over-the-row harvester. ‘Manzanilla de Sevilla’ fruit was the least tolerant to damage, and for this variety, harvesting at the highest nominal speed led to the greatest percentage of fruits with cuts. Different vibration patterns were applied to the olive trees and were evaluated using triaxial accelerometers. The use of two light detection and ranging (LiDAR) sensing devices allowed us to evaluate structural changes in the studied olive trees. Before- and after-harvest measurements revealed significant differences in the LiDAR data analysis, particularly at the highest nominal speed. The results of this work show that the operating conditions of the harvester are key to minimising fruit damage and that a rapid estimate of the damage produced by an over-the-row harvester with contactless sensing could provide useful information for automatically adjusting the machine parameters in individual olive groves in the future.Ministerio de Economía y Competitividad AGL2013-46343-RJunta de Andalucía P12-AGR-122

Hints for Irrigation Management and Agroecological Approaches

Publisher Copyright: © 2023 by the authors.The production of olive oil in Portugal and other countries of the Mediterranean region has greatly increased in recent years. Intensification efforts have focused on the growth of the planted area, but also on the increase of the orchards density and the implementation of irrigation systems. Concerns about possible negative impacts of modern olive orchard production have arisen in the last years, questioning the trade-offs between the production benefits and the environmental costs. Therefore, it is of great importance to review the research progress made regarding agronomic options that preserve ecosystem services in high-density irrigated olive orchards. In this literature review, a keywords-based search of academic databases was performed using, as primary keywords, irrigated olive orchards, high density/intensive/hedgerow olive orchards/groves, irrigation strategies, and soil management. Aside from 42 general databases, disseminated research, and concept-framing publications, 112 specific studies were retrieved. The olive orchards were classified as either traditional (TD) (50–200 trees ha−1), medium-density (MD) (201–400 trees ha−1), high-density (HD) (401–1500 trees ha−1), or super-high-density (SHD) orchards (1501–2500 trees ha−1). For olive crops, the crop coefficient (Kc) ranges ranges from 0.65 to 0.70, and can fall as low as 0.45 in the summer without a significant decrease in oil productivity. Several studies have reported that intermediate irrigation levels linked with the adoption of deficit irrigation strategies, like regulated deficit irrigation (RDI) or partial rootzone drying (PRD), can be effective options. With irrigation, it is possible to implement agroecosystems with cover crops, non-tillage, and recycling of pruning residues. These practices reduce the soil erosion and nutrient leaching and improve the soil organic carbon by 2 to 3 t C ha−1 year−1. In this situation, in general, the biodiversity of plants and animals also increases. We expect that this work will provide a reference for research works and resource planning focused on the improvement of the productive and environmental performance of dense irrigated olive orchards, thereby contributing to the overall enhancement of the sustainability of these expanding agroecosystems.publishersversionpublishe

Sustainability of high-density olive orchards: Hints for irrigation management and agroecological approaches

The production of olive oil in Portugal and other countries of the Mediterranean region has greatly increased in recent years. Intensification efforts have focused on the growth of the planted area, but also on the increase of the orchards density and the implementation of irrigation systems. Concerns about possible negative impacts of modern olive orchard production have arisen in the last years, questioning the trade-offs between the production benefits and the environmental costs. Therefore, it is of great importance to review the research progress made regarding agronomic options that preserve ecosystem services in high-density irrigated olive orchards. In this literature review, a keywords-based search of academic databases was performed using, as primary keywords, irrigated olive orchards, high density/intensive/hedgerow olive orchards/groves, irrigation strategies, and soil management. Aside from 42 general databases, disseminated research, and concept-framing publications, 112 specific studies were retrieved. The olive orchards were classified as either traditional (TD) (50–200 trees ha−1), medium-density (MD) (201–400 trees ha−1), high-density (HD) (401–1500 trees ha−1), or super-high-density (SHD) orchards (1501–2500 trees ha−1). For olive crops, the crop coefficient (Kc) ranges ranges from 0.65 to 0.70, and can fall as low as 0.45 in the summer without a significant decrease in oil productivity. Several studies have reported that intermediate irrigation levels linked with the adoption of deficit irrigation strategies, like regulated deficit irrigation (RDI) or partial rootzone drying (PRD), can be effective options. With irrigation, it is possible to implement agroecosystems with cover crops, non-tillage, and recycling of pruning residues. These practices reduce the soil erosion and nutrient leaching and improve the soil organic carbon by 2 to 3 t C ha−1 year−1. In this situation, in general, the biodiversity of plants and animals also increases. We expect that this work will provide a reference for research works and resource planning focused on the improvement of the productive and environmental performance of dense irrigated olive orchards, thereby contributing to the overall enhancement of the sustainability of these expanding agroecosystems

