Multispectral AI-driven imaging for detection of downy mildew and gray mold in grapevines Dimitrios Kapetas, Panagiotis Christakakis, Ioannis Naounoulis, Ioannis Vagelas, Sofia Faliagka, Eleftheria Maria Pechlivani, Nikolaos Katsoulas Smart Agricultural Technology, 2026 • Dual-head SegFormer enables robust grape disease segmentation • Multispectral and depth data improve disease detection accuracy • YOLO-derived masks boost leaf segmentation IoU by over 11% • 15-channel fusion enhances pixel-level classification performance • Framework supports UAV and robotic precision agriculture systems Downy mildew ( Plasmopara viticola ) and gray mold ( Botrytis cinerea ) are among the most destructive grapevine diseases worldwide, causing substantial yield losses and compromising fruit quality. Traditional diagnostic methods based on visual assessment and microscopic examination are time-consuming, labor-intensive, and require considerable expertise. This study presents a novel computer vision approach for automated grape disease detection by combining instance and semantic segmentation techniques on multispectral imagery. A dataset of 451 captures comprising RGB and five-band multispectral images (460, 540, 640, 780, 880 nm) was collected from open-field vineyards, including healthy, gray mold–symptomatic, and downy mildew–symptomatic leaves. Two complementary approaches were developed: (i) a YOLOv11-based instance segmentation model for rapid leaf identification, and (ii) a dual-head SegFormer architecture for semantic segmentation incorporating 15 input channels, including RGB, multispectral bands, derived vegetation indices, YOLO-generated masks, and depth information. The dual-head SegFormer includes a primary multiclass segmentation head and a secondary binary head for leaf–background discrimination, with consistency regularization between heads to enhance performance. The YOLOv11 model achieved 89.7% mAP50 for leaf segmentation. The SegFormer-based model achieved an overall mean IoU of 75.22%, an F1-Score of 83.53% and a single-class leaf segmentation IoU of 91.79%. Disease-specific segmentation performance was high, with gray mold achieving 94.32% IoU and an F1-score of 97.08%, while downy mildew achieved 75.5% IoU and an F1-score of 86.04%. The integration of multispectral channels and derived indices improved mean IoU by 3–5%, while the inclusion of YOLO-derived masks and depth information from the Depth Anything V2 model increased single-class IoU by more than 11%. The proposed framework demonstrates strong capability for disease-specific detection and is well suited for UAV- and ground robotics–based precision agriculture applications.
Adaptation of the VegSyst model to predict crop nutrient uptake and water needs for precise soilless crop fertigation in greenhouses Sofia Faliagka, Ioannis Naounoulis, Marisa Gallardo, Nikolaos Katsoulas Irrigation Science, 2026 Precision fertigation involves the precise application of water and fertilisers at optimal doses and frequencies, tailored to the weekly needs of the crops. In the present study, the existing VegSyst model was (i) adapted for soilless crop fertigation and (ii) validated for dry matter production (DMP) and uptake of macronutrients N, P, K and Ca in cucumber and tomato crops. The adaptation consisted of applying the VegSyst model together with climate forecast and a greenhouse climate model to predict the dry matter production of the greenhouse crop, and subsequently apply a simplified version of the Penman-Monteith (P–M) equation to predict the crop irrigation requirements, enabling nutrient requirements to be tailored to expected weather conditions. To validate the performance of the model, three experiments were conducted in a soilless greenhouse, cultivating cucumber and tomato crops. Two fertigation treatments were employed: (a) a conventional approach, reflecting the prevailing regional practice, where plants received a nearly constant nutrient concentration throughout the cultivation period, and (b) an improved approach adjusting nutrient concentrations on a weekly basis based on weather predictions and the predicted crop nutrient uptake. The primary objective of the model is to support its integration into a decision support system, providing greenhouse farmers with a tailored nutrient recipe aligned with crop requirements. This integration aims to mitigate water and nutrient waste in agriculture. Notably, in real-case scenarios, deploying the model led to a remarkable increase in agronomic efficiency. Simultaneously, there was a reduction in nitrate and phosphate leaching in the cucumber trials (up to 22% and 40%, respectively), without compromising overall productivity.
