<p>During the last decades, there has been a growing demand for wild edible vegetable consumption which are considered a staple of the Mediterranean diet for their high nutritional value (Petropoulos et al., 2018). Although the Mediterranean landscape hosts more than twenty wild edible vegetable species (such as <em>Crithmum maritimum</em>, <em>Cynara cardunculus</em> and <em>Taraxacum officinale</em>) which could be commercially cultivated, the cultivation process has not been sufficiently studied (Chatzigianni et al., 2019; Corr&#234;a et al., 2020; Papadimitriou et al., 2020). In this context, we examine the feasibility of soilless cultivation of the wild edible species <em>Scolymus hispanicus</em> L. (Asteraceae) in five substrates including perlite (PE), coir (CO), and three mixtures of perlite and coir at 3:1 (3P1C), 1:1 (1P1C) and 1:3 (1P3C) ratio, in two different containers (grow bag and pot container). Three <em>S. hispanicus</em> L. seedlings were transplanted per grow bag (24 L) and one seedling per plastic pot (8 L) resulting in 8 L of substrate for each plant and 12 plants per substrate. The plants were fertigated daily with a standard nutrient solution which was identical in all ten treatments of the experiment. Four months after transplant, yield characteristics of plants, including leaf number, leaf and tuberous root fresh weight [g] and rosette diameter [cm], were examined. Statistical analysis of the results demonstrates a significant increase in rosette diameter [cm], leaf and tuberous root fresh weight [g] in CO, 1P3C and 1P1C compared to those of 3P1C and PE substrates. Additionally, the use of grow bags significantly increased leaf number and leaf fresh weight [g] compared to those achieved with the use of pot containers, contrariwise pot significantly increased root fresh weight [g] compared to the growbag container. Based on these results, we conclude that an optimal hydroponic system should use mixture of Coir and Perlite substrate of 1:1 ratio in a grow bag container.</p> <p><strong>Reference</strong></p> <p>Chatzigianni, M., Ntatsi, G., Theodorou, M., Stamatakis, A., Livieratos, I., Rouphael, Y., Savvas, D., 2019. Functional Quality, Mineral Composition and Biomass Production in Hydroponic Spiny Chicory (Cichorium spinosum L.) Are Modulated Interactively by Ecotype, Salinity and Nitrogen Supply. Front. Plant Sci. 10, 1&#8211;14. https://doi.org/10.3389/fpls.2019.01040</p> <p>Corr&#234;a, R.C.G., Di Gioia, F., Ferreira, I.C.F.R., Petropoulos, S.A., 2020. Wild greens used in the Mediterranean diet, Second Edi. ed, The Mediterranean Diet. Elsevier Inc. https://doi.org/10.1016/b978-0-12-818649-7.00020-5</p> <p>Papadimitriou, D., Kontaxakis, E., Daliakopoulos, I., Manios, T., Savvas, D., 2020. Effect of N:K Ratio and Electrical Conductivity of Nutrient Solution on Growth and Yield of Hydroponically Grown Golden Thistle (Scolymus hispanicus L.). Proceedings 30, 87. https://doi.org/10.3390/proceedings2019030087</p> <p>Petropoulos, S.A., Karkanis, A., Martins, N., Ferreira, I.C.F.R., 2018. Edible halophytes of the Mediterranean basin: Potential candidates for novel food products. Trends Food Sci. Technol. 74, 69&#8211;84. https://doi.org/10.1016/j.tifs.2018.02.006</p>
<p>Fast and rigorous assessment of tree characteristics from earth observation products has many environmental applications, including monitoring of the canopy biomass available for pruning and utilisation as soil amendment or energy source. Here we explore the efficiency of three supervised classification algorithms in assessing canopy area of olive trees, the staple food crop of the Mediterranean that annually produces an estimated 2,82 &#924;t ha<sup>-1</sup> of residual biomass (Vel&#225;zquez-Mart&#237; et al., 2011) which is currently largely unexploited and often an environmental hazard due to on-site fires. The algorithms include (a) a thresholding algorithm (Daliakopoulos et al., 2009) processing Normalized Difference Vegetation Index values, (b) a supervised machine learning algorithm comprised on an Artificial Neural Network (ANN) with 4 hidden layers, and (c) the AdaBoost supervised deep learning algorithm. Following Yang et al. (2009), the latter two methods use image colour, texture, and entropy as inputs. Ground truth was developed by manually producing a binary mask where pixels depicting tree crown were marked with 1 and otherwise 0, and classification results were evaluated using the Dice similarity coefficient (DSC; Nisio et al., 2020). The three algorithms were tested on assessing olive tree crown projected surface area on