Soil organic carbon and nitrogen mineralisation dynamics in successive greenhouse tomato crops

Soil organic carbon and nitrogen mineralisation dynamics in successive greenhouse tomato crops | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Soil organic carbon and nitrogen mineralisation dynamics in successive greenhouse tomato crops Cecilia Berrueta, Santiago Dogliotti This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6058670/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Understanding and predicting soil organic carbon (SOC) dynamics and the capacity of soil to supply nitrogen (N) to plants agroecosystems has been widely addressed. Many soil properties like texture, moisture, temperature, pH, and cropping practices such as tillage modify SOC and organic N dynamics. This complexity justifies quantifying SOC and N mineralisation in the field. This study aims to determine the evolution of SOC and N mineralisation in greenhouse tomato monoculture over five tomato growing seasons. The amount of SOC mineralised per crop cycle was assessed as the difference between the amount of SOC at the beginning of one crop cycle and the next. SOC mineralisation rate was compared with mineralisation in open-field cropping systems simulated by a model calibrated and validated in Uruguay. An N mass balance was carried out to determine the evolution of N mineralisation and the net soil N mineralisation. Rapid SOC mineralisation under greenhouse systems was evidenced. The total SOC loss during the three years of the experiment was 11.3 Mg ha − 1 (25.6%), overcoming open-field model predictions (6.6 Mg ha − 1 , 14.6%). Annual mineralised soil N (NMn) was higher in 2019, 594 kg ha − 1 , compared to 2021 (398.3 kg ha − 1 ) and was the primary source of N for plant growth. We obtained annual N mineralisation rates between 4.6% and 8.0%, which varied according to the growing season. A higher N mineralisation rate was observed for spring crops with higher temperatures than autumn. SOC and N mineralisation depletion without fertilisation causes a significant reduction in tomato yield. This knowledge will contribute to estimating better soil N supply in greenhouse crops to improve fertilisation plans, not only to improve crop yield but also to minimise environmental burden and fertiliser costs. In addition, soil organic amendments should be planned to maintain SOC content and prevent soil degradation. Earth and environmental sciences/Biogeochemistry/Carbon cycle Earth and environmental sciences/Biogeochemistry/Element cycles Solanum lycopersicum Nitrogen supply Soil degradation Mineralisation rate Figures Figure 1 Figure 2 Figure 3 1. Introduction Soil degradation is a major global challenge to developing sustainable agriculture. Over half of the agricultural land in the world is affected, moderately or severely by degradation processes (UNCCD, 2017 ). The soil organic carbon (SOC) loss due to high soil erosion rates and intensive tillage is the main cause of soil degradation (Steiner, 1996 ; Lal, 2015 ; Haddaway et al., 2017 ). The soil’s capacity to store water and soluble nutrients is associated with carbon (C) organic inputs and turnover. Furthermore, the recovery rate of degraded soil is also linked to stocks and flows of organic C (Neal et al., 2020 ). A decline in SOC causes reduced nitrogen (N) and water supply capacity, constituting important vegetable yield-limiting factors (Alliaume et al., 2013 ). Understanding and modelling SOC dynamics is essential to prevent soil degradation and design management techniques to recover degraded soils. The loss of SOC is a significant sustainability problem for vegetable production systems in Uruguay (Dogliotti et al., 2014 ). Soils under vegetable production in south Uruguay have lost between 44 and 54% of SOC, depending on soil type, compared to the historical reference (Alliaume et al., 2013 ). Scientists worldwide have worked for decades to understand, model, and predict the SOC dynamics and the soil’s N supply capacity to plants in different agroecosystems, which are intimately linked. Plant-available N is a pillar of the performance and productivity of any agroecosystem. It is considered a continuum of inorganic and organic soluble N, with the latter composed of diverse structural complexity molecules, which cycle constantly (Dessureault-Rompré, 2022 ). Optimising N cycling is related to improving the synchronicity between the plant requirement and soil N supply to reduce N losses. Enhancing the sustainability of agroecosystems involves optimising the N cycle. The N supply has been identified as a significant factor limiting greenhouse tomato yield in Uruguay, among other factors such as K nutrition and irrigation (Berrueta et al., 2019 ). On the other hand, NO 3 − leaching to groundwater is more likely if the rate of NO 3 − uptake by the crop is not great enough (Yuan et al., 2000 ). The greater the N excess, the greater the chance of NO 3 − leaching from the upper soil layers to groundwater (Gheysari et al., 2009 ). In the north region of Uruguay, high levels of NO 3 − were detected at 20–40 cm depth in greenhouse soils (Silvera and Barbazán, 2020 ) and constitute a risk for groundwater. Berrueta et al. ( 2024 ) quantified N leaching rates between 12.8–23.4 kg N ha − 1 during two greenhouse tomato growing seasons (145–190 days) in south Uruguay. Crop N fertilisation depends on crop requirement and soil N availability. Soil texture, water content, temperature, pH, and cropping practices such as soil tillage determine the mineralisation of SOC and organic N (Griffin et al., 2008 ). Laboratory incubations have been used to identify and hierarchize the physical and chemical soil properties affecting mineralisation, e.g. the SOC, pH, calcium carbonate content, soil texture and structure (Morvan et al., 2022 ). However, laboratory data do not accurately predict mineralisation under field conditions. Plant-soil interactions strongly affect mineralisation processes, such as soil microorganisms and mesofauna interactions, which are active in decomposition (Scheu, 2005 ) and the plant rhizodeposition effects on N mineralisation. Furthermore, variabilities in the environmental conditions that drive these processes also help to understand why laboratory incubation data are poor predictors of mineralisation under field conditions (Morvan et al., 2022 ). These complexities justify studying and quantifying SOC and N mineralisation in the field. Most fresh tomato production in Uruguay is done under greenhouses and cultivated directly on soil. The greenhouses mostly consist in low-cost structures build with wood and covered with plastic film. The predominant crop cycles are one crop per year (long cycle), transplanted mainly in September and ending in May or June, or two short crops per year (short Spring and Autumn cycles), the Spring cycle transplanted in August until January or February and the Autumn cycle transplanted in February and finished in July. The main reasons to do two short crops per year instead of one long cycle are to deal better with the systemic disease and nematodes and avoid the loss of quality of fruits and problems in fruit set during the summer period (January to February) (Berrueta et al., 2020 ). This study aims to determine the evolution of SOC and N mineralisation in greenhouse tomato monoculture (Uruguay’s primary tomato production system) over five tomato growing seasons by C and N mass balance. This knowledge will contribute to i) better estimation of N supply by soil in greenhouse crops to improve fertilisation plans, not only to improve yield but also to minimise environmental burden and fertilisers costs ii) planning of soil organic amendments to maintain SOC content and prevent soil degradation. 