AI-Based Potato Crop Abiotic Stress Detection via Instance Segmentation Emmanouil Savvakis, Dimitrios Kapetas, María del Carmen Martínez-Ballesta, Nikolaos Katsoulas, Eleftheria Maria Pechlivani AI Switzerland, 2026 Background: Automated monitoring of crop health and the precise detection of abiotic stress, such as herbicide damage, are demanding challenges for modern agriculture. Abiotic stresses are a demanding challenge for modern agriculture, responsible for up to 82% of yield losses in major food crops. To address this, researchers are increasingly leveraging artificial intelligence (AI) to automate the detection and management of these stressors. Methods: In particular, this paper presents an instance segmentation framework to precisely detect interveinal chlorosis and leaf curling on potato leaves, two common symptoms of herbicide damage and soft wind. Within the context of precision agriculture and the need to address the inherent ambiguity in manual leaf assessment, this study employs a partial label learning approach to refine the dataset. This method utilizes an EfficientNet-b1 model to classify ambiguous samples, generating high-confidence pseudo-labels for instances that are difficult to categorize visually. The core of the proposed framework is a Mask2Former model, which is first fine-tuned on general potato leaf dataset to enhance its segmentation capabilities and then transferred on the refined, pseudo-labeled dataset. Results & Conclusions: This two-stage approach yields a highly accurate segmentation tool, achieving 89% mAP50 and a pseudo-label classification accuracy of 95%, designed for integration into smart agriculture systems like ground level robotics or unmanned aerial vehicles for real-time, automated crop monitoring.
Assessment of Future Water Stress of Winter Wheat and Olive Trees in Greece Using High-Resolution Climate Model Projections Angeliki Elvanidi, Persefoni Maletsika, Nikolaos Katsoulas, Giorgos Papadopoulos, Dimitrios Melas, Kostas Douvis, Ioannis Faraslis, Stavros Keppas, Ioannis Stergiou, Anastasia Poupkou, Dimitrios Voloudakis, John Kapsomenakis, Dimitris K. Papanastasiou Agronomy, 2026 Climate change is expected to increasingly intensify the water stress that directly impacts crop productivity in the near future. This study integrates the crop water stress index (CWSI) with high-resolution regional climate simulations produced by the weather research and forecasting (WRF) model to evaluate water stress that winter wheat and olive trees will potentially experience in Greece in the future. Decadal, high-resolution climate simulations were generated for both the present and near-future periods using the most recent shared socioeconomic pathways (SSP) framework. A bias-corrected dataset based on 18 models from the Coupled Model Intercomparison Project 6 was used for boundary conditions to mitigate errors associated with individual global model biases. Projections indicated a mean air temperature increase of 1.1–1.7 °C and a relative humidity decrease of up to 3.5%. Mean CWSI increases of up to 6% and 4% were projected in most of the country for winter wheat and olive trees, respectively. The water stress of the winter wheat was also assessed over the three growing stages defined by the FAO. The analysis showed that water stress may occur during all growing stages, inducing potential impacts on tillering, photosynthetic efficiency, biomass accumulation, or yield. Additionally, a water stress threshold (i.e., CWSI > 0.5) was applied for both species in order to carry out a spatial assessment of the water stress that is projected to occur in the future in key winter wheat-, olive oil- and table olive-producing Greek regions. The findings of this study can support the irrigation scheduling and the development of climate-resilient agricultural practices in Greece. The modeling framework that was established in this study can also be applied to other crops and regions in the Mediterranean.