New strategies for row-crop management based on cost-effective remote sensors

Agricultural technology can be an excellent antidote to resource scarcity. Its growth has led to the extensive study of spatial and temporal in-field variability. The challenge of accurate management has been addressed in recent years through the use of accurate high-cost measurement instruments by researchers. However, low rates of technological adoption by farmers motivate the development of alternative technologies based on affordable sensors, in order to improve the sustainability of agricultural biosystems. This doctoral thesis has as main objective the development and evaluation of systems based on affordable sensors, in order to address two of the main aspects affecting the producers: the need of an accurate plant water status characterization to perform a proper irrigation management and the precise weed control. To address the first objective, two data acquisition methodologies based on aerial platforms have been developed, seeking to compare the use of infrared thermometry and thermal imaging to determine the water status of two most relevant row-crops in the region, sugar beet and super high-density olive orchards. From the data obtained, the use of an airborne low-cost infrared sensor to determine the canopy temperature has been validated. Also the reliability of sugar beet canopy temperature as an indicator its of water status has been confirmed. The empirical development of the Crop Water Stress Index (CWSI) has also been carried out from aerial thermal imaging combined with infrared temperature sensors and ground measurements of factors such as water potential or stomatal conductance, validating its usefulness as an indicator of water status in super high-density olive orchards. To contribute to the development of precise weed control systems, a system for detecting tomato plants and measuring the space between them has been developed, aiming to perform intra-row treatments in a localized and precise way. To this end, low cost optical sensors have been used and compared with a commercial LiDAR laser scanner. Correct detection results close to 95% show that the implementation of these sensors can lead to promising advances in the automation of weed control. The micro-level field data collected from the evaluated affordable sensors can help farmers to target operations precisely before plant stress sets in or weeds infestation occurs, paving the path to increase the adoption of Precision Agriculture techniques

Using a GIS technology to plan an agroforestry sustainable system in Sardinia

This study was conducted with the aim to quantify the spread of livestock agroforestry in a Mediterranean ecosystem (island of Sardinia, Italy) and evaluate its sustainability in terms of grazing impact. By using GIS software ArcMap 10.2.2, the map of Sardinia vegetal landscape, obtained by information of Sardinia nature map based on the classification of habitat according to CORINE-Biotopes system, have been overplayed with the map of livestock grazing impact map CAIA developed by INTREGA (spin-off ENEA), to obtain for Meriagos (local agro-silvo-pastoral systems; classified “Dehesa 84.6” according to CORINE-Biotopes system), bushlands and woodlands, the surfaces under grazing and evaluate the extension of overgrazing for each of them

Quantifying the potential of almond production in the Western Cape for future extension and high-density plantings in suitable climatic regions