2. Materials and methods 2.1. Experimental and cropping information The three-year experiment was conducted in a greenhouse located at the National Institute of Agricultural Research station in Canelones (South of Uruguay) (34°40’S, 56°20’W and 32 m elevation). The average mean annual temperature in the region is 17°C. The greenhouse soil was classified as Luvic Phaeozems according to FAO classification (2006). Five consecutive tomato crops ( Solanum lycopersicum L.): Aut-19, Spr-19, Aut-20, Aut-21, and Spr-21 grown in 2019, 2020, and 2021 were used for SOC and N balances (Table 1 ). The tomato cultivar used for spring crops was Lapataia, and the cultivar Elpida was used for autumn crops, as is typical for each growing season in commercial farms in the region. During spring 2020, the greenhouse remained bare fallow. The greenhouse was made of wood, 60 m long and 14.5 m wide (870 m 2 ), and had a single gable roof structure covered with light-diffusing plastic film. The maximum height (ridge) was 4.5 m and the minimum (gutter) was 2 m. The greenhouse had passive lateral and ridge ventilation and north-south orientation. Before the greenhouse construction, the field was used for open-field vegetable production until 2008. From autumn 2008 to autumn 2018, annual winter and summer forage crops were rotated with four or five years of grass and legume pastures (two cycles of a 5 or 6 years rotation). In autumn 2018, the pasture was tilled, and the soil was left fallow during the greenhouse construction. Table 1 Cultivar, dates, and growth period of tomato crops (south hemisphere) Crop Transplanting date First harvest date End of crop date Growth period (days) Aut-19 Feb 6, 19 Apr 29, 19 Aug 12, 19 187 Spr-19 Aug 22, 19 Nov 29, 19 Jan 23, 20 154 Aut-20 Feb 10, 20 May 5, 20 Aug 18, 20 190 Aut-21 Feb 01, 21 Apr 19, 21 Aug 02, 21 182 Spr-21 Aug 30, 21 Dec 2, 21 Jan 22, 22 145 Seedlings were transplanted in raised beds at a plant density of 2.66 plants m − 2 (1.88 x 0.2 m) five weeks after sowing. The soil was tilled 15 days before transplanting each crop using a chisel plough, a disc harrow, and a disk hiller for putting up the raised beds. The raised beds were 90 cm wide and 20 cm high (Fig. 1 ). The soil was also tilled before the fallow period of autumn 2020. After tillage, the raised beds were covered with a white, 1.4 m width plastic mulch. Tomato plants were trained by tying up the main stem with nylon cords hanging from a steel wire 1.8 m in height, and suckers were periodically pruned. The top of the plants was pruned after the eighth cluster. The irrigation system consisted of drip tape on the soil surface, two paired lines per raised bed (5.3 dripper m 2 with a flow rate of 1 L h − 1 ). Irrigation was sheduled to keep the soil matric potential in the root zone within − 8 to − 12 kPa. Soil matric potential was measured daily with 12 tensiometers (Irrometer, Co., Riverside, USA) located at 20 cm depth in the middle of each plot. Three treatments, consisting of different mineral fertilisation rates, were applied to each of the five tomato crops. In the control (T1), no fertilisers were added. T1 was the only treatment used for this study. The second treatment (T2) was fertirrigated with a complete nutrient solution to ensure that crop growth was not limited by macronutrients and micronutrients using nutrient total absorption, according to Ciampitti and García ( 2007 ). We did petiole sap tests every two weeks to check N and potassium levels and compared them to reference values (Hochmuth, 2015) to ensure that they were not limiting crop growth. The last treatment (T3) consisted of 50% more nitrogen applied compared to T2. For each trial, the experiment was conducted using a randomised complete block design with four replications. Plots measured 14 m long by 1.88 m width and contained one tomato plant row. Two blocks were located in the north part of the greenhouse and two to the south with a central path of 2.5 m along its east-west axis. The raised beds on the edges of the greenhouse were not included in the experiment and were left as borders. 2.2. Soil and greenhouse climate measurements The top soil layer (0–30 cm) was sampled before the Aut-19 crop to measure the silt, sand, and clay fraction by the modified pipette method (Maltoni and Aquino, 2003 ). To assess soil bulk density and the moisture retention curves, we took two undisturbed samples at 10–15 cm depth per plot, using metal rings (5 cm length and 5.5 cm diameter) before the first tomato crop planting (January 2019). Bulk-density metal rings were oven-dried for 48 hours at 105 ºC. A soil profile was taken to measure the soil horizons and rooting depth. The soil top layer was 30 cm deep, and the textural class was silty clay loam (35% clay, 61% silt and 4% sand). The bulk density (5–20 cm depth) at the beginning of the experiment (January 2019) was 1.19 Mg m − 3, and the available water was 13.91 mm 10 cm − 1 . Composite soil samples in two depths (0–20 and 20–40 cm) were collected at the raised beds immediately before planting each tomato crop and at the end of Spr-21 crop. Mineral N (NO 3 − – N), organic C, pH, electrical conductivity (EC), and exchangeable Na + , Ca ++ , K + , and Mg ++ were analysed. Mineral N was measured by the nitrate electrode method (Gelderman and Beegle, 1998 ). Organic C content was determined by sample dry combustion and subsequent detection of CO 2 by infrared (Wright and Bailey, 2001 ). The amounts of mineral N and organic C per ha were estimated using the initial bulk density (1.19 Mg m -3 ) and a soil volume of 1914.9 m 3 ha -1 : Soil volume (m 3 ha -1 ) = (10000 m 2 * raised beds width (m) / distance between rows (m)) * depth explored by roots (m) (1) Where, Raised beds width (m) = 0.9 Distance between rows (m) = 1.88 Depth explored by roots (m) = 0.4 Greenhouse air temperature and relative humidity were measured and recorded every 1 hour with a weather station (model Vantage Pro2, Davis Instruments, USA) located at the centre of the greenhouse placed 2 m above the ground. The daily radiation inside the greenhouse was estimated by multiplying outside solar radiation by greenhouse transmissivity. A pyranometer (model CS320, Campbell Scientific, UT, USA) located outside the greenhouse was used to record daily global radiation. We measured the greenhouse transmissivity for each trial at crop planting using a ceptometer (model LP-80, Decagon Devices Inc., Pullman, USA). On each measurement day, we took 16 measurements at different positions inside and outside the greenhouse, at 1.5 m above ground, three times (9:00, 12.00, and 16:00). Greenhouse transmissivity was assessed on sunny days. 2.3. Calculation of SOC mineralisation and model simulation of SOC The amount of SOC mineralised per crop cycle was calculated as the difference between the amount of SOC at the beginning of one crop cycle and the next. The average SOC mineralisation rate was estimated as the difference between the initial and final SOC divided by the experiment length (3 years). To compare the SOC mineralisation rate under greenhouse and open-field cropping systems, we used a simulation model developed, calibrated and validated for open-field cropping systems in South Uruguay by Dogliotti et al. ( 2004 ). We simulated the evolution of soil organic matter in the top 20 cm of soil in the field where the greenhouse was built in 2018 from autumn 2006 till autumn 2021. The crops yields, residue yield ratios, initial conditions and parameters set used for the simulation are provided in detail in Appendix A. 2.4. Calculating Net Soil N Mineralisation from N mass balance To determine the evolution of N mineralisation in greenhouse tomato monoculture over five tomato growing seasons, we carried an N mass balance for the control treatment (T1), applying Eq. 2. T1 had no manure application, and all above-ground crop residues were removed from the greenhouse. It was assumed that gaseous N losses were low and largely compensated by N symbiotic fixation and atmospheric deposition of N (Morvan et al., 2022 ). NMn + Ni + Nwater = Nuptake + Nleached + Nf (2) Where, NMn (kg N ha − 1 ) = mineralised soil N per crop season Ni (kg N ha − 1 ) = soil mineral N in the 0–20 cm soil layer at transplanting Nf (kg N ha − 1 ) = soil mineral N in the 0–20 cm soil layer at the end of crop cycle Nwater (kg N ha − 1 ) = N in water applied with crop irrigation Nuptake (kg N ha − 1 ) = Total N uptake by the crop Nleached (kg N ha − 1 ) = N leached as NO 3 − during crop growth Net soil N mineralisation was determined by N balance from Eq. 3, as follows: NMn = Nuptake + Nleached + Nf – Ni – Nwater (3) 2.4.1. Estimation of tomato crop N uptake The evolution of the above-ground biomass production throughout each crop cycle was assessed by destructive measurements of one plant per replicated plot every 20 days. Dry matter was measured by oven-drying leaves, stems and fruits at 65 ◦ C until constant weight. The biomass of all pruned shoot material and harvested fruits was determined in 10 plants per replicate plot throughout each crop cycle, and dry matter was determined as previously described for whole plant sampling. On average, seven whole-plant destructive measurements, 9 fruit harvests and 14 shoot prunings were conducted for each tomato crop. The total dry matter production was determined by adding the dry matter of leaves, stems, and immature fruits plus the accumulated dry weight of all pruned material and harvested fruits before the sampling date. The determination of dry matter N content (%) was done in finely ground samples of leaves, fruits and stems from the biomass samplings, harvested fruits, and pruned material using the Kjeldahl method. The N uptake was calculated as the product of the dry weight and N content. The above-ground crop N uptake was calculated for each biomass sampling as the sum of the N uptake of leaves, immature fruit, and stems plus the accumulated uptake of harvested fruits and all shoot material pruned before the sampling date. Below-ground crop N uptake was estimated as 4% of total N uptake (Khan and Sagar, 1969 ; Richards et al., 1979 ; Scholberg et al., 2000 ) and was added to above-ground crop N uptake to estimate total crop N uptake. 