Evaluation of a Three-Level Cascade Soilless System Under Saline Greenhouse Conditions Eleni Karatsivou, Angeliki Elvanidi, Nikolaos Katsoulas Horticulturae, 2025 A three-level cascade hydroponic system was designed to enhance resource efficiency by reusing drainage solutions across sequential crops: tomato (primary-donor crop), herbs (mint, peppermint; secondary receivers from primary), and halophytes (lemon balm, sea fennel; tertiary receivers from secondary). The aim was to address salinity, a common challenge in hydroponics limiting plant growth and resource use. Two fertigation strategies were applied to secondary and tertiary crops to simulate salinity, with electrical conductivity (EC) increasing weekly by 1 dS m−1 to reach 9 dS m−1 for secondary and 11 dS m−1 for tertiary crops. Control (S1) used fresh nutrient solution (FS), while the recycling treatment (S2) used tomato drainage with added NaCl. For tertiary crops, the control (S3) received a salinity-enriched FS, and the recycling treatment (S4) reused 70% of secondary crop drainage combined with 30% of its own, plus NaCl to reach target EC. Under moderate salinity (9 dS m−1), mint produced 2.5 kg m−2, whereas lemon balm dropped 16.7%, showing sensitivity; peppermint was more tolerant. Sea fennel showed resilience under high salinity (11 dS m−1), with high chlorophyll (97.2) and improved ion uptake. The system reduced nutrient and fertilizer use by 86–88%, highlighting potential for sustainable nutrient recycling and efficient crop production.
Sustainable greenhouse microclimate modeling: A comparative analysis of recurrent and Graph Neural Networks Emiliano Seri, Marcello Petitta, Chryssoula Papaioannou, Nikolaos Katsoulas, Cristina Cornaro Building and Environment, 2025 The integration of photovoltaic (PV) systems into greenhouses not only optimizes land use but also enhances sustainable agricultural practices by enabling dual benefits of food production and renewable energy generation. However, accurate prediction of internal temperature is crucial to ensure optimal crop growth while maximizing energy production. This study introduces a novel application of Spatio-Temporal Graph Neural Networks (STGNNs) to greenhouse microclimate modeling, comparing their performance with traditional Recurrent Neural Networks (RNNs). While RNNs excel at temporal pattern recognition, they cannot explicitly model directional relationships between environmental variables. Our STGNN approach addresses this limitation by representing these relationships as directed graphs, enabling the model to capture both environmental dependencies and their directionality. We benchmark RNNs against directed STGNNs on two 15-min resolution datasets from Volos (Greece): a four-variable, driver-response campaign (2020) and an eight-variable, feedback-rich campaign (2024) that adds PAR and CO 2 . In the 2020 case the RNN attains near-perfect accuracy, outperforming the STGNN. When additional drivers are available in 2024, the STGNN overtakes the RNN ( R 2 = 0 . 905 vs 0.740), demonstrating that explicitly modelling directional dependencies becomes critical as interaction complexity grows. These findings indicate that graph-based models become worthwhile when new sensors create cross-links that a sequence model cannot untangle. This insight helps practitioners balance model complexity against instrumentation cost and supplies a fast empirical core for real-time digital twins that jointly optimise crop yield and PV yield in agrivoltaic houses. • Compare RNN and directed STGNN for greenhouse temperature prediction. • RNN already saturates accuracy in 4-variable “weather-only” 2020 data. • Adding PAR and CO 2 lifts STGNN test R 2 from 0.74 to 0.905. • Results pinpoint the tipping-point where graph models beat sequence nets. • Insights guide sensor investment and enable real-time digital-twin control.