a WorldView II image of resolution 0.5 &#215; 0.5 m of a rural area of Heraklion, Crete, Greece, acquired on November 10, 2020. Masking was performed in 42 olive tree plots including a total of 1,080 olive trees, including on-site visual validation of the masking results. Results show that the ANN performed better than AdaBoost and NDVI thresholding, scoring 81.98%, compared to 75.06 and 70.03%, respectively. The trained ANN is currently used to provide olive tree canopy estimates, used as input to assess canopy biomass available for pruning for the CompOlive system, an online platform that facilitates matchmaking of olive tree farms, olive mills, and mobile composting equipment, to optimise on-farm compost production and utilisation.</p> <p><strong>Acknowledgements</strong></p> <p>This research is co-financed by the European Union and Greek national funds through the Operational Program CRETE 2014-2020, under Project &#8220;CompOlive: Integrated System for the Exploitation of Olive Cultivation Byproducts Soil Amendments&#8221; (KPHP3-0028773).</p> <p><strong>References</strong></p> <p>Daliakopoulos, I. N., Grillakis, E. G., Koutroulis, A. G., & Tsanis, L. K. (2009). Tree Crown Detection on Multispectral VHR Satellite Imagery. <em>Photogrammetric Engineering and Remote Sensing</em>, <em>75</em>(10), 1201&#8211;1211. https://doi.org/10.14358/PERS.75.10.1201</p> <p>Vel&#225;zquez-Mart&#237;, B., Fern&#225;ndez-Gonz&#225;lez, E., L&#243;pez-Cort&#233;s, I., & Salazar-Hern&#225;ndez, D. M. (2011). Quantification of the residual biomass obtained from pruning of trees in Mediterranean olive groves. <em>Biomass and Bioenergy</em>, <em>35</em>(7), 3208&#8211;3217. https://doi.org/10.1016/J.BIOMBIOE.2011.04.042</p> <p>Yang, L., Wu, X., Praun, E., & Ma, X. (2009). Tree detection from aerial imagery. <em>GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems</em>, 131&#8211;137. https://doi.org/10.1145/1653771.1653792</p> <p>&#160;</p>
<p>Land degradation and desertification are considered major threats for the present and future of Mediterranean arid and semiarid agro-ecosystems (Daliakopoulos et al., 2017). Long-term anthropogenic pressure on forest and agricultural lands, combined with abiotic factors and the global trend of accelerated dryer climate and dryland expansion, create an uncertain and unstable living environment which has been demonstrated to increase poverty and force domestic and even cross-border migration. While our understanding and the flow of information about these threats is unprecedented, challenges persist and uptake of good practices by stakeholders is hindered by constraints and barriers both biophysical and socioeconomic (Daliakopoulos, 2022). For example, in one of the pioneer institutional initiatives aiming to enhance long-term forest resources and combat soil erosion and desertification by promoting forestry as an alternative form of land use, the Agricultural Land Afforestation (ALA) Program (Regulation 2080/92) introduced compensations for the income loss incurred during the non-productive period of afforested agricultural land. However, awareness about the Program by landowners, and the overall effectiveness of afforestation both in forestation success and in reducing soil erosion remains uncertain (Arabatzis et al., 2006; Nunes et al., 2011). In this context, the premise of the REACT4MED Project is that massive and effective land restoration actions need not only to make sense from an environmental point of view, but to also be socially acceptable, economically viable (Daliakopoulos & Keesstra, 2020), and have measurable impact, thus combining good practices with organic and inclusive transformation of all social actors. Here we present an overview of the effectiveness of the former ALA in the REACT4MED Pilot Area of Heraklion and outlines the supporting actions, both top down and bottom up, planned during the REACT4MED Project to increase the effectiveness of the forthcoming ALA Program by combining good practices with organic and inclusive transformation of all social actors.</p><p><strong>References</strong></p><p>Arabatzis, G., Christopoulou, O., & Soutsas, K. (2006). The EEC Regulation 2080/92 about forest measures in agriculture. <em>International Journal of Ecodynamics</em>, <em>1</em>(3), 245&#8211;257. https://doi.org/10.2495/ECO-V1-N3-245-257</p><p>Daliakopoulos, I. N. (2022). Sustainable Soil and Water Management for Combating Land Degradation and Desertification and Promoting Mediterranean Ecosystem Restoration: The REACT4MED Concept. <em>Third World Conference on the Revitalization of the Mediterranean Diet</em>, 28.