Thesis (MScAgric)--Stellenbosch University, 2022.ENGLISH ABSTRACT: Almond (Prunus amygdalus Batsch) has become popular as an alternative crop with South African growers as the need for marginal crops in the Western Cape increases. Growers are also seeking more efficient and sustainable production methods that will reduce inputs to remain globally competitive. High-density plantings proved to be more profitable in commercial crops like peach and nectarine than traditional low-density plantings, but proper canopy management and manipulations are required to maintain the efficiency of these systems. The aim of this study was to assess different spacing and training configurations with respect to maximizing future reproductive potential, for two commercial cultivars. The canopy development and performance of two newly established super- high-density (SHD) (2049 trees.ha -1) training systems in the Robertson region were evaluated for the Soleta cultivar on ‘Garnem’ rootstock. The study focused on the relationship between light interception (LI) and potential yield efficiency, as the orchard was in a vegetative phase during the first two seasons. The Open-Vase (OV) system showed more vigorous growth patterns than Bi-Axis (BA), resulting in a significantly higher stem circumference (in all three seasons), shoot growth and canopy volume (CV) after summer pruning (2020/21) and LI during full bloom (2020/21;2021/22). The OV had a significantly higher trunk cross-sectional area (TCSA), which translated into the significantly higher yield efficiency in the BA system, in 2020/21. The OV had a significantly higher in-shell and kernel weight, -length and -width. Initial results indicated that both systems are suitable for ‘Soleta’ at SHD, but the BA system outperformed the OV system with regard to yield efficiency at the first commercial harvest (three years after establishment). The effect of two alternative rootstocks, ‘Viking’ and ‘Flordaguard’, on the vegetative development of ‘Nonpareil’, was evaluated in the Durbanville region. Rootstock did not influence the stem circumference or the average annual shoot growth during the two consecutive seasons. However, rootstock affected CV, after shoot growth cessation, and LI, after leaf drop. ‘Nonpareil’ trees on ‘Flordaguard’ had a significantly higher CV and LI than trees on ‘Viking’, which indicated that ‘Flordaguard’ resulted in more vigorous growth of the ‘Nonpareil’ scion than ‘Viking’. Almond cultivation at higher densities is a relatively new concept than the historical, traditional systems currently under production. A financial comparison was conducted on the performance of the Soleta (more compact, self-fertilising) and Nonpareil (vigorous, self-infertile) cultivars in the Durbanville, Robertson and Montagu regions, planted in different orchard systems, with varying planting densities and training systems. For each system, the net present value (NPV) and modified internal rate of return (MIRR) were calculated. The NPV at a discount rate of 5% and 10% indicate that the low-density system is preferred for both cultivars. A sensitivity analysis was performed on the year that full production is achieved, as well as on the orchard's life expectancy. With the exception of the MIRR, which increased by 1% for a two-year decrease in the life expectancy of low-density orchard systems, both factors had a negative impact on the NPV and a negative or no impact on the MIRR.AFRIKAANSE OPSOMMING: Die gewildheid van die amandel (Prunus amygdalus Batsch) het toegeneem onder Suid-Afrikaanse produsente weens die behoefte aan beter alternatiewe gewasse in die Weskaap. Produsente soek ook meer doeltreffende en volhoubare produksiemetodes wat insette sal verminder om wêreldwyd mededingend te bly. Hoë- digtheid aanplantings blyk om meer winsgewend te wees in kommersiële gewasse soos perske en nektarien as tradisionele lae-digtheid aanplantings, maar gepaste blaardakbestuur en manipulasies is nodig om die doeltreffendheid van hierdie stelsels te handhaaf. Die doel van hierdie studie was om verskillende spasiëring en opleistelsels vir twee kommersiële kultivars te assesseer om toekomstige opbrengs potensiaal te maksimeer. Die Soleta kultivar se blaardakontwikkeling en prestasie in twee nuut gevestigde super-hoë-dighteid (2049 bome.ha -1) opleistelsels in die Robertson area is geëvalueer. Die studie het gefokus op die verhouding tussen ligonderskepping en potensiële opbrengsdoeltreffendheid, aangesien die boord gedurende die eerste twee seisoene in 'n vegetatiewe fase was. Die oopkelk (OK) stelsel het sterker groeipatrone getoon, wat gelei het tot 'n betekenisvolle hoër stamomtrek (in al drie seisoene), lootgroei en blaardakvolume na somersnoei (2020/21) en ligonderskepping tydens volblom (2020/21;2021/22). Die OK het 'n betekenisvolle hoër stamomtrek area gehad, wat gelei het tot die betekenisvolle hoër opbrengsdoeltreffendheid in die twee- as (TA) stelsel in 2020/21. Die OK het 'n betekenisvolle hoër in-dop- en neut gewig, - lengte en -breedte gehad. Aanvanklike resultate het aangedui dat beide stelsels geskik is vir 'Soleta' in super-hoë-dighteid, maar die TA stelsel het beter gevaar as die OK stelsel met betrekking tot opbrengsdoeltreffendheid in die eerste kommersiële oes (drie jaar na vestiging). Die effek van twee alternatiwe onderstamme, 'Viking' en 'Flordaguard', op die vegetatiewe ontwikkeling van 'Nonpareil', is in die Durbanville area geëvalueer. Die onderstam het nie die stamomtrek of die gemiddelde jaarlikse lootgroei gedurende die twee opeenvolgende seisoene beïnvloed nie. Die onderstam het wel blaardakvolume na die voltooiing van lootgroei beïnvloed, asook die ligonderskepping, na blaarval. 'Nonpareil' bome op 'Flordaguard' het 'n betekenisvolle hoër blaardakvolume en ligonderskepping as bome op 'Viking' gehad, wat aangedui het dat 'Flordaguard' tot ‘n meer groeikragtige 'Nonpareil' bostam gelei het as 'Viking'. Amandelverbouing teen hoër digthede is 'n relatief nuwe konsep teenoor die historiese, tradisionele stelsels wat tans gebruik word. ’n Finansiële vergelyking is getref tussen die prestasie van die Soleta (meer kompak, self-bestuiwende) en Nonpareil (kragtige, kruis-bestuiwende) kultivars in die Durbanville-, Robertson- en Montagu-streke, geplant in verskillende boordstelsels, met verskillende plantafstande en opleistelsels. Vir elke stelsel is die netto huidige waarde (NHW) en aangepaste interne opbrengskoers (AIOK) bereken. Die NHW teen 'n verdiskonteringskoers van 5% en 10% het aangedui dat die lae-digtheid stelsel vir beide kultivars verkies word. ’n Sensitiwiteits analise is uitgevoer vir die jaar wat voldrag behaal word, asook vir die boord se lewensverwagting. Met die uitsondering van die AIOK, wat met 1% toegeneem het vir 'n twee-jaar afname in die lewensverwagting van lae-digtheid boordstelsels, het beide faktore 'n negatiewe impak op die NHW en 'n negatiewe of geen impak op die AIOK gehad.Master