Projected Heat-Stress in Sheep and Cattle in Greece Under Future Climate Change Scenarios Dimitris K. Papanastasiou, Athanasios I. Gelasakis, Giorgos Papadopoulos, Dimitrios Melas, Kostas Douvis, Ioannis Faraslis, Stavros Keppas, Ioannis Stergiou, Anastasia Poupkou, Dimitris Voloudakis, Athena Progiou, John Kapsomenakis, Nikolaos Katsoulas Agriculture Switzerland, 2025 It is well established that exposure to heat-stress conditions significantly impacts the physiology, health, welfare, and productivity of both sheep and cattle. The aim of this study was to apply the Temperature Humidity Index (THI) in order to assess the impact of future climate conditions on the thermal stress exposure of sheep and cattle in Greece. The Weather Research and Forecasting (WRF) model was used as a high-resolution regional climate model to simulate climate conditions for two decades in Greece at a 10 Km spatial resolution and a 1 h temporal resolution. The WRF model was applied to two emission scenarios, namely SSP2-4.5 (intermediate) and SSP5-8.5 (worst-case). Projections were made for the near-future decade (2046–2055), with the decade (2005–2014) serving as the reference period for comparative analysis. The data analysis indicated that under the SSP2-4.5 emission scenario, the mean temperature is projected to increase by 1.2–1.4 °C and 1.4–1.6 °C across 38% and 58% of the country’s territory, respectively. Increases higher than 1.6 °C are projected across 32% of the Greek territory under the SSP5-8.5 emission scenario. The mean THI (sheep) and mean THI (adj) (cattle) are projected to increase by 5–10% and by 4% across 74% and 82% of the Greek territory, respectively, when considering the SSP2-4.5 emission scenario. Slightly more severe mean heat-stress conditions were projected when considering the SSP5-8.5 emission scenario. The analysis of the hourly THI values showed that sheep and cattle are expected to experience heat-stress conditions during extended periods in the future, in which hot weather will prevail. Specifically, the number of severe/danger heat-stress hours is projected to double in the greater part of the country. To mitigate the adverse effects of climate-change-induced thermal stress on animal productivity, health, and welfare, the implementation of adaptation measures and best management practices is strongly recommended for sheep and cattle farmers. These measures encompass improvements in breeding strategies, livestock housing and microclimate management, nutritional interventions, and the adoption of precision livestock farming technologies. Given the outstanding economic, social, and environmental importance of sheep and cattle farming in Greece, effective adaptation to and mitigation of climate change impacts represent urgent priorities to ensure the long-term sustainability and resilience of the livestock sector.
Capturing the physiological and growth dynamics of cucumber cultivated in coupled and decoupled aquaponic systems Anastasia Mourantian, Maria Aslanidou, Eleni Mente, Nikolaos Katsoulas, Efi Levizou Scientia Horticulturae, 2025 • Nutrient dynamics play key-role in cucumber physiology/growth responses in coupled system. • Low K, P and Zn of leaves in coupled system synergistically account for stunted growth. • Adequate leaf N and Fe in coupled aquaponics sustain high photosynthetic performance. • Decoupled aquaponics resulted in comparable features to hydroponics in all evaluated parameters. • Decoupled aquaponics appear to address all the drawbacks associated with coupled systems. Decoupled aquaponics, an emerging area of research, has garnered interest due to its potential in overcoming the constraints identified in coupled (one-loop) aquaponics systems, thereby enhancing crop productivity. The present study employs a physiological approach to elucidate the mechanisms underlying the growth responses of cucumber in both coupled (CAP) and decoupled (DCAP) aquaponics systems, in comparison to conventional hydroponics (HP). A 90-day experiment was conducted in a pilot-scale aquaponics greenhouse, where detailed and regular measurements of various physiological and growth parameters were taken to capture their dynamics. Additionally, fruit quality parameters were assessed to complete the evaluation of the tested cropping systems. CAP plants exhibited stunted growth in terms of aerial biomass accumulation and leaf area, while anatomical features such as leaf thickness and leaf specific mass were significantly higher than those observed in HP and DCAP plants. However, the photosynthetic performance, the light use efficiency, and the photosynthetic pigments concentration were comparable among treatments. The leaf elemental analysis revealed that adequate N and Fe concentrations supported high photosynthetic rates, however, the reduced K, P and Zn levels influenced the growth profile of CAP plants. DCAP demonstrated comparable performance to HP in almost all the evaluated characteristics. Collectively, the results indicate that DCAP addressed limitations associated with coupled systems, indicating its significant potential to support the transition of conventional hydroponics towards a more sustainable cropping system.