2.4.2. Estimation of N leached Water drainage was collected using three free draining lysimeters with 2 m long, 0.9 m wide and 1.4 m deep, located on the northern side of the greenhouse for Spr-19, Aut-20, Aut-21 and Spr-21. The soil profile in lysimeters was the same as the greenhouse soil described above. At the lysimeter bottom, a layer of gravel between geotextile meshes was used as a filter layer. Accumulated water drainage volumes were assessed 5 times per week. Once a week, representative sub-samples from each lysimeter drainage volume were analysed to determine the concentration of NO 3 − by ion chromatography. N leaching was calculated as the product of N concentration and drainage volume. For Aut-19, lysimeters were not installed; thus, N leached was estimated using the equation proposed by Berrueta et al. ( 2024 ) (Eq. 4). Total drainage was calculated as the difference between total irrigation and crop evapotranspiration (ETc). ETc was estimated using the VegSyst model calibrated and validated for Uruguay (Berrueta et al., 2023 ). N leaching (kg ha − 1 ) = 0.2182 (total drainage (mm)) – 0.1594 (4) 2.4.3. Estimation of N in irrigation water The volume of irrigation was measured daily for each treatment using volumetric meters. Samples of irrigation water were collected in January 2019, 2020, and 2021 to evaluate the concentrations of N - NO 3 − , pH, and electrical conductivity (Table 2 ). The N applied through irrigation was calculated using the N concentrations and the total amount of irrigation applied during the crop growth period. Table 2 Chemical characteristics of irrigation water (samples of January 2019, 2020 and 2021) Year pH EC * (dS m − 1 ) N - NO 3 − (mg N l − 1 ) 2019 6.8 0.16 0.5 2020 7.2 0.24 0.5 2021 7.3 0.22 1.4 *Electrical conductivity 2.5. Calculating N annual mineralisation rate The N annual mineralisation rate was calculated using Eq. 5. The initial amount of organic N was calculated from the SOC content in the soil (0–20 cm) and assuming a soil C:N ratio of 10:1. N annual mineralisation rate (%) = (NMn/Organic N) * (365/Growth period) * 100 (5) Where, N annual mineralisation rate (%) is the percentage of soil organic N mineralised per year to a 20 cm depth. NMn (kg ha − 1 ) is the net soil N mineralisation determined by N balance from Eq. 3. Organic N (kg ha − 1 ) is the amount of soil organic N to a 20 cm depth estimated from the SOC content before transplanting of each crop and a C:N ratio of 10:1. Growth period (days) is each crop growth period as presented in Table 1 . 2.6. Tomato yield and N utilisation efficiency determinations Tomato yield was determined by harvesting all mature fruits in 10 plants per plot for each trial. N utilisation efficiency (kg fruit kg N uptake − 1 ) was estimated as the ratio between tomato yield (kg fruit ha − 1 ) and total N uptake (kg N ha − 1 ). 3. Results 3.1. Soil and climate Greenhouse solar transmissivity measured were in the range of 60 and 64%, with the highest value for Aut-19 and the lowest for Spr-21. Significant differences in daily solar radiation and air temperature were observed between growing seasons. Spring crops showed higher average daily solar radiation and air temperature compare to autumn crops (Table 3 ). For a given growing season (autumn and spring), average air temperature and daily solar radiation had no significant variation among years. Table 3 Average air temperature (mean, minimum and maximum) and average daily solar radiation integral during each crop’s tomato growing season. Crop Air temperature (º C) Average daily integral of solar radiation (MJ m − 2 d − 1 ) Mean Minimum Maximum Aut-19 17.3 11.6 24.5 8.1 Spr-19 20.9 13.7 29.5 13.2 Aut-20 17.6 11.9 25.6 7.8 Aut-21 17.8 12.2 25.6 8 Spr-21 20.9 14.4 28.4 12.6 The SOC at the beginning of the experiment was 1.93% and decreased by 26% during the experiments (Table 4 ). Mineral N at crop transplanting also decreased from 40 kg ha − 1 in Aut-19 to 1.4 kg ha − 1 in autumn 2022 (Aut-22). From Aut-20, mineral N remained below 3 kg ha − 1 . Table 4 Soil organic carbon (SOC) and mineral nitrogen (N) at transplanting for each trial and at the end of the experiments in autumn 2022 (Aut-22) Aut-19 Spr-19 Aut-20 Aut-21 Spr-21 Aut-22 SOC (%) 1.93 1.76 1.66 1.52 1.33 1.43 SOC (Mg ha − 1 ) 44.0 40.1 37.8 34.5 30.2 32.7 Mineral N (kg ha − 1 ) 40.0 21.1 2.4 1.9 1.4 1.4 3.2. SOC mineralisation SOC decreased rapidly, from 44.0 Mg ha -1 at the beginning of the experiment to 32.7 Mg ha -1 at the end (Table 4 , Fig. 2 ). The annual SOC mineralisation rate was highest (14.0%) during the first year of the experiment, reducing to 8.7% and 5.3% in the subsequent years (Table 5 ). The total SOC loss during the three years of the experiment was 11.3 Mg ha -1 (25.6%). The simulation of SOC evolution with the model predicted a slower reduction of SOC, from 44.8 to 38.2 Mg ha -1 (6.6 Mg ha -1 , 14.6%) (Fig. 2 ), and lower annual mineralisation rates (Table 5 ) compared to observed values. However, the simulation of the period between autumn 2006 and autumn 2019 was very accurate, with a difference of only 200 kg ha -1 with observed SOC at the beginning of the experiment (Fig. 2 ). Table 5 Observed and simulated annual soil organic carbon (SOC) mineralisation rate (%) Year Observed SOC mineralisation rate (%) Simulated SOC mineralisation rate (%) Autumn 2019–2020 14.0 9.0 Autumn 2020–2021 8.7 3.7 Autumn 2021–2022 5.3 3.5 3.3. N balance and net soil N mineralisation NMn per crop ranged from 187.3 to 307.3 kg ha -1 with higher values for Aut-19 and Spr-19 crops (Table 6 ). Annual NMn was higher in 2019, 594 kg ha -1 , compared to 2021, with a NMn of 398.3 kg ha -1 . Tomato N uptake was the major component of the N mass balance for all crops and showed a decrease from 325.3 kg ha -1 in Aut-19 to 174.0 kg ha -1 in Spr-21. Aut-20 had lower N uptake than Aut-21, which was explained by the incidence of foliar diseases affecting crop growth. Nwater showed lower values for all tomato crops. N mineral showed high values for Aut-19 and Spr-19 but values above 3 kg ha -1 from Aut-20 onward. N leached ranged from 5.5 to 23.4 kg ha -1 . The primary source of N for plant growth was soil N mineralisation. N from mineralisation was 93%, 92%, 98%, 98% and 97% of total N balance outputs (Nuptake and Nleached) for Aut-19, Spr-19, Aut-20, Aut-21 and Spr-21, respectively. N in irrigation water only contributed to N balance inputs in the 0.4–2.9% range. The total N mineralisation during the five crop cycles evaluated was 1182.4 kg ha -1 . The total SOC loss during the three years of the experiment was 11.3 Mg ha -1 , resulting in a C:N ratio of 9.6. Table 6 Mass N balance components and net soil N mineralisation (NMn) for each tomato crop Crop Balance component (kg ha − 1 ) Aut-19 Spr-19 Aut-20 Aut-21 Spr-21 Ni 46.6 24.6 2.8 2.2 1.7 Nf 24.6 2.8 1.6 1.7 1.6 Nwater 1.4 2.5 2.9 3.2 5.6 Nuptake 325.3 298.1 178.7 191.3 174.0 Nleached 5.5* 12.8 15.6 23.4 19.0 NMn 307.3 286.6 190.2 211.0 187.3 *Nleached for Aut-19 was estimated considering the regression curve between N leaching and drainage (Berrueta et al., 2024 ). Drainage was calculated as the difference between total irrigation water and ETc obtained from the VegSyst model (Berrueta et al., 2023 ). N annual mineralisation rate estimated ranged from 4.6–8.0%. Higher values (8.0% and 7.4%) were observed in spring crops (Spr-19 and Spr-21, respectively) compared to autumn crops, with annual mineralisation rates of 6.4%, 4.6% and 5.8% for Aut-19, Aut-20 and Aut-21, respectively. These differences were related to growing season variation in air mean temperatures (Fig. 3 ). Spring crops showed 3 ºC more than autumn on average air temperature (Table 3 ). 3.4. Tomato yield and N utilisation efficiency Tomato yield decreased from 18 kg m -2 in Aut-19 and Spr-19 to 11–12 kg m -2 in the subsequent growing seasons (Table 7 ). The yield gap between actual yield and yield without nutrient limitations increased from 1.0 kg m -2 in Aut-19 to 6.4 kg m -2 in Spr-21. N utilisation efficiency ranged between 559 and 699 kg fruit per kg of N uptake. The concentration of N in plant biomass ranged between 2.23 and 2.85%. Higher N concentration was observed in Aut-19 and Spr-19. Table 7 Actual yield, yield without nutrient limitations, N utilisation efficiency and average N content in dry matter for each tomato crop. Aut-19 Spr-19 Aut-20 Aut-21 Spr-21 Actual yield (kg m − 2 ) 18.2 18.1 12.5 11.5 11.5 Yield without nutrient limitations (kg m − 2 ) * 19.2 20.7 15.2 14.9 17.9 N utilisation efficiency (kg fruit per kg of N uptake) 559.5 607.1 699.3 601.0 661.1 Average N content (%) 2.71 2.85 2.23 2.46 2.58 * Yield without nutrient limitation: tomato yield measured in Treatment 2 (see section 2.1). 