Urban gardens are increasingly framed as multifunctional components of urban green infrastructure, yet limited evidence exists on how ordinary, municipally managed gardens are experienced through everyday and long-term use. This study examined perceived environmental restorativeness, self-reported well-being, and patterns of social and motivational engagement among users of municipally managed urban gardens in Padua, Italy. A mixed-methods design combined a qualitative phase, including document analysis, site observations, and interviews with municipal stakeholders and garden representatives, with a quantitative survey completed by 210 gardeners across ten sites (response rate ≈62%). The questionnaire collected data on sociodemographic characteristics, garden use, social interactions, motivations, and self-reported well-being, and assessed perceived restorativeness using the validated Italian 11-item Perceived Restorativeness Scale (PRS-11). Results showed that gardens were widely perceived as restorative environments, with a mean total PRS-11 score of 7.0 and high internal consistency (Cronbach’s alpha = 0.91). Cluster analyses identified distinct user profiles based on seasonal attendance, social interactions, motivations, and perceived restorativeness. In an exploratory Ordinary Least Squares (OLS) regression, motivations related to being in nature and cultivating the land were significantly associated with higher PRS-11 scores, while meeting friends showed a borderline positive association. Self-reported well-being was highly positive across the sample and showed a descriptive gradient across PRS-11 groups. Overall, the findings suggest that municipally managed urban gardens can function as everyday, socially embedded green infrastructures whose perceived restorative value depends on patterns of access, engagement, motivation, and governance, with implications for inclusive urban green infrastructure planning and municipal policy.

This study presents a modular outdoor vertical farming system integrated into building façades to address urban food security and sustainability challenges in Singapore. The design integrates passive climate control, hydroponics and soil-based irrigation, with active monitoring of the vapor pressure deficit (VPD) and photosynthetically active radiation (PAR). Continuous visual imaging is used to support growth monitoring and predictive harvesting, reducing labor needs. Under experimental conditions, deployment of UCNP-coated light-conversion films improved crop yield by 30% and reduced plant heat stress. Photovoltaic arrays and battery storage enabled energy self-sufficiency and microclimate management in the modular farm. The results demonstrated that building-integrated vertical farms can enhance urban food resilience and resource efficiency, offering a scalable model for sustainable agriculture in land-constrained cities.

IntroductionVertical farming offers a sustainable solution for urban food production, but energy optimization remains a critical challenge, with nearly half of the electricity requirements dedicated to artificial lighting. Dynamic adjustment of blue and red light can reduce energy costs, as blue light is more energy-intensive, thereby lowering operating expenses and increasing profitability.MethodsThis research investigates the effects of dynamic adjustment of blue and red light on lettuce (Lactuca sativa, cv. Danstar) plants. Four light treatments were tested, each maintaining a total photosynthetic photon flux density (PPFD) of 200 μmol m-2 s-1 under a 16-hour photoperiod: (1) RB3 (control, 150 μmol m-2 s-1 red and 50 μmol m-2 s-1 blue); (2) 25% blue (B) reduction with hourly alternation between control and 175 μmol m-2 s-1 red/25 μmol m-2 s-1 blue; (3) 38% B reduction with hourly cycling through RB3, 162/38, 175/25, and 188/12 μmol m-2 s-1 of red/blue light; and (4) 50% B reduction with hourly alternation between control and 200 μmol m-2 s-1 monochromatic red. Agronomical, physiological, and morphological data were collected weekly from 7, 14, and 21 days after transplanting.ResultsWhile the 50% B dynamic treatment did not enhance overall crop performance compared to the RB3 control, 25% B and 38% B increased lettuce fresh yield by 50-60%, with dry weight remaining stable.DiscussionThese responses indicate improved leaf hydration (reduced dry matter content) resulting in increased fresh marketable yield, improved light-energy use efficiency by up to 63% and reduced lighting costs by 40%, demonstrating that constant blue light at a fixed PPFD is not required for optimal growth. This approach may offer a viable strategy to reduce production costs and enhance sustainability in controlled environment agriculture.