Cascade Hydroponics as a Means to Increase the Sustainability of Cropping Systems: Evaluation of Functional, Growth, and Fruit Quality Traits of Melons Zoe Karachaliou, Ioannis Naounoulis, Nikolaos Katsoulas, Efi Levizou Sustainability Switzerland, 2025 The necessity of optimizing the nutrient and water efficiency in conventional hydroponics and enhancing their sustainability has given rise to the concept of cascade cropping systems. These achieve high water and resource use efficiencies, together with a lower environmental footprint, which is especially important for Mediterranean areas. However, scientific questions about the mechanisms that drive productivity in this system remain to be answered. This study aimed at a comprehensive evaluation of crop performance in cascade systems in terms of morphoanatomical and functional responses, also including product quality parameters, which influence the marketability of the fruit. In a three-month experiment, the dynamics of melon’s photosynthetic light use efficiency, pigment contents, growth parameters, and leaf compactness were assessed in a cascade system using drainage of tomato cultivation in comparison to classic hydroponic melon. The fruits’ chroma, hardness, total soluble solids, and pH were also measured. Comparable plant functional responses in the control and cascade melon plants resulted in similar growth and morphoanatomical traits. The fruit quality attributes were also found to be almost identical. It is proposed that the cascade system is both effective and sustainable in regions facing climatic and water scarcity pressures, such as those that are prevalent around the Mediterranean basin.
Farmers concerns in relation to organic livestock production Carmen L. Manuelian, Sophie Valleix, Héloïse Bugaut, Birgit Fuerst-Waltl, Luciana da Costa, Sara Burbi, Ulrich Schmutz, Adrian Evans, Nikolaos Katsoulas, Sofia Faliagka, Uygun Aksoy, Özge Çiçekli, Danuta Dróżdż, Krystyna Malińska, Lindsay Whistance, Marion Johnson, Lucas Knebl, Federico Righi, Massimo De Marchi Italian Journal of Animal Science, 2023
Remote sensing for crop water stress detection in greenhouses T. Bartzanas, N. Katsoulas, A. Elvanidi, K.P. Ferentinos, C. Kittas Precision Agriculture 2015 Papers Presented at the 10th European Conference on Precision Agriculture Ecpa 2015, 2015
Measurements and simulation of microclimatic effects of a horizontal hydroponic pergola Ceur Workshop Proceedings, 2015
Relationships between reflectance and water status in a greenhouse rocket (Eruca sativa Mill.) cultivation European Journal of Horticultural Science, 2013
Minimizing environmental impact from applying selected inputs in plant production Environmental Management Systems Sustainability and Current Issues, 2012
Shading effects on greenhouse microclimate and crop transpiration in a cucumber crop grown under mediterranean conditions Applied Engineering in Agriculture, 2012
Greenhouse microclimate and soilless pepper crop production and quality as affected by a fog evaporative cooling system Transactions of the Asabe, 2007
Influence of an aluminized thermal screen on greenhouse microclimate and canopy energy balance Transactions of the American Society of Agricultural Engineers, 2003
Adaptation of the VegSyst model to predict crop nutrient uptake and water needs for precise soilless crop fertigation in greenhouses S Faliagka, I Naounoulis, M Gallardo, N Katsoulas Irrigation Science 44 (3), 66 , 2026 2026
AI-Based Potato Crop Abiotic Stress Detection via Instance Segmentation E Savvakis, D Kapetas, MC Martínez-Ballesta, N Katsoulas, ... AI 7 (3), 111 , 2026 2026
Multispectral AI-driven imaging for detection of downy mildew and gray mold in grapevines D Kapetas, P Christakakis, I Naounoulis, I Vagelas, S Faliagka, ... Smart Agricultural Technology, 101990 , 2026 2026