4. Discussion 4.1. SOC mineralisation in greenhouse tomato production overcomes model predictions During 3 years of experiments with tomato monoculture (5 cycles in 3 years) grown in greenhouse conditions, SOC mineralisation measured was 11300 kg ha − 1 , decreasing by 25.6%. These values are significantly higher than SOC mineralisation measured in field-grown crops (Mazzili et al., 2015; Cortazzo, 2022 ; Frerichs and Daum, 2023 ). Observed SOC mineralisation was 57% above the simulated mineralisation rate estimated by a simulation model parameterised for open field cropping systems. Under intensive farming systems, the decrease in SOC is a major cause of soil fertility loss (Scotti et al., 2015 ). SOC plays a key role in the soil ecosystem. Decomposing microbes use SOC as substrates providing mineral nutrients to plants. SOC improves soil structure and porosity, increasing aeration and water holding capacity (Abiven et al., 2009 ), reduces heavy metal toxicity (Park et al., 2011 ) and contributes to natural suppressiveness of soil-borne diseases (Bonanomi et al., 2010 ). The loss of SOC can be associated to an imbalance between the amount of organic matter inputs and the amount of organic C outflows, mainly regulated by soil moisture, temperature and tillage (Parton et al., 1994 ; Scotti et al., 2015 ). Rapid SOC mineralisation under greenhouse systems could be due to i) higher soil temperatures, ii) the constant soil moisture and avoidance of soil water logging because of daily irrigation controlled by tensiometer and the use of plastic mulching, which provides favourable conditions for soil microbial and fungal activities (Aerts, 1997 ). Moreover, the intensive tillage (twice a year) promotes organic C mineralisation by favouring gas exchanges among different soil layers (Paustian et al., 2000 ) and by the breakdown of soil aggregates and, therefore, exposure of organic matter to microorganisms (Balesdent et al., 2000 , Kumar et al., 2012 ). All above-ground crop residues were completely removed from the greenhouse during the experiment, which is a common practice in greenhouses to limit phytopathological problems (Agrios, 2005 ). The limited fraction of plant debris that is integrated into the soil (e.g. dead roots, exudates and a fraction of the leaf litter) has high organic C biochemical quality due to low lignin content, abundant labile C fraction and low C:N ratio (Scotti et al., 2015 ) resulting in rapid mineralisation following incorporation (White et al., 2020 ). The experiment was conducted in fine-textured soil, typical of the southern region of Uruguay. Soil texture significantly influences SOC mineralisation because of substrate availability since clay protects it chemically and physically from decomposition (Hassink, 1994 ). Sandy soils, like those in the country’s northern region (Silvera and Barbazán, 2020 ), could present even higher SOC loss rates. SOC mineralisation rate decreased in subsequent years, from 14.0% in the first to 5.3% in the third year. The elevated SOC mineralisation rate in the first year could be related to previous crops cultivated in the plot under study. Annual winter and summer forage crops were rotated with four or five years of grass and legume pastures. These crops produce significant plant debris that was integrated into the soil before the experiment began and could increase the mineralisation rate during the first year after soil tillage (Chen et al., 2014 ). 4.2. Reduction of soil N supply and loss of crop yield Observed SOC depletion implied a reduction of soil N mineralisation to sustain tomato growth without N fertilisation. Mineralised N was 1182.4 kg ha − 1 during the experiment. NMn decreased from 2019 (594.0 kg ha − 1 year − 1 ) compared to 2021 with a NMn of 398.3 kg ha − 1 . Soil N mineralisation contributed to more than 90% of N outputs in the N mass balance. N leached was between 15.6 kg ha − 1 year − 1 and 42.4 kg ha − 1 year − 1 . The reduction in N availability for tomato growth in 2020 and 2021 caused a significant reduction in tomato yield. The tomato yield gap (to yield without nutrient limitations) increased from 5% in Aut-19 to 35% in Spr-21. These results coincide with what was obtained by Fu et al. ( 2017 ) for tomato monoculture. Vegetables production poses a significant challenge in terms of N management because crops require large quantities of N fertiliser to maximise yields. At the same time, vegetable production systems are highly vulnerable for SOC decrease and N mineralisation and also for N loss by lixiviation (Congreves and Van Eerd, 2015; Berrueta et al., 2024 ). It should be noted that the yields obtained in 2019 without applying fertilisers, both in autumn and spring, are close to the maximum attainable in the region (Berrueta et al., 2019 ), indicating the potential of a soil with high SOC content to sustain high yielding crops. Uncertainty in predicting N mineralisation from soil is a critical restriction to making precise fertiliser N recommendations for crops. We obtained annual N mineralisation rates between 4.6% and 8.0%, which varied according to the growing season. A higher N mineralisation rate was observed for spring crops (7.7% on average) than autumn (5.6% on average). This difference could be related to higher mean temperature during crop growth during spring crops. During the spring growing season, mean temperatures were 3 ºC higher than in autumn. Temperature plays a crucial role in N mineralisation because the enzymatic and chemical reactions during organic matter decomposition are highly temperature-dependent (Davidson and Janssens, 2006 ; Dessureault-Rompré et al., 2010 ; Frerichs and Daum, 2023 ). 4.3. Alternatives to avoid losses of SOC and N supply in greenhouse soils Identification of long-term sustainable management strategies is essencial to plan farming systems that efficiently maintain or increase soil health to improve crop yields and reduce input use, and to capture C and N in the soil (Lal, 2015 ). In this scenario, restoring depleted SOC and maintaining it at a satisfactory level is critical. Practices such as organic fertilisation (Triberti et al., 2008 ; Scotti et al., 2015 ), inclusion of green manure in crop rotations (Poeplau and Don, 2015 ) and incorporation of crop residues into soils (Lehtinen et al., 2014 ) sustain SOC level by increasing C input. The responsiveness to improved management practices is expected to be lower for soils with already high C reserves (Powlson et al., 2011 ; Alliaume et al., 2013 ; Minasny et al., 2017 ), mainly if soil C content is high in relation to the clay content (Merante et al., 2017 ). According to Hassink and Whitmore’s ( 1997 ) equation, the saturation SOC content according to the mineral composition of the soil and the content of clays that protect the SOC from microorganisms is 3.4% for the soil under study. SOC measured is far from saturation SOC content, even at the beginning of the experiment. There is ample room for C sequestration in the soil. Increasing interest arises in identifying organic amendments that can maximise the stable SOC recovery, with an improvement of soil health, while allowing adequate release of mineral nutrients to sustain crop yields in sustainable agricultural management (Scotty et al., 2015). Temperature and soil moisture depend largely on irrigation management and cannot be majorly modified under greenhouse cultivation systems. Thus, a suitable alternative is to control organic C quality (Scotty et al., 2013). Compost applications and green manure have proven to be useful practices to reduce the negative impact of intensive vegetable production on SOC (Jackson et al., 2004 ; Scotty et al., 2013; Cogger et al., 2016 ; White et al., 2020 ). Compost application is the most effective to increase total SOC stocks (White et al., 2020 ). However, high green manure frequency increased the proportion of labile C in the total SOC stock, potentially increasing nutrient availability and thus likely impacting crop yields more than compost (White et al., 2020 ). Organic amendments, especially those that increase the concentrations of easily available C in the soil, could increase soil N mineralisation rates (Kim et al., 2011 ). Reduced tillage can represent a sustainable tool for reducing C and N output and improving soil fertility in intensive agriculture (Alliaume et al.,2014; Scarlato et al., 2024 ). Long-term soil management studies involving plough-tillage and no-tillage practices, as well as undisturbed native soils, have demonstrated that tillage can cause a significant reduction in soil organic matter content and mineralisation of N and C (McCarty et al., 1995 ; Six et al.,1999; Kristensen et al., 2003 ). 