</p><p>Daliakopoulos, I. N., & Keesstra, S. (2020). TERRAenVISION: Science for Society. Environmental issues today. <em>Science of the Total Environment</em>, <em>704</em>. https://doi.org/10.1016/j.scitotenv.2019.135238</p><p>Daliakopoulos, I. N., Panagea, I. S., Tsanis, I. K., Grillakis, M. G., Koutroulis, A. G., Hessel, R., Mayor, A. G., & Ritsema, C. J. (2017). Yield Response of Mediterranean Rangelands under a Changing Climate. <em>Land Degradation & Development</em>. https://doi.org/10.1002/ldr.2717</p><p>Nunes, A. N., de Almeida, A. C., & Coelho, C. O. A. (2011). Impacts of land use and cover type on runoff and soil erosion in a marginal area of Portugal. <em>Applied Geography</em>, <em>31</em>(2), 687&#8211;699. https://doi.org/10.1016/J.APGEOG.2010.12.006</p><p><strong>Acknowledgements</strong></p><p>This work has received funding from REACT4MED: Inclusive Outscaling of Agro-Ecosystem Restoration Actions for the Mediterranean. The REACT4MED Project (grant agreement 2122) is funded by PRIMA, a program supported by Horizon 2020.</p>
<p>Population rise and economic growth put additional pressure on global water resources, especially in the Mediterranean Island states that have a long history of aridity and water management challenges. In Crete, Greece, 81.2% of total water consumption is attributed to the agricultural sector, with olive trees covering 64.2% of the total cultivated land. Simulation and applied studies have shown that Irrigation Decision Support Systems (IDSS) can reduce water consumption from 10 (Fotia et al., 2021) to 34% (Phogat et al., 2014). Here we examine the feasibility of optimizing such a IDSS for deficit irrigation while maintaining olive crop yield. Experiments are conducted in the DRIP Project infrastructure (Daliakopoulos et al., 2020; Petousi et al., 2018) including an olive grove of 90 10 year-old trees and 5 20m3 lysimeters planted with olive trees from the same olive grove. The infrastructure includes a precision irrigation system comprised of FDR soil moisture sensors, microclimatic stations, and smart irrigation schedulers. The CROPWAT model (Smith et al., 2002) is calibrated using data from 5 irrigation treatments ranging from overirrigation to rainfed cultivation. Field measurements included stomatal conductance [mmol cm-2 s-1], relative chlorophyl fluorescence [Fv/Fm], leaf relative water content [%], leaf area [%], pruning weight [kg], and yield [kg]. Results clearly highlight the differences in olive tree physiological parameters in deficit irrigation treatments and the lack of significant yield benefit in over-irrigation, while the modeling study can estimate exact irrigation scheduling for incorporation with the IDSS.</p><p><strong>Acknowledgments</strong></p><p>This research has been co-financed by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH-CREATE-INNOVATE (project code: T1EDK-03372)</p><p><strong>References</strong></p><p>Daliakopoulos, I. &#925;., Papadimitriou, D., Matsoukas, T., Zotos, N., Moysiadis, H., Anastasopoulos, K., Mavrogiannis, I., & Manios, T. (2020). Development and Preliminary Results from the Testbed Infrastructure of the DRIP Project. Proceedings, 30(1), 64. https://doi.org/10.3390/proceedings2019030064</p><p>Doorenbos, J., & Pruitt, W. O. (1975). Guidelines for predicting crop water requirements. Irrigation and Drainage Paper.</p><p>Fotia, K., Mehmeti, A., Tsirogiannis, I., Nanos, G., Mamolos, A. P., Malamos, N., Barouchas, P., & Todorovic, M. (2021). Lca-based environmental performance of olive cultivation in northwestern greece: from rainfed to irrigated through conventional and smart crop management practices. Water (Switzerland), 13(14). https://doi.org/10.3390/w13141954</p><p>Petousi, I., Daliakopoulos, I. N., Matsoukas, T., Zotos, N., Mavrogiannis, I., & Manios, T. (2018). DRIP: Development of an Advanced Precision Drip Irrigation System for Tree Crops. TERRAENVISION Abstracts, 1, 2018&#8211;2. https://terraenvision2018.eu/abstracts/export.php?id=269</p><p>Phogat, V., Skewes, M. A., Cox, J. W., Sanderson, G., Alam, J., & &#352;im&#367;nek, J. (2014). Seasonal simulation of water, salinity and nitrate dynamics under drip irrigated mandarin (Citrus reticulata) and assessing management options for drainage and nitrate leaching. Journal of Hydrology, 513, 504&#8211;516. https://doi.org/10.1016/j.jhydrol.2014.04.008</p><p>Smith, M., Kivumbi, D., & Heng, L. K. (2002). Use of the FAO CROPWAT model in deficit irrigation studies. In Deficit irrigation practices.</p>
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