Corrigendum to “Capturing the physiological and growth dynamics of cucumber cultivated in coupled and decoupled aquaponic systems”[Scientia Horticulturae Volume 351, September … A Mourantian, M Aslanidou, E Mente, N Katsoulas, E Levizou Scientia Horticulturae, 114674 , 2026 2026
Assessment of Future Water Stress of Winter Wheat and Olive Trees in Greece Using High-Resolution Climate Model Projections A Elvanidi, P Maletsika, N Katsoulas, G Papadopoulos, D Melas, K Douvis, ... Agronomy 16 (1), 35 , 2025 2025 Citations: 1
Projected Heat-Stress in Sheep and Cattle in Greece Under Future Climate Change Scenarios DK Papanastasiou, AI Gelasakis, G Papadopoulos, D Melas, K Douvis, ... Agriculture 15 (20), 2141 , 2025 2025 Citations: 3
A circular tri-trophic system incorporating plants, fish, and insects turns waste into a resource: case study with the cultivation of cucumber E Levizou, A Mourantian, M Chatzinikolaou, M Feka, IT Karapanagiotidis, ... Frontiers in Plant Science 16, 1638443 , 2025 2025 Citations: 2
Multi-State Modeling of Greenhouse Cucumber Yield Dynamics Under Microclimate Effects E Seri, F Biso, G Bovesecchi, N Katsoulas, C Cornaro arXiv preprint arXiv:2510.11485 , 2025 2025 Citations: 1
Evaluation of a Three-Level Cascade Soilless System Under Saline Greenhouse Conditions E Karatsivou, A Elvanidi, N Katsoulas Horticulturae 11 (10), 1168 , 2025 2025 Citations: 3
Capturing the physiological and growth dynamics of cucumber cultivated in coupled and decoupled aquaponic systems A Mourantian, M Aslanidou, E Mente, N Katsoulas, E Levizou Scientia Horticulturae 351, 114377 , 2025 2025 Citations: 1
Sustainable greenhouse microclimate modeling: A comparative analysis of recurrent and Graph Neural Networks E Seri, M Petitta, C Papaioannou, N Katsoulas, C Cornaro Building and Environment, 113473 , 2025 2025 Citations: 7
Cascade Hydroponics as a Means to Increase the Sustainability of Cropping Systems: Evaluation of Functional, Growth, and Fruit Quality Traits of Melons Z Karachaliou, I Naounoulis, N Katsoulas, E Levizou Sustainability 17 (10), 4527 , 2025 2025 Citations: 2
Effect of installing organic photovoltaic panels on the environmental performance of greenhouse tomato in Greece. A Giakoumatos, V Anestis, T Bartzanas, N Katsoulas 2025
Artificial intelligence algorithms revolutionizing insect monitoring and detection challenges. P Christakakis, D Kapetas, N Frangakis, S Faliagka, N Katsoulas, ... 2025
Greenhouses energy audits-procedures and results. C Baxevanou, D Fidaros, C Papaioannou, N Katsoulas 2025
AI-driven insect detection, real-time monitoring, and population forecasting in greenhouses D Kapetas, P Christakakis, S Faliagka, N Katsoulas, EM Pechlivani AgriEngineering 7 (2), 29 , 2025 2025 Citations: 20
Simulating the Microclimate of a Pilot Greenhouse for the EU Project REGACE on Innovative Agri-Voltaic Technology C Cornaro, M Petitta, G Bovesecchi, P Fagiano, C Voinea, W Fornari, ... BUILDING SIMULATION APPLICATIONS BSA..., 173-181 , 2025 2025
Simulating the microclimate of a pilot greenhouse for testing innovative agri-voltaic system technology C Cornaro, M Petitta, G Bovesecchi, C Voinea, W Fornari, C Baxevanou, ... 2025
Cascade hydroponics enhanced water and nutrients use efficiency in a greenhouse cucumber-melon crop combination I Naounoulis, S Faliagka, E Levizou, N Katsoulas Scientia Horticulturae 338, 113822 , 2024 2024 Citations: 4
In Situ Nitrate Monitoring for Improved Fertigation in On-Demand Coupled Aquaponic Systems S Faliagka, I Naounoulis, EM Pechlivani, N Katsoulas Nitrogen 5 (4), 1048-1057 , 2024 2024 Citations: 2
MOST CITED SCHOLAR PUBLICATIONS
Internet of Things in agriculture, recent advances and future challenges A Tzounis, N Katsoulas, T Bartzanas, C Kittas Biosystems engineering 164, 31-48 , 2017 2017 Citations: 1438