Comparison of SHD and open-center training systems in Almond Tree Orchards cv. ‘Soleta’

The increase in the demand for almonds, the development of novel self-fertile and late-flowering varieties, and the establishment of plantations in new irrigated areas have led to significant progress in the productive techniques of almond tree cultivation. One of the most important has been the increase in planting density, due to the development of dwarfing rootstocks. This paper presents a comparison between two training systems with ‘Soleta’ almond cultivar: a super high density (SHD) system using Rootpac-20 dwarfing rootstock versus an open-center training system using GF-677 rootstock. To this end, several parameters related to chlorophyll content (fluorescence and SPAD) and light interception (from photosynthetically active radiation (PAR) measurements) were monitored throughout two vegetative cycles, and other productive conditions (flowering, fruit set and production) were tracked at specific times of the cycle. The open-center system resulted in higher PAR interception than the SHD system, but also in the presence of poorly illuminated fractions of the canopy. Differences were observed between both systems in terms of average fruit weight and yield per canopy volume. Lower yields were obtained in SHD system than in open-center, which may be significantly increased by adapting the inter-row spacing. However, the degree of efficiency in the use of resources or productive inputs, such as irrigation, was favorable to the new SHD training system, so its potential to become a reference system in modern plantations (using over-the-row harvesters similar to those used for vine and olive trees) seems promising