Vertical farming (VF) is increasingly regarded as a promising solution for year-round, local leafy-green production; however, its substantial electricity demand remains a key environmental concern, and evidence from commercial multi-crop facilities is still limited. We conducted a cradle-to-grave life-cycle assessment (LCA) of a commercial hydroponic VF in Stockholm producing lettuce, pak choi, and kale; the functional unit (FU) was 1 kg of marketed edible product. Impacts were assessed with Environmental Footprint (EF) 3.1 midpoint indicators and sensitivity analyses for electricity sourcing and allocation. Under the baseline electricity mix, climate change reached 2.89 kg CO₂-eq per kg. Energy use dominated most impact categories, while infrastructure was the second contributor and main driver of abiotic depletion of elements. Shifting the electricity supply altered climate-change results from 2.03 to 3.26 kg CO₂-eq per kg, introducing trade-offs across other indicators, notably water use and mineral depletion. Under identical conditions, higher yields resulted in lower impacts for pak choi than lettuce and kale. Allocation sensitivity was limited: economic and mass allocation matched due to uniform prices, and retail-price allocation did not alter crop ranking or hotspot identification. Overall, environmental performance is governed by electricity demand, electricity-mix assumptions, and dilution of fixed burdens through crop productivity.

Light quality plays a decisive role in controlled-environment agriculture, shaping plant morphology, physiology, and productivity. This study investigated the impact of far-red (FR) light on Cannabis sativa L. by comparing two different application strategies: continuous FR supplementation throughout 12 h of the photoperiod and end-of-day (EOD) FR exposure applied only at the end of the light period. In both treatments, FR was added to a background spectrum of red and blue (RB) light, while a control group grown under RB light alone was included to assess the specific effects of FR on plant growth, physiological responses, and flowering. Continuous FR exposure induced pronounced shade-avoidance traits, increasing plant height by 9% and petiole length by 17% relative to the control, and raised leaf dry weight to 12.9 g, 9% higher than under EOD (11.7 g) and 16.3% higher than under RB alone (10.8 g). Besides plant height and petiole length, both FR and EOD treatment induced limited morphological adjustments but increased chlorophyll content by 9%, resulting in greater canopy expansion and photosynthetic potential. However, flowering time was unaffected by spectral treatment, confirming that Cannabis floral induction is tightly regulated by photoperiod rather than light quality. Energy-use analysis revealed that EOD supplementation achieved many of the benefits of continuous FR while reducing overall consumption, but energy-use efficiency analysis proved FR as the more efficient treatment. These findings highlight the potential of FR light, particularly when applied continuously, to optimize vegetative growth and canopy physiology in controlled-environment Cannabis cultivation, while EOD strategies offer a practical compromise between cost savings and physiological benefits.

While vertical farming may offer high productivity per unit land area and has received increasing attention for urban food production, research has primarily focused on leafy greens and herbs. Although recent studies have also introduced fruiting vegetables and cereal crops, comparative evaluations under standardized environmental conditions remain limited because crop morphology, duration, harvestable organs, and biomass allocation differ substantially among crop types. This study, conducted in AlmaVFarm, the experimental vertical farm of the University of Bologna, evaluated the productivity and resource use efficiency of five representative crops grown under identical environmental conditions. Crops included dwarf corn as a staple crop, dwarf tomato as a fruit crop, basil as an herb, and lettuce and arugula as leafy greens. To enable meaningful cross-crop evaluations, performance was assessed using normalized indicators of land-surface, cultivation volume, light, energy, and cost use efficiencies. Lettuce achieved the highest annual marketable yield (73.2 kg FW m−2 y−1), producing 46% more than arugula and 35% more than basil. It also exhibited the greatest land-surface use efficiency (65 kg m−2 y−1), volume use efficiency (24.5 kg m−3 y−1), and energy use efficiency (46.7 g FW kWh−1), corresponding to 3.5-fold and 58-fold higher energy efficiency than tomato and corn, respectively, and up to 1.8-fold higher than arugula and basil. The normalized resource use efficiency framework enabled robust comparisons among contrasting crop categories despite their distinct biological characteristics, revealing substantial differences in adaptation to indoor cultivation. These findings provide a quantitative basis for crop selection and diversification strategies in vertical farming while highlighting the need for crop-specific optimization to improve the resource use efficiency and commercial viability of fruit and staple crops in CEA.