5. Conclusions This study obtained SOC and N mineralisation measurements for greenhouse systems with tomato monoculture, a common system in greenhouses in Uruguay. SOC in 0-20cm soil layer decreased almost 26% in three years. This reduction implied lower levels of N supply from the soil, and with no N fertilisation, reduced tomato yield significantly. These estimates indicate the amount of organic matter required to maintain SOC and soil health and maintain N supply by soil to sustain crop growth. Maintaining SOC levels in the soil proved to be very important in reducing the need for fertiliser input to obtain high-yielding crops under intensive horticulture. Annual mineralisation rates vary according to the growing season and should be accounted for in better-estimating N supply by the soil to improve fertilisation plans, avoiding excess N synthetic fertilisation and making N leaching less likely. Declarations Funding: This work was supported by the Instituto Nacional de Investigación Agropecuaria (INIA) from Uruguay. Author Contribution C. B. led the field research and data curation. C.B. and S.D. did formal analysis and wrote the main manuscript. Both authors reviewed the manuscript. Acknowledgement The authors wish to thank all the Wilson Ferreira Aldunate experimental station (INIA Uruguay) field and laboratory staff for their excellent collaboration and assistance during field experiments. References Abiven, S., Menassero, S., Chenu, C., 2009. The effect of organic inputs over time on soil aggregate stability - a literature analysis. Soil Biol. Biochem. 41, 1-12. https://doi.org/10.1016/j.soilbio.2008.09.015. Aerts, R., 1997. Climate, leaf litter chemistry and leaf litter decomposition in terrestrial ecosystems: a triangular relationship. Oikos 79, 439-449. h ttps://doi.org/10.2307/3546886. Agrios, G.N., 2005. Plant diseases caused by fungi, in: Plant Pathology, fifth ed. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6058670","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":433988183,"identity":"fe1158b8-601b-49c0-bff1-8338659df3e6","order_by":0,"name":"Cecilia Berrueta","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA30lEQVRIiWNgGAWjYDACCRiDvbGBIYEULRIMPAdJ1iJBnHoGBv7Zzcc+V7bZ1PHPfNz24EENg5x5/wI2aR58ltw5ljzzbFuahMTtxHaDhGMMxjI3HuDXYiCRY8zY2HZYguF2YptEAhtD4gyJA4S05H8GavkvIX/zIFDLP6K05DADtRyQMLjB2CaR2AbUwt9A0C/GjA3nkiU3ngE6LLFPwlhCgrHZcg4eLcAQe8zYUGbHL3f8+DPJH99s5CT4Dx+88QaPFgxbgSixgQmfw7BZfICB8QdpWkbBKBgFo2B4AwBIbUeBCg0mrwAAAABJRU5ErkJggg==","orcid":"","institution":"Instituto Nacional de Investigación Agropecuaria","correspondingAuthor":true,"prefix":"","firstName":"Cecilia","middleName":"","lastName":"Berrueta","suffix":""},{"id":433988187,"identity":"bae870c7-9ddb-4da2-b72d-5076539c162e","order_by":1,"name":"Santiago Dogliotti","email":"","orcid":"","institution":"Universidad de la República","correspondingAuthor":false,"prefix":"","firstName":"Santiago","middleName":"","lastName":"Dogliotti","suffix":""}],"badges":[],"createdAt":"2025-02-18 19:23:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6058670/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6058670/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":79359275,"identity":"aad781df-5856-4a97-b462-0fe60df93796","added_by":"auto","created_at":"2025-03-27 12:04:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":30167,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic representation of raised beds with soil sampling area and lysimeters positions.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6058670/v1/14a6431cbfea649ad118cad6.png"},{"id":79360216,"identity":"e6e8abc6-51c2-4223-a233-595103919816","added_by":"auto","created_at":"2025-03-27 12:12:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":25581,"visible":true,"origin":"","legend":"\u003cp\u003eEvolution of observed and simulated soil organic carbon (SOC) (Mg ha\u003csup\u003e-1\u003c/sup\u003e) from June 2006 till February 2022\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6058670/v1/3f470539cbc532520a9519c9.png"},{"id":79360217,"identity":"a262421f-b5a8-4641-90b4-6d7d7feec222","added_by":"auto","created_at":"2025-03-27 12:12:06","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":17867,"visible":true,"origin":"","legend":"\u003cp\u003eN annual mineralisation rate according to mean air temperature for ( \u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;) autumn and (▲)spring crops.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6058670/v1/2df121dd695817271e0af066.png"},{"id":84258645,"identity":"f39df9a3-ee72-4848-b3d4-390a6df1f7b4","added_by":"auto","created_at":"2025-06-09 22:31:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1115563,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6058670/v1/2ed90e3d-1355-4bb0-a416-f3bba0c474fe.pdf"},{"id":79359276,"identity":"3a0762dc-8973-4e32-9566-9159b1e34b41","added_by":"auto","created_at":"2025-03-27 12:04:06","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":19655,"visible":true,"origin":"","legend":"","description":"","filename":"AppendixA.docx","url":"https://assets-eu.researchsquare.com/files/rs-6058670/v1/d823e29fcee4afb4d6550569.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Soil organic carbon and nitrogen mineralisation dynamics in successive greenhouse tomato crops","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSoil degradation is a major global challenge to developing sustainable agriculture. Over half of the agricultural land in the world is affected, moderately or severely by degradation processes (UNCCD, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The soil organic carbon (SOC) loss due to high soil erosion rates and intensive tillage is the main cause of soil degradation (Steiner, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Lal, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Haddaway et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The soil\u0026rsquo;s capacity to store water and soluble nutrients is associated with carbon (C) organic inputs and turnover. Furthermore, the recovery rate of degraded soil is also linked to stocks and flows of organic C (Neal et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). A decline in SOC causes reduced nitrogen (N) and water supply capacity, constituting important vegetable yield-limiting factors (Alliaume et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Understanding and modelling SOC dynamics is essential to prevent soil degradation and design management techniques to recover degraded soils. The loss of SOC is a significant sustainability problem for vegetable production systems in Uruguay (Dogliotti et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Soils under vegetable production in south Uruguay have lost between 44 and 54% of SOC, depending on soil type, compared to the historical reference (Alliaume et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eScientists worldwide have worked for decades to understand, model, and predict the SOC dynamics and the soil\u0026rsquo;s N supply capacity to plants in different agroecosystems, which are intimately linked. Plant-available N is a pillar of the performance and productivity of any agroecosystem. It is considered a continuum of inorganic and organic soluble N, with the latter composed of diverse structural complexity molecules, which cycle constantly (Dessureault-Rompr\u0026eacute;, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Optimising N cycling is related to improving the synchronicity between the plant requirement and soil N supply to reduce N losses. Enhancing the sustainability of agroecosystems involves optimising the N cycle.\u003c/p\u003e \u003cp\u003eThe N supply has been identified as a significant factor limiting greenhouse tomato yield in Uruguay, among other factors such as K nutrition and irrigation (Berrueta et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). On the other hand, NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e leaching to groundwater is more likely if the rate of NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e uptake by the crop is not great enough (Yuan et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). The greater the N excess, the greater the chance of NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e leaching from the upper soil layers to groundwater (Gheysari et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). In the north region of Uruguay, high levels of NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e were detected at 20\u0026ndash;40 cm depth in greenhouse soils (Silvera and Barbaz\u0026aacute;n, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and constitute a risk for groundwater. Berrueta et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) quantified N leaching rates between 12.8\u0026ndash;23.4 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e during two greenhouse tomato growing seasons (145\u0026ndash;190 days) in south Uruguay.