Implementing sustainable irrigation in water-scarce regions under the impact of climate change G Nikolaou, D Neocleous, A Christou, E Kitta, N Katsoulas Agronomy 10 (8), 1120 , 2020 2020 Citations: 458
Effect of Light Intensity and Quality on Growth Rate and Composition of Chlorella vulgaris MN Metsoviti, G Papapolymerou, IT Karapanagiotidis, N Katsoulas Plants 9 (1), 31 , 2019 2019 Citations: 325
Influence of whitening on greenhouse microclimate and crop energy partitioning A Baille, C Kittas, N Katsoulas Agricultural and forest meteorology 107 (4), 293-306 , 2001 2001 Citations: 214
Crop reflectance monitoring as a tool for water stress detection in greenhouses: A review N Katsoulas, A Elvanidi, KP Ferentinos, M Kacira, T Bartzanas, C Kittas Biosystems Engineering 151, 374-398 , 2016 2016 Citations: 202
Air temperature regime in a forced ventilated greenhouse with rose crop C Kittas, M Karamanis, N Katsoulas Energy and buildings 37 (8), 807-812 , 2005 2005 Citations: 200
Effect of misting on transpiration and conductances of a greenhouse rose canopy N Katsoulas, A Baille, C Kittas Agricultural and forest meteorology 106 (3), 233-247 , 2001 2001 Citations: 188
Wireless sensor networks for greenhouse climate and plant condition assessment KP Ferentinos, N Katsoulas, A Tzounis, T Bartzanas, C Kittas Biosystems engineering 153, 70-81 , 2017 2017 Citations: 187
Effect of irrigation frequency on rose flower production and quality N Katsoulas, C Kittas, G Dimokas, C Lykas Biosystems engineering 93 (2), 237-244 , 2006 2006 Citations: 183
Effect of vent openings and insect screens on greenhouse ventilation N Katsoulas, T Bartzanas, T Boulard, M Mermier, C Kittas Biosystems Engineering 93 (4), 427-436 , 2006 2006 Citations: 182
Irrigation of greenhouse crops G Nikolaou, D Neocleous, N Katsoulas, C Kittas Horticulturae 5 (1), 7 , 2019 2019 Citations: 171
Influence of shading screens on microclimate, growth and productivity of tomato C Kittas, N Rigakis, N Katsoulas, T Bartzanas International Symposium on Strategies Towards Sustainability of Protected … , 2008 2008 Citations: 145
Modelling crop transpiration in greenhouses: Different models for different applications N Katsoulas, C Stanghellini Agronomy 9 (7), 392 , 2019 2019 Citations: 140
Effect of two UV-absorbing greenhouse-covering films on growth and yield of an eggplant soilless crop C Kittas, M Tchamitchian, N Katsoulas, P Karaiskou, CH Papaioannou Scientia Horticulturae 110 (1), 30-37 , 2006 2006 Citations: 128
Interactions between salinity and irrigation frequency in greenhouse pepper grown in closed-cycle hydroponic systems D Savvas, E Stamati, IL Tsirogiannis, N Mantzos, PE Barouchas, ... Agricultural Water Management 91 (1-3), 102-111 , 2007 2007 Citations: 125
Computational fluid dynamics applications to improve crop production systems T Bartzanas, M Kacira, H Zhu, S Karmakar, E Tamimi, N Katsoulas, IB Lee, ... Computers and Electronics in Agriculture 93, 151-167 , 2013 2013 Citations: 123
Effects on microclimate, crop production and quality of a tomato crop grown under shade nets C Kittas, N Katsoulas, V Rigakis, T Bartzanas, E Kitta The Journal of Horticultural Science and Biotechnology 87 (1), 7-12 , 2012 2012 Citations: 122
Comparison of growth rate and nutrient content of five microalgae species cultivated in greenhouses MN Metsoviti, G Papapolymerou, IT Karapanagiotidis, N Katsoulas Plants 8 (8), 279 , 2019 2019 Citations: 103
Thermal environment of urban schoolyards: current and future design with respect to children’s thermal comfort D Antoniadis, N Katsoulas, DΚ Papanastasiou Atmosphere 11 (11), 1144 , 2020 2020 Citations: 91
Influence of greenhouse ventilation regime on the microclimate and energy partitioning of a rose canopy during summer conditions C Kittas, N Katsoulas, A Baille Journal of Agricultural Engineering Research 79 (3), 349-360 , 2001 2001 Citations: 87