This study investigated the effect of different red:blue (R:B) spectral light ratios on the performance of a multi-task convolutional neural network (CNN) model developed for the automatic classification of four horticultural species and their corresponding phenological stages under controlled artificial lighting conditions. The model was trained and tested using RGB images acquired under five distinct spectral treatments (R:B 1, 3, 5, 7, and 9), and its performance was evaluated using accuracy, precision, recall, F1-score, and Matthews correlation coefficient (MCC). For species classification, the best results were obtained with an R:B 1, achieving an accuracy of 86%, precision of 87%, recall of 85%, F1-score of 85%, and MCC of 0.81. In terms of phenological stage classification, the highest performance was observed at R:B 3 and R:B 5, both yielding 93% accuracy and F1-score, precision and recall above 92%, and an MCC of 0.86. These findings demonstrate that the multi-task CNN model is capable of learning robust and generalizable representations, maintaining high classification performance even under non-optimal spectral conditions. The integration of optimized artificial lighting with intelligent classifiers proves to be a strategic approach for automated monitoring systems in indoor and precision agriculture. Future research should explore the impact of additional spectral components (e.g., green or far-red wavelengths) and the adoption of more advanced neural architectures to further enhance the system’s robustness and scalability.

Strawberry (Fragaria x ananassa Duch.) perishability challenges postharvest quality retention. Traditional postharvest methods have limitations, and early harvesting to extend shelf-life often compromises sensory attributes. This study investigated whether 24 h or 48 h treatments performed at the beginning of postharvest with Red, Blue, Far-Red, or UV-A light-emitting diode (LED) light could improve 'Elsanta' strawberry quality during subsequent 7-day storage at suboptimal temperature (5 degrees C). Fruit quality attributes, including firmness, weight loss, soluble solids content (SSC), titratable acidity (TA), anthocyanins, and volatile organic compounds (VOCs), were assessed. While LED treatments did not significantly affect firmness, they generally increased weight loss compared to dark controls (particularly after 48 h Blue/Red/Far-Red exposures). Light effects on SSC were complex and duration-dependent. Notably, all LED treatments significantly enhanced total anthocyanin content (especially after 48 h exposure), although instrumental color measurements remained unchanged. Compared to dark controls Blue and Red light (especially after 48 h) significantly increased the concentration of key aroma-related VOCs, for the most esters. In conclusion a brief, early postharvest LED exposure, particularly using Blue and Red light, can trigger lasting beneficial effects, enhancing nutritionally relevant anthocyanins and aroma-defining VOCs during storage at 5 degrees C. This suggests an 'early signal' mechanism and offers a potentially practical strategy to improve strawberry quality, mitigating negative impacts of commercial early harvesting practices and potentially benefiting other non-climacteric fruits.

Agriculture remains a key contributor to Central America’s economy, despite climate change posing a significant threat to the sector. In the Trifinio region, already afflicted by arid summers, temperatures are expected to rise in the near future, potentially exacerbating the vulnerability of smallholder farmers. This study investigates the effects of two fungal symbionts, Trichoderma asperellum (TR) and the Arbuscular mycorrhiza fungi (AMF) Glomus cubense, and agronomic choices and practices such as cultivar selection, substrate type, and fertigation management on tomato (Solanum lycopersicum L.) seedling growth and quality. Results showed that nutrient solution and the adoption of forest topsoil as substrate significantly enhanced morphological, physiological, and quality parameters. Modifying the nutrient solution to allow for an increase in plant height of 170% and a dry weight of 163% and enhancing Dickson’s quality index (DQI) by 64.5%, while the use of forest topsoil resulted in plants 58.6% higher, with an increase of 101% in dry weight and of 90.1% in the DQI. Both T. asperellum and G. cubense had positive effects on specific growth parameters; for instance, TR increased leaf number (+6.95%), while AMF increased stem diameter (+3.56%) and root length (+19.1%), although they did not, overall, significantly increase the seedling’s biomass and quality. These findings underscore the importance of agronomic practices in mitigating the impacts of climate change on tomato production, offering valuable insights for farmers in semi-arid regions.

Vertical farming is gaining attention as an indoor growing system because it enables standardised and intense production, thanks to fully controlled growing settings where environmental parameters can be precisely tuned to satisfy plants’ needs. While vertical farming is claimed to feature high use efficiencies of land, water, and nutrient resources, its high energy use is behind some recent major bankruptcies and hinders large-scale uptake of the technology. Thus, a critical analysis of the productive, economic, and environmental performances of vertical farming is needed. Here, we review the state of the art of vertical farming, with the aim to provide quantitative data on productivity and environmental performance, with a focus on resource use efficiency, which can also be used for benchmarking. The article elaborates on how vertical farming compares with open-field and greenhouse production of leafy greens (in particular lettuce). Lettuce yield (as fresh weight, FW, per cultivation area) in vertical farms commonly averages 60 to 105 kg FW m−2 year−1, with energy use efficiency of approximately 0.08–0.13 kg FW kWh−1, and water use efficiency of approximately 140 g FW L−1 H2O. The higher greenhouse gas emissions of vertical farming technology systems (on average, 2.9 kg CO2 kg−1 FW) as compared with traditional systems are discussed and compared to impacts associated with transport in longer supply chains or those caused by energy-intensive greenhouse technologies that enable cultivation in harsh environments. The potential for consistent production throughout seasons in vertical farming suggests that looking at yearly yield only (rather than their monthly trends) may be misleading when addressing a stable food supply in a specific region.

Dynamic management of nitrogen (N) guided by multispectral sensors can help match in-season crop N requirements with precise N supply through fertigation. In the present work, different dynamic strategies to optimize N fertigation in processing tomatoes were explored in two plot experiments across two different years and locations, compared with a well-fertilized control (180 kg N ha-1, N180). In dynamic N strategies, the green vegetation index (GVI) was monitored with a hand-held multispectral radiometer. Whenever the GVI fell below a critical threshold, N fertilizer was supplied via fertigation. Critical thresholds were developed using different approaches: in the spy plot strategy (N SPY), the N fertilizer was supplied whenever the GVI of the plot was below 90% of the GVI in the spy plot N180. Conversely, absolute threshold GVI values were developed in previous modeling stages based on linear-plateau relationships between the GVI and the relative yield (N THR strategies) or based on the monitoring of the GVI profile of tomatoes under non-limiting N conditions in a previous growing season (N SPYEVO). In general, the dynamic N strategies saved a significant amount of N fertilizers (with reductions ranging from 38 to 60%), with best performances observed for the N THR and N SPYEVO. Dynamic N strategies did not penalize the marketable yield, thus, the N use efficiency, the fertilizer costs, and the greenhouse gas emission intensity associated with the fertilization were significantly optimized. Furthermore, dynamic N strategies produced fewer but bigger fruits. The present work shows innovative N management strategies to optimize N inputs in processing tomato cultivation, confirming the potential of multispectral sensors in precision agriculture.

Hyperspectral imaging is widespread in crop nitrogen (N) monitoring for precision agriculture, although approaches that address the agronomical recommendation of the optimal N rate are still lacking. Here, two approaches are explored in defining the optimal N rate to be supplied in fertigated processing tomatoes through hyperspectral imaging. The first one, called the N uptake approach, focuses on the virtual reproduction of the critical N uptake curve through the estimation of both aboveground biomass and crop N uptake. The estimated biomass is used to derive the critical N uptake, and the optimal N rate is computed as the difference between the critical N uptake and the estimated actual N uptake. The second approach focuses on the monitoring of the Nitrogen Nutrition Index (NNI) and biomass. Again, the biomass is used to calculate the critical N uptake, which, when combined with the estimated NNI, resolves the equation to retrieve the actual crop N uptake. A modeling stage was included to estimate the N-related variables from crop canopy reflectance across the full spectrum (400-1000 nm). Canopy reflectance was measured by using an unmanned aerial vehicle at five growth stages of processing tomatoes grown under experimental plot conditions with different N rates. Three nonparametric algorithms were trained, i.e., Gaussian Process Regression (GPR), Support Vector Regression (SVR), and Partial Least Square Regression (PLSR). Multicollinearity of spectral bands was prevented with a principal component analysis, and models were 5-fold cross-validated. Considering the pivotal role of biomass in the selected N rate estimation approaches, two distinct biomass estimation methods were explored. The direct biomass retrieval from spectral data was compared with the indirect biomass retrieval from the remotely sensed LAI applying empirical regressions. PLSR outperformed the other algorithms in estimating N uptake (Relative Root Mean Square Error, RRMSE=21.8%), while SVR better estimated NNI (RRMSE=10.2%) and direct biomass (RRMSE=19.4%). The indirect estimation of biomass outperformed the direct approach when GPR is used (RRMSE 18.2% vs. 21.4%), although the influence of soil background at early growth stages determines an unreliable biomass estimation for both methods. The NNI approach outperformed the N uptake approach in estimating the optimal N rate, especially when the biomass is directly retrieved from GPR. The promising estimation performances in N rate estimation (R2=0.88 and RRMSE=36%) revealed the effectiveness of hyperspectral imaging in entering the agronomical scheduling of precision N management.

The soil of the Trifinio region, the tri-national territory between Guatemala, Honduras, and El Salvador, is damaged by the expansion of monoculture, which decreases fertility and causes problems for local farmers. Furthermore, the region also faces issues of erosion and soil contamination. As an alternative to soil cultivation, soilless systems can be adopted, not requiring fertile soil, and significantly increasing yields and resource use efficiency. To encourage soilless technique application in the region, the aim of this study was to compare 18 different substrate mixes to identify the most suitable for the local cultivation of cucumber (Cucumis sativus L.). The substrates were obtained comparing three rates of peat and compost (0%, 20% and 40%, by volume) in factorial combination, with the remaining being either coir or pumice (filling component). Plant growth, flower setting, physiological status (relative chlorophyll content and leaf temperature), and plant production were evaluated. Highest yield was achieved with 20% peat, while compost (20% and 40%) was able to increase fruit length and improve the relative chlorophyll content, but did not affect total production. However, when focusing on environmental sustainability as an important standpoint, a peat-free substrate should be utilized even though the results favored the 20% peat treatment for production. Considering that the differences in production in favor of 20% peat treatment were of limited practical relevance. In regard to the filling components (coir and pumice) yields were unaffected and only minor parameters were changed. Based on the results obtained, a substrate consisting of 60% coir and 40% compost resulted in the best option for the soilless cultivation of cucumber in the Trifinio region, with both materials being sustainable and easily available for local farmers.

Vertical farming is gaining popularity as a sustainable solution to global food demand, particularly in urban areas where space is limited. However, optimizing key factors such as planting density remains a critical issue, as it directly affects light interception, energy efficiency, and crop yield. Lettuce and basil, the most commonly grown crops in vertical farms, were chosen for this study, with the aim of addressing the impact of planting density on light interception and overall productivity for improving the performance and sustainability of vertical farming systems. Plants were grown in an ebb-and-flow system of a fully controlled experimental vertical farm, where light was provided by light-emitting diode fixtures delivering a photoperiod of 16 h d−1 and 200 µmol m−2 s−1 of photosynthetic photon flux density. Experimental treatments included three planting densities, namely 123 (low density, LD), 237 (medium density, MD), and 680 (high density, HD) plant m−2. At the final harvest (29 days after sowing), the adoption of the highest planting density (680 plant m−2) resulted in greater fresh yield (kg FW m−2), leaf area index (LAI, m2 m−2), light use efficiency (LUE, g DW mol−1) and light energy use efficiency (L-EUE, g FW kWh−1) for both lettuce (+207%, +227%, +142%, +206%, respectively), and basil (+312%, +316%, +291, +309%, respectively), as compared to the lowest density (123 plant m−2). However, the fresh and dry weights of the individual plants were lowered, probably as a result of the reduced light availability due to the highly dense plants’ canopy. Overall, these findings underscore the potential of increasing planting density in vertical farms to enhance yield and resource efficiency.

Within the current scenario of cropland use and forest surface loss, there is a need for the implementation of viable urban farming systems, e.g., indoor vertical farming (VF). Light management is fundamental in VF, although responses to light spectra are often species-specific. As the interest of consumers and farmers towards baby-leaf vegetables has recently increased, this study aimed at assessing the most effective red:blue (RB) ratio for enhanced baby-leaf production of kale (Brassica oleracea). Within an ebb-and-flow system, increasing RB ratios (RB3, RB5, RB7 and RB9) were tested, sharing a photoperiod of 16 h day−1 and a light intensity of 215 μmol m−2 s−1. A larger yield was obtained for plants under RB5, featuring an intermediate B fraction compared to other treatments, with plants displaying more expanded and thinner leaves. Also, for lighting energy and cultivated surface use efficiency, RB5 was the most effective treatment, performing up to 57 g FW kWh−1 and 54 kg FW m−2 y−1, respectively. From multispectral data, a tendency of reduced Fv/Fm and Fq′/Fm′ was observed as the RB ratio increased, while the chlorophyll index was enhanced under RB ≥ 7. This study highlighted the light recipe with an RB ratio of 5 as the most effective lighting mixture for optimal baby-leaf kale production in terms of balanced growth, resource use efficiency and yield.

Current trends evidence a growing demand for nutritious, convenient, and ready-to-eat food options. In this scenario, baby-leaf vegetables result appealing in the food market, by combining elevated nutritional value and ease of consumption. Moreover, their short growth cycle and reduced size make them a convenient and ideal crop category for indoor farming, allowing for both multiple harvests and enhanced yield across the year. Furthermore, leafy greens in their juvenile stage have been identified as highly nutritious and among crops that have recently gained significant attention. Considering the novelty provided by indoor farming technologies and the need for crop diversification beyond well-studied species (e.g., lettuce or basil), this research aimed at identifying for baby-leaf kale cultivation in ebb-and-flow hydroponics in a vertical farm. Plants were therefore grown under high planting density (1,950 plants m-2) for 21 days under four distinct light spectra: two red (R) and blue (B) spectra (at RB ratios of 1 and 3, respectively named RB1 and RB3), or in combination with a white (W) background, featuring the same RB ratios (namely W-RB1 and W-RB3). In all the settings, light intensity (220 mu mol m-2 s-1) and photoperiod (16 h day-1) were the same among treatments. The adoption of a light spectrum with a higher percentage of R resulted in a greater fresh yield, with the highest performances associated with the treatments W-RB3 and RB3 (on average 4.06 kg m-2), also contributing to enhanced water, land surface and lighting-energy use efficiency. Plants under W-RB3 also obtained the greatest dry weight per sample, while dry matter content increased under RB1 and W-RB1 treatments. to boost baby-leaf kale production in a vertical farming system.