\u003c/p\u003e \u003cp\u003eCrop N fertilisation depends on crop requirement and soil N availability. Soil texture, water content, temperature, pH, and cropping practices such as soil tillage determine the mineralisation of SOC and organic N (Griffin et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Laboratory incubations have been used to identify and hierarchize the physical and chemical soil properties affecting mineralisation, e.g. the SOC, pH, calcium carbonate content, soil texture and structure (Morvan et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, laboratory data do not accurately predict mineralisation under field conditions. Plant-soil interactions strongly affect mineralisation processes, such as soil microorganisms and mesofauna interactions, which are active in decomposition (Scheu, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) and the plant rhizodeposition effects on N mineralisation. Furthermore, variabilities in the environmental conditions that drive these processes also help to understand why laboratory incubation data are poor predictors of mineralisation under field conditions (Morvan et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These complexities justify studying and quantifying SOC and N mineralisation in the field.\u003c/p\u003e \u003cp\u003eMost fresh tomato production in Uruguay is done under greenhouses and cultivated directly on soil. The greenhouses mostly consist in low-cost structures build with wood and covered with plastic film. The predominant crop cycles are one crop per year (long cycle), transplanted mainly in September and ending in May or June, or two short crops per year (short Spring and Autumn cycles), the Spring cycle transplanted in August until January or February and the Autumn cycle transplanted in February and finished in July. The main reasons to do two short crops per year instead of one long cycle are to deal better with the systemic disease and nematodes and avoid the loss of quality of fruits and problems in fruit set during the summer period (January to February) (Berrueta et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study aims to determine the evolution of SOC and N mineralisation in greenhouse tomato monoculture (Uruguay\u0026rsquo;s primary tomato production system) over five tomato growing seasons by C and N mass balance. This knowledge will contribute to i) better estimation of N supply by soil in greenhouse crops to improve fertilisation plans, not only to improve yield but also to minimise environmental burden and fertilisers costs ii) planning of soil organic amendments to maintain SOC content and prevent soil degradation.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Experimental and cropping information\u003c/h2\u003e \u003cp\u003eThe three-year experiment was conducted in a greenhouse located at the National Institute of Agricultural Research station in Canelones (South of Uruguay) (34\u0026deg;40\u0026rsquo;S, 56\u0026deg;20\u0026rsquo;W and 32 m elevation). The average mean annual temperature in the region is 17\u0026deg;C. The greenhouse soil was classified as Luvic Phaeozems according to FAO classification (2006).\u003c/p\u003e \u003cp\u003eFive consecutive tomato crops (\u003cem\u003eSolanum lycopersicum\u003c/em\u003e L.): Aut-19, Spr-19, Aut-20, Aut-21, and Spr-21 grown in 2019, 2020, and 2021 were used for SOC and N balances (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The tomato cultivar used for spring crops was Lapataia, and the cultivar Elpida was used for autumn crops, as is typical for each growing season in commercial farms in the region. During spring 2020, the greenhouse remained bare fallow. The greenhouse was made of wood, 60 m long and 14.5 m wide (870 m\u003csup\u003e2\u003c/sup\u003e), and had a single gable roof structure covered with light-diffusing plastic film. The maximum height (ridge) was 4.5 m and the minimum (gutter) was 2 m. The greenhouse had passive lateral and ridge ventilation and north-south orientation. Before the greenhouse construction, the field was used for open-field vegetable production until 2008. From autumn 2008 to autumn 2018, annual winter and summer forage crops were rotated with four or five years of grass and legume pastures (two cycles of a 5 or 6 years rotation). In autumn 2018, the pasture was tilled, and the soil was left fallow during the greenhouse construction.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCultivar, dates, and growth period of tomato crops (south hemisphere)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCrop\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTransplanting date\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFirst harvest date\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEnd of crop date\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGrowth period (days)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAut-19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFeb 6, 19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eApr 29, 19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAug 12, 19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e187\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpr-19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAug 22, 19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNov 29, 19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eJan 23, 20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e154\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAut-20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFeb 10, 20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMay 5, 20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAug 18, 20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e190\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAut-21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFeb 01, 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eApr 19, 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAug 02, 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e182\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpr-21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAug 30, 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDec 2, 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eJan 22, 22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e145\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSeedlings were transplanted in raised beds at a plant density of 2.66 plants m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e (1.88 x 0.2 m) five weeks after sowing. The soil was tilled 15 days before transplanting each crop using a chisel plough, a disc harrow, and a disk hiller for putting up the raised beds. The raised beds were 90 cm wide and 20 cm high (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The soil was also tilled before the fallow period of autumn 2020. After tillage, the raised beds were covered with a white, 1.4 m width plastic mulch. Tomato plants were trained by tying up the main stem with nylon cords hanging from a steel wire 1.8 m in height, and suckers were periodically pruned. The top of the plants was pruned after the eighth cluster. The irrigation system consisted of drip tape on the soil surface, two paired lines per raised bed (5.3 dripper m\u003csup\u003e2\u003c/sup\u003e with a flow rate of 1 L h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). Irrigation was sheduled to keep the soil matric potential in the root zone within \u0026minus;\u0026thinsp;8 to \u0026minus;\u0026thinsp;12 kPa. Soil matric potential was measured daily with 12 tensiometers (Irrometer, Co., Riverside, USA) located at 20 cm depth in the middle of each plot.\u003c/p\u003e \u003cp\u003eThree treatments, consisting of different mineral fertilisation rates, were applied to each of the five tomato crops. In the control (T1), no fertilisers were added. T1 was the only treatment used for this study. The second treatment (T2) was fertirrigated with a complete nutrient solution to ensure that crop growth was not limited by macronutrients and micronutrients using nutrient total absorption, according to Ciampitti and Garc\u0026iacute;a (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). We did petiole sap tests every two weeks to check N and potassium levels and compared them to reference values (Hochmuth, 2015) to ensure that they were not limiting crop growth. The last treatment (T3) consisted of 50% more nitrogen applied compared to T2.\u003c/p\u003e \u003cp\u003eFor each trial, the experiment was conducted using a randomised complete block design with four replications. Plots measured 14 m long by 1.88 m width and contained one tomato plant row. Two blocks were located in the north part of the greenhouse and two to the south with a central path of 2.5 m along its east-west axis. The raised beds on the edges of the greenhouse were not included in the experiment and were left as borders.