AI Knowledge Transfer from the University to Society

AI Knowledge Transfer from the University to Society: Applications in High-Impact Sectors brings together examples from the "Innovative Ecosystem with Artificial Intelligence for Andalusia 2025" project at the University of Seville, a series of sub-projects composed of research groups and different institutions or companies that explore the use of Artificial Intelligence in a variety of high-impact sectors to lead innovation and assist in decision-making. Key Features Includes chapters on health and social welfare, transportation, digital economy, energy efficiency and sustainability, agro-industry, and tourism Great diversity of authors, expert in varied sectors, belonging to powerful research groups from the University of Seville with proven experience in the transfer of knowledge to the productive sector and agents attached to the Andalucía TECH Campu

Orchard mapping and mobile robot localisation using on-board camera and laser scanner data fusion

Agricultural mobile robots have great potential to effectively implement different agricultural tasks. They can save human labour costs, avoid the need for people having to perform risky operations and increase productivity. Automation and advanced sensing technologies can provide up-to-date information that helps farmers in orchard management. Data collected from on-board sensors on a mobile robot provide information that can help the farmer detect tree or fruit diseases or damage, measure tree canopy volume and monitor fruit development. In orchards, trees are natural landmarks providing suitable cues for mobile robot localisation and navigation as trees are nominally planted in straight and parallel rows. This thesis presents a novel tree trunk detection algorithm that detects trees and discriminates between trees and non-tree objects in the orchard using a camera and 2D laser scanner data fusion. A local orchard map of the individual trees was developed allowing the mobile robot to navigate to a specific tree in the orchard to perform a specific task such as tree inspection. Furthermore, this thesis presents a localisation algorithm that does not rely on GPS positions and depends only on the on-board sensors of the mobile robot without adding any artificial landmarks, respective tapes or tags to the trees. The novel tree trunk detection algorithm combined the features extracted from a low cost camera's images and 2D laser scanner data to increase the robustness of the detection. The developed algorithm used a new method to detect the edge points and determine the width of the tree trunks and non-tree objects from the laser scan data. Then a projection of the edge points from the laser scanner coordinates to the image plane was implemented to construct a region of interest with the required features for tree trunk colour and edge detection. The camera images were used to verify the colour and the parallel edges of the tree trunks and non-tree objects. The algorithm automatically adjusted the colour detection parameters after each test which was shown to increase the detection accuracy. The orchard map was constructed based on tree trunk detection and consisted of the 2D positions of the individual trees and non-tree objects. The map of the individual trees was used as an a priority map for mobile robot localisation. A data fusion algorithm based on an Extended Kalman filter was used for pose estimation of the mobile robot in different paths (midway between rows, close to the rows and moving around trees in the row) and different turns (semi-circle and right angle turns) required for tree inspection tasks. The 2D positions of the individual trees were used in the correction step of the Extended Kalman filter to enhance localisation accuracy. Experimental tests were conducted in a simulated environment and a real orchard to evaluate the performance of the developed algorithms. The tree trunk detection algorithm was evaluated under two broad illumination conditions (sunny and cloudy). The algorithm was able to detect the tree trunks (regular and thin tree trunks) and discriminate between trees and non-tree objects with a detection accuracy of 97% showing that the fusion of both vision and 2D laser scanner technologies produced robust tree trunk detection. The mapping method successfully localised all the trees and non-tree objects of the tested tree rows in the orchard environment. The mapping results indicated that the constructed map can be reliably used for mobile robot localisation and navigation. The localisation algorithm was evaluated against the logged RTK-GPS positions for different paths and headland turns. The average of the RMS of the position error in x, y coordinates and Euclidean distance were 0.08 m, 0.07 m and 0.103 m respectively, whilst the average of the RMS of the heading error was 3:32°. These results were considered acceptable while driving along the rows and when executing headland turns for the target application of autonomous mobile robot navigation and tree inspection tasks in orchards