Recently, far-red wavelengths (FR, 700–750 nm) have been largely investigated in indoor cultivation systems due to their morphological effects on plants (e.g., leaf expansion and stem elongation), resulting also in increasing yield. This work investigated the effect of substituting part of the red (R) and blue (B) radiation with far-red radiation, while keeping constant the photon flux density, in the light spectrum for lettuce grown in a vertical farm. Lettuce (Lactuca sativa var. Canasta) plants were transplanted and grown in an ebb-and-flow system for 29 days. During the cycle, plants were subjected to five different light treatments: a control treatment consisting of an optimized R and B spectrum (ratio of 3; RB3) with a photosynthetic photon flux density of 200 µmol m−2 s−1, and four treatments in which R and B were partially replaced by 10, 30, 50 and 70 µmol m−2 s−1 of FR light, resulting in an increasing FR fraction. Biomass production and most of the morphological parameters were affected from 15 days after transplanting (DAT), while stomatal conductance from 22 DAT. Leaf greenness and specific leaf area values were influenced by the FR radiation starting from 8 DAT. At 29 DAT, substitution of an amount of R and B photons equal to 30 (RB3–30) or 50 (RB3–50) µmol m−2 s−1 with the same amount of FR radiation resulted in increased leaf biomass in both fresh (+49 and +47%, respectively) and dry weight (+45 and +42%, respectively). With RB3–30, the increase was due to leaf area expansion (+103%), whereas stomatal conductance (gs) and quantum efficiency of photosystem II (ΦPSII) did not change compared with the spectrum with only R and B. With RB3–50, gs and ΦPSII decreased compared with RB3 (-27 and -6%, respectively), but the greater biomass accumulation was supported by the greater leaf expansion (+119 %). The adoption of RB3–30 and RB3–50 also promoted light use efficiency (+45 and +42 %, respectively), lighting energy use efficiency (+48 and +53 %, respectively) and therefore the overall energy performance of the system. The adoption of RB3–30 and RB3–50 is a valid strategy to increase yield for lettuce production, but further studies, also in relation to blue radiation intensity, are needed to avoid the negative effect on leaf pigmentation.

Controversial figures on environmental impacts associated with urban agriculture are receiving attention from the media and the general public. For comparative analysis, however, methodologically sound evidence is needed, before conclusions can be drawn. In this manuscript, we address issues associated with comparative assessment of environmental performances between rural and urban farming, while also evidencing the need for specifically designed indicators that enable for comprehensive assessment of multifunctional urban agriculture.

Climate change significantly impacts agriculture and forage production, requiring the implementation of strategies toward increased water and energy use efficiency. So, this study investigated the yield of forage cactus (Opuntia stricta (Haw.) Haw) under different irrigation depths using brackish groundwater (1.7 dS m−1), whose management was based on reference evapotranspiration (ETo) estimated by the Hargreave–Samani (HS) and Penman–Monteith (PM) equations. The research was conducted in Independência, Ceará, Brazil, under the tropical semi-arid climate. A randomized block design in a 2 × 5 factorial scheme was employed, varying the ET0 estimation equations (HS and PM) and irrigation levels (0; 20; 40; 70; and 100% of total required irrigation—TRI). Growth, productivity, and water use efficiency variables were evaluated at 6, 12, and 18 months after treatment initiation. The economic analysis focused on added value, farmer income, and social reproduction level. The results showed no isolated effect of the equations or their interaction with irrigation depths on the analyzed variables, suggesting that irrigation management can be effectively performed using the simpler HS equation. Furthermore, there was no statistical difference between the means of 100% and 70% TRI as well as between 70% and 40% TRI for most variables. This indicates satisfactory crop yield under deficit irrigation. Dry matter productivity and farmer income at 12 months resulting from complementary irrigation with depths between 40% and 70% of TRI were significantly higher than under rainfed conditions. The 70% depth resulted in yields equivalent to those at 100% TRI, with the social reproduction level being achieved on 0.65 hectares in the second year.