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Soil and greenhouse climate measurements\u003c/h2\u003e \u003cp\u003eThe top soil layer (0\u0026ndash;30 cm) was sampled before the Aut-19 crop to measure the silt, sand, and clay fraction by the modified pipette method (Maltoni and Aquino, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). To assess soil bulk density and the moisture retention curves, we took two undisturbed samples at 10\u0026ndash;15 cm depth per plot, using metal rings (5 cm length and 5.5 cm diameter) before the first tomato crop planting (January 2019). Bulk-density metal rings were oven-dried for 48 hours at 105 \u0026ordm;C. A soil profile was taken to measure the soil horizons and rooting depth. The soil top layer was 30 cm deep, and the textural class was silty clay loam (35% clay, 61% silt and 4% sand). The bulk density (5\u0026ndash;20 cm depth) at the beginning of the experiment (January 2019) was 1.19 Mg m\u003csup\u003e\u0026minus;\u0026thinsp;3,\u003c/sup\u003e and the available water was 13.91 mm 10 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eComposite soil samples in two depths (0\u0026ndash;20 and 20\u0026ndash;40 cm) were collected at the raised beds immediately before planting each tomato crop and at the end of Spr-21 crop. Mineral N (NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e \u0026ndash; N), organic C, pH, electrical conductivity (EC), and exchangeable Na\u003csup\u003e+\u003c/sup\u003e, Ca\u003csup\u003e++\u003c/sup\u003e, K\u003csup\u003e+\u003c/sup\u003e, and Mg\u003csup\u003e++\u003c/sup\u003e were analysed. Mineral N was measured by the nitrate electrode method (Gelderman and Beegle, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Organic C content was determined by sample dry combustion and subsequent detection of CO\u003csub\u003e2\u003c/sub\u003e by infrared (Wright and Bailey, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). The amounts of mineral N and organic C per ha were estimated using the initial bulk density (1.19 Mg m\u003csup\u003e-3\u003c/sup\u003e) and a soil volume of 1914.9 m\u003csup\u003e3\u003c/sup\u003e ha\u003csup\u003e-1\u003c/sup\u003e:\u003c/p\u003e \u003cp\u003eSoil volume (m\u003csup\u003e3\u003c/sup\u003e ha\u003csup\u003e-1\u003c/sup\u003e) = (10000 m\u003csup\u003e2\u003c/sup\u003e * raised beds width (m) / distance between rows (m)) * depth explored by roots (m) (1)\u003c/p\u003e \u003cp\u003eWhere,\u003c/p\u003e \u003cp\u003eRaised beds width (m)\u0026thinsp;=\u0026thinsp;0.9\u003c/p\u003e \u003cp\u003eDistance between rows (m)\u0026thinsp;=\u0026thinsp;1.88\u003c/p\u003e \u003cp\u003eDepth explored by roots (m)\u0026thinsp;=\u0026thinsp;0.4\u003c/p\u003e \u003cp\u003eGreenhouse air temperature and relative humidity were measured and recorded every 1 hour with a weather station (model Vantage Pro2, Davis Instruments, USA) located at the centre of the greenhouse placed 2 m above the ground. The daily radiation inside the greenhouse was estimated by multiplying outside solar radiation by greenhouse transmissivity. A pyranometer (model CS320, Campbell Scientific, UT, USA) located outside the greenhouse was used to record daily global radiation. We measured the greenhouse transmissivity for each trial at crop planting using a ceptometer (model LP-80, Decagon Devices Inc., Pullman, USA). On each measurement day, we took 16 measurements at different positions inside and outside the greenhouse, at 1.5 m above ground, three times (9:00, 12.00, and 16:00). Greenhouse transmissivity was assessed on sunny days.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Calculation of SOC mineralisation and model simulation of SOC\u003c/h2\u003e \u003cp\u003eThe amount of SOC mineralised per crop cycle was calculated as the difference between the amount of SOC at the beginning of one crop cycle and the next. The average SOC mineralisation rate was estimated as the difference between the initial and final SOC divided by the experiment length (3 years).\u003c/p\u003e \u003cp\u003eTo compare the SOC mineralisation rate under greenhouse and open-field cropping systems, we used a simulation model developed, calibrated and validated for open-field cropping systems in South Uruguay by Dogliotti et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). We simulated the evolution of soil organic matter in the top 20 cm of soil in the field where the greenhouse was built in 2018 from autumn 2006 till autumn 2021. The crops yields, residue yield ratios, initial conditions and parameters set used for the simulation are provided in detail in Appendix A.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Calculating Net Soil N Mineralisation from N mass balance\u003c/h2\u003e \u003cp\u003eTo determine the evolution of N mineralisation in greenhouse tomato monoculture over five tomato growing seasons, we carried an N mass balance for the control treatment (T1), applying Eq.\u0026nbsp;2. T1 had no manure application, and all above-ground crop residues were removed from the greenhouse. It was assumed that gaseous N losses were low and largely compensated by N symbiotic fixation and atmospheric deposition of N (Morvan et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNMn\u0026thinsp;+\u0026thinsp;Ni\u0026thinsp;+\u0026thinsp;Nwater\u0026thinsp;=\u0026thinsp;Nuptake\u0026thinsp;+\u0026thinsp;Nleached\u0026thinsp;+\u0026thinsp;Nf (2)\u003c/p\u003e \u003cp\u003eWhere,\u003c/p\u003e \u003cp\u003eNMn (kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u0026thinsp;=\u0026thinsp;mineralised soil N per crop season\u003c/p\u003e \u003cp\u003eNi (kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u0026thinsp;=\u0026thinsp;soil mineral N in the 0\u0026ndash;20 cm soil layer at transplanting\u003c/p\u003e \u003cp\u003eNf (kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u0026thinsp;=\u0026thinsp;soil mineral N in the 0\u0026ndash;20 cm soil layer at the end of crop cycle\u003c/p\u003e \u003cp\u003eNwater (kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u0026thinsp;=\u0026thinsp;N in water applied with crop irrigation\u003c/p\u003e \u003cp\u003eNuptake (kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u0026thinsp;=\u0026thinsp;Total N uptake by the crop\u003c/p\u003e \u003cp\u003eNleached (kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u0026thinsp;=\u0026thinsp;N leached as NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e during crop growth\u003c/p\u003e \u003cp\u003eNet soil N mineralisation was determined by N balance from Eq.\u0026nbsp;3, as follows:\u003c/p\u003e \u003cp\u003eNMn\u0026thinsp;=\u0026thinsp;Nuptake\u0026thinsp;+\u0026thinsp;Nleached\u0026thinsp;+\u0026thinsp;Nf \u0026ndash; Ni \u0026ndash; Nwater (3)\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.4.1. Estimation of tomato crop N uptake\u003c/h2\u003e \u003cp\u003eThe evolution of the above-ground biomass production throughout each crop cycle was assessed by destructive measurements of one plant per replicated plot every 20 days. Dry matter was measured by oven-drying leaves, stems and fruits at 65 \u003csup\u003e◦\u003c/sup\u003eC until constant weight. The biomass of all pruned shoot material and harvested fruits was determined in 10 plants per replicate plot throughout each crop cycle, and dry matter was determined as previously described for whole plant sampling. On average, seven whole-plant destructive measurements, 9 fruit harvests and 14 shoot prunings were conducted for each tomato crop. The total dry matter production was determined by adding the dry matter of leaves, stems, and immature fruits plus the accumulated dry weight of all pruned material and harvested fruits before the sampling date.\u003c/p\u003e \u003cp\u003eThe determination of dry matter N content (%) was done in finely ground samples of leaves, fruits and stems from the biomass samplings, harvested fruits, and pruned material using the Kjeldahl method. The N uptake was calculated as the product of the dry weight and N content. The above-ground crop N uptake was calculated for each biomass sampling as the sum of the N uptake of leaves, immature fruit, and stems plus the accumulated uptake of harvested fruits and all shoot material pruned before the sampling date. Below-ground crop N uptake was estimated as 4% of total N uptake (Khan and Sagar, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1969\u003c/span\u003e; Richards et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e1979\u003c/span\u003e; Scholberg et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) and was added to above-ground crop N uptake to estimate total crop N uptake.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.4.2. Estimation of N leached\u003c/h2\u003e \u003cp\u003eWater drainage was collected using three free draining lysimeters with 2 m long, 0.9 m wide and 1.4 m deep, located on the northern side of the greenhouse for Spr-19, Aut-20, Aut-21 and Spr-21. The soil profile in lysimeters was the same as the greenhouse soil described above. At the lysimeter bottom, a layer of gravel between geotextile meshes was used as a filter layer. Accumulated water drainage volumes were assessed 5 times per week. Once a week, representative sub-samples from each lysimeter drainage volume were analysed to determine the concentration of NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e by ion chromatography. N leaching was calculated as the product of N concentration and drainage volume. For Aut-19, lysimeters were not installed; thus, N leached was estimated using the equation proposed by Berrueta et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) (Eq.\u0026nbsp;4). Total drainage was calculated as the difference between total irrigation and crop evapotranspiration (ETc). ETc was estimated using the VegSyst model calibrated and validated for Uruguay (Berrueta et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eN leaching (kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u0026thinsp;=\u0026thinsp;0.2182 (total drainage (mm)) \u0026ndash; 0.1594 (4)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.4.3. Estimation of N in irrigation water\u003c/h2\u003e \u003cp\u003eThe volume of irrigation was measured daily for each treatment using volumetric meters. Samples of irrigation water were collected in January 2019, 2020, and 2021 to evaluate the concentrations of N - NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e, pH, and electrical conductivity (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The N applied through irrigation was calculated using the N concentrations and the total amount of irrigation applied during the crop growth period.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChemical characteristics of irrigation water (samples of January 2019, 2020 and 2021)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEC\u003csup\u003e*\u003c/sup\u003e (dS m\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN - NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e (mg N l\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e*Electrical conductivity\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Calculating N annual mineralisation rate\u003c/h2\u003e \u003cp\u003eThe N annual mineralisation rate was calculated using Eq.\u0026nbsp;5. The initial amount of organic N was calculated from the SOC content in the soil (0\u0026ndash;20 cm) and assuming a soil C:N ratio of 10:1.\u003c/p\u003e \u003cp\u003eN annual mineralisation rate (%) = (NMn/Organic N) * (365/Growth period) * 100 (5)\u003c/p\u003e \u003cp\u003eWhere,\u003c/p\u003e \u003cp\u003eN annual mineralisation rate (%) is the percentage of soil organic N mineralised per year to a 20 cm depth.\u003c/p\u003e \u003cp\u003eNMn (kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) is the net soil N mineralisation determined by N balance from Eq.\u0026nbsp;3.\u003c/p\u003e \u003cp\u003eOrganic N (kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) is the amount of soil organic N to a 20 cm depth estimated from the SOC content before transplanting of each crop and a C:N ratio of 10:1.\u003c/p\u003e \u003cp\u003eGrowth period (days) is each crop growth period as presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Tomato yield and N utilisation efficiency determinations\u003c/h2\u003e \u003cp\u003eTomato yield was determined by harvesting all mature fruits in 10 plants per plot for each trial. N utilisation efficiency (kg fruit kg N uptake\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) was estimated as the ratio between tomato yield (kg fruit ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and total N uptake (kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Soil and climate\u003c/h2\u003e \u003cp\u003eGreenhouse solar transmissivity measured were in the range of 60 and 64%, with the highest value for Aut-19 and the lowest for Spr-21. Significant differences in daily solar radiation and air temperature were observed between growing seasons. Spring crops showed higher average daily solar radiation and air temperature compare to autumn crops (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). For a given growing season (autumn and spring), average air temperature and daily solar radiation had no significant variation among years.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAverage air temperature (mean, minimum and maximum) and average daily solar radiation integral during each crop\u0026rsquo;s tomato growing season.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCrop\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eAir temperature (\u0026ordm; C)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAverage daily integral of solar radiation\u003c/p\u003e \u003cp\u003e(MJ m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMinimum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAut-19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpr-19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAut-20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAut-21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpr-21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe SOC at the beginning of the experiment was 1.93% and decreased by 26% during the experiments (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Mineral N at crop transplanting also decreased from 40 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in Aut-19 to 1.4 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in autumn 2022 (Aut-22). From Aut-20, mineral N remained below 3 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSoil organic carbon (SOC) and mineral nitrogen (N) at transplanting for each trial and at the end of the experiments in autumn 2022 (Aut-22)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAut-19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpr-19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAut-20\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAut-21\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSpr-21\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAut-22\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOC (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOC (Mg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e44.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e34.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e30.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e32.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMineral N (kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.2. SOC mineralisation\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eSOC decreased rapidly, from 44.0 Mg ha\u003csup\u003e-1\u003c/sup\u003e at the beginning of the experiment to 32.7 Mg ha\u003csup\u003e-1\u003c/sup\u003e at the end (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The annual SOC mineralisation rate was highest (14.0%) during the first year of the experiment, reducing to 8.7% and 5.3% in the subsequent years (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The total SOC loss during the three years of the experiment was 11.3 Mg ha\u003csup\u003e-1\u003c/sup\u003e (25.6%). The simulation of SOC evolution with the model predicted a slower reduction of SOC, from 44.8 to 38.2 Mg ha\u003csup\u003e-1\u003c/sup\u003e (6.6 Mg ha\u003csup\u003e-1\u003c/sup\u003e, 14.6%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), and lower annual mineralisation rates (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) compared to observed values. However, the simulation of the period between autumn 2006 and autumn 2019 was very accurate, with a difference of only 200 kg ha\u003csup\u003e-1\u003c/sup\u003e with observed SOC at the beginning of the experiment (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eObserved and simulated annual soil organic carbon (SOC) mineralisation rate (%)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObserved SOC\u003c/p\u003e \u003cp\u003emineralisation rate (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimulated SOC\u003c/p\u003e \u003cp\u003emineralisation rate (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAutumn 2019\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAutumn 2020\u0026ndash;2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAutumn 2021\u0026ndash;2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.3. N balance and net soil N mineralisation\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eNMn per crop ranged from 187.3 to 307.3 kg ha\u003csup\u003e-1\u003c/sup\u003e with higher values for Aut-19 and Spr-19 crops (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Annual NMn was higher in 2019, 594 kg ha\u003csup\u003e-1\u003c/sup\u003e, compared to 2021, with a NMn of 398.3 kg ha\u003csup\u003e-1\u003c/sup\u003e. Tomato N uptake was the major component of the N mass balance for all crops and showed a decrease from 325.3 kg ha\u003csup\u003e-1\u003c/sup\u003e in Aut-19 to 174.0 kg ha\u003csup\u003e-1\u003c/sup\u003e in Spr-21. Aut-20 had lower N uptake than Aut-21, which was explained by the incidence of foliar diseases affecting crop growth. Nwater showed lower values for all tomato crops. N mineral showed high values for Aut-19 and Spr-19 but values above 3 kg ha\u003csup\u003e-1\u003c/sup\u003e from Aut-20 onward. N leached ranged from 5.5 to 23.4 kg ha\u003csup\u003e-1\u003c/sup\u003e. The primary source of N for plant growth was soil N mineralisation. N from mineralisation was 93%, 92%, 98%, 98% and 97% of total N balance outputs (Nuptake and Nleached) for Aut-19, Spr-19, Aut-20, Aut-21 and Spr-21, respectively. N in irrigation water only contributed to N balance inputