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Models for the evapotranspiration of greenhouse crops are needed both for accurate irrigation and for the simulation or management of the greenhouse climate. For this purpose, several evapotranspiration models have been developed and presented, all based on the Penman–Monteith approach, the “big-leaf” model. So, on the one hand, relatively simple models have been developed for irrigation scheduling purposes, and on the other, “knowledge–mechanistic” models have been developed for climate control purposes. These models differ in the amount of detail about variables, such as stomatal and aerodynamic conductance. The aim of this review paper is to present the variables and parameters affecting greenhouse crop transpiration, and to analyze and discuss the existing models for its simulation. The common sub-models used for the simulation of crop transpiration in greenhouses (aerodynamic and stomatal conductances, and intercepted radiation) are evaluated. The worth of the multilayer models for the simulation of the mass and energy exchanges between crops and air are also analyzed and discussed. Following the presentation of the different models and approaches, it is obvious that the different applications for which these models have been developed entail varying requirements to the models, so that they cannot always be compared. Models developed in different locations (high–low latitudes or for closed or highly ventilated greenhouses) are discussed, and their sensitivity to different parameters is presented.

The sustainability of irrigated agriculture is threatening due to adverse climate change, given future projections that every one in four people on Earth might be suffering from extreme water scarcity by the year 2025. Pressurized irrigation systems and appropriate irrigation schedules can increase water productivity (i.e., product yield per unit volume of water consumed by the crop) and reduce the evaporative or system loss of water as opposed to traditional surface irrigation methods. However, in water-scarce countries, irrigation management frequently becomes a complex task. Deficit irrigation and the use of non-conventional water resources (e.g., wastewater, brackish groundwater) has been adopted in many cases as part of a climate change mitigation measures to tackle the water poverty issue. Protected cultivation systems such as greenhouses or screenhouses equipped with artificial intelligence systems present another sustainable option for improving water productivity and may help to alleviate water scarcity in these countries. This article presents a comprehensive review of the literature, which deals with sustainable irrigation for open-field and protected cultivation systems under the impact of climatic change in vulnerable areas, including the Mediterranean region.

In this research, the effect of solar irradiance on Chlorella vulgaris cultivated in open bioreactors under greenhouse conditions was investigated, as well as of ratio of light intensity in the 420–520 nm range to light in the 580–680 nm range (I420–520/I580–680) and of artificial irradiation provided by red and white LED lamps in a closed flat plate laboratory bioreactor on the growth rate and composition. The increase in solar irradiance led to faster growth rates (μexp) of C. vulgaris under both environmental conditions studied in the greenhouse (in June up to 0.33 d−1 and in September up to 0.29 d−1) and higher lipid content in microalgal biomass (in June up to 25.6% and in September up to 24.7%). In the experiments conducted in the closed bioreactor, as the ratio I420–520/I580–680 increased, the specific growth rate and the biomass, protein and lipid productivities increased as well. Additionally, the increase in light intensity with red and white LED lamps resulted in faster growth rates (the μexp increased up to 0.36 d−1) and higher lipid content (up to 22.2%), while the protein, fiber, ash and moisture content remained relatively constant. Overall, the trend in biomass, lipid, and protein productivities as a function of light intensity was similar in the two systems (greenhouse and bioreactor).

Greenhouse climate control systems are usually based on greenhouse microclimate settings to exert any control. However, to save energy, water and nutrients, additional parameters related to crop performance and physiology will have to be considered. In addition, detecting crop stress before it is clearly visible by naked eye is an advantage that could aid in microclimate control. In this study, a Machine Learning (ML) model which takes into account microclimate and crop physiological data to detect different types of crop stress was developed and tested. For this purpose, a multi-sensor platform was used to record tomato plant physiological characteristics under different fertigation and air temperature conditions. The innovation of the current model lies in the integration of photosynthesis rate (Ps) values estimated by means of remote sensing using a photochemical reflectance index (PRI). Through this process, the time-series Ps data were combined with crop leaf temperature and microclimate data by means of the ML model. Two different algorithms were evaluated: Gradient Boosting (GB) and MultiLayer perceptron (MLP). Two runs with different structures took place for each algorithm. In RUN 1, there were more feature inputs than the outputs to build a model with high predictive accuracy. However, in order to simplify the process and develop a user-friendly approach, a second, different run was carried out. Thus, in RUN 2, the inputs were fewer than the outputs, and that is why the performance of the model in this case was lower than in the case of RUN 1. Particularly, MLP showed 91% and 83% accuracy in the training sample, and 89% and 82% in testing sample, for RUNs 1 and 2, respectively. GB showed 100% accuracy in the training sample for both runs, and 91% and 83% in testing sample in RUN 1 and RUN 2, respectively. To improve the accuracy of RUN 2, a larger database is required. Both models, however, could easily be incorporated into existing greenhouse climate monitoring and control systems, replacing human experience in detecting greenhouse crop stress conditions.

Precision agricultural greenhouse systems indicate considerable scope for improvement of irrigation management practices, since growers typically irrigate crops based on their personal experience. Soil-based greenhouse crop irrigation management requires estimation on a daily basis, whereas soilless systems must be estimated on an hourly or even shorter interval schedule. Historically, irrigation scheduling methods have been based on soil or substrate monitoring, dependent on climate or time with each having both strengths and weaknesses. Recently, plant-based monitoring or plant reflectance-derived indices have been developed, yet their potential is limited for estimating the irrigation rate in order to apply proper irrigation scheduling. Optimization of irrigation practices imposes different irrigation approaches, based on prevailing greenhouse environments, considering plant-water-soil relationships. This article presents a comprehensive review of the literature, which deals with irrigation scheduling approaches applied for soil and soilless greenhouse production systems. Irrigation decisions are categorized according to whether or not an automatic irrigation control has the ability to support a feedback irrigation decision system. The need for further development of neural networks systems is required.

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.

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.

Aquaponics is an innovative farming system that combines hydroponics and aquaculture, resulting in the production of both crops and fish. Decoupled aquaponics is a new approach introduced in aquaponics research for the elimination of certain system bottlenecks, specifically targeting the optimization of crops and fish production conditions. The aquaponics-related literature predominantly examines the system's effects on crop productivity, largely overlooking the plant functional responses which underlie growth and yield performance. The aim of the study was the integrated evaluation of basil performance cultivated under coupled and decoupled aquaponic systems compared with a hydroponic one, in terms of growth and functional parameters in a pilot-scale aquaponics greenhouse. We focused on the efficiency of the photosynthetic process and the state of the photosynthetic machinery, assessed by instantaneous gas exchange measurements as well as photosynthetic light response curves, and chlorophyll fluorescence. Light use efficiency was estimated through leaf reflectance determination. Photosynthetic pigments content and leaf nutritional state assessments completed the picture of basil functional responses to the three different treatments/systems. The plant's functional parameters were assessed at 15-day intervals. The experiment lasted for two months and included an intermediate and a final harvest during which several basil growth parameters were determined. Coupled aquaponics resulted in reduced growth, which was mainly ascribed to sub-sufficient leaf nutrient levels, a fact that triggered a series of negative feedbacks on all aspects of their photosynthetic performance. These plants experienced a down-regulation of PSII activity as reflected in the significant decreases of quantum yield and efficiency of electron transport, along with decreased photosynthetic pigments content. On the contrary, decoupled aquaponics favored both growth and photochemistry leading to higher light use efficiency compared with coupled system and hydroponics, yet without significant differences from the latter. Photosynthetic light curves indicated constantly higher photosynthetic capacity of the decoupled aquaponics-treated basil, while also enhanced pigment concentrations were evident. Basil functional responses to the three tested production systems provided insights on the underlying mechanisms of plant performance highlighting key-points for systems optimization. We propose decoupled aquaponics as an effective system that may replace hydroponics supporting high crops productivity. We suggest that future works should focus on the mechanisms involved in crop and fish species function, the elucidation of which would greatly contribute to the optimization of the aquaponics productivity.

Aquaponics is currently undergoing a transformation into an intensive food production system. The initially applied systems focused on small-scale, fish-centric coupled (CAP, the aquaculture, and the hydroponic units are arranged in a single loop, and the water flows continuously from the fish tanks to the plant unit and back) aquaponics. More recently, the primary area of research interest has shifted toward larger-scale, plant-centric decoupled (aquaculture and hydroponics units are arranged in a multi-loop setup as separate functional units that can be controlled independently) systems, aiming to achieve greater economic benefits and employ more environmentally friendly practices. The objective of this study was to address gaps in the expansion of decoupled larger-scale aquaponics and to provide a comprehensive understanding of the water and nutrient flow in the system. For this purpose, experiments were performed in a greenhouse on CAP and DCAP systems, while this study also included measurements in a pure hydroponic system (HP). This study presents an assessment of the water and nutrient flow in four different crops: basil; cucumber; parsley; and tomato, all co-cultivated with a tilapia aquaculture system. Significant nutrient deficiencies and imbalances were identified in the CAP solution, leading to pronounced impacts on nutrient assimilation, particularly for fruiting vegetables. However, the average nutrient use efficiency (NUE) for nitrogen, phosphorous, potassium, and calcium was found to be 42% higher in the CAP treatment compared to HP and DCAP treatments. The nutrient solution in the DCAP treatment did not exhibit differences in water quality parameters and nutrient efficiency when compared to HP, resulting in similar effects on nutrient assimilation. Nonetheless, it was observed that DCAP plants exhibited superior NUE compared to HP plants.

Urban outdoor thermal conditions, and its impacts on the health and well-being for the city inhabitants have reached increased attention among biometeorological studies during the last two decades. Children are considered more sensitive and vulnerable to hot ambient conditions compared to adults, and are affected strongly by their thermal environment. One of the urban outdoor environments that children spend almost one third of their school time is the schoolyard. The aims of the present manuscript were to review studies conducted worldwide, in order to present the biophysical characteristics of the typical design of the urban schoolyard. This was done to assess, in terms of bioclimatology, the interactions between the thermal environment and the children’s body, to discuss the adverse effects of thermal environment on children, especially the case of heat stress, and to propose measures that could be applied to improve the thermal environment of schoolyards, focusing on vegetation. Human thermal comfort monitoring tools are mainly developed for adults, thus, further research is needed to adapt them to children. The schemes that are usually followed to design urban schoolyards create conditions that favour the exposure of children to excessive heat, inducing high health risks to them. The literature survey showed that typical urban schoolyard design (i.e., dense surface materials, absence of trees) triggered high surface temperatures (that may exceed 58 °C) and increased absorption of radiative heat load (that may exceed 64 °C in terms of Mean Radiant Temperature) during a clear day with intense solar radiation. Furthermore, vegetation cover has a positive impact on schoolyard’s microclimate, by improving thermal comfort and reducing heat stress perception of children. Design options for urban schoolyards and strategies that can mitigate the adverse effects of heat stress are proposed with focus on vegetation cover that affect positively their thermal environment and improve their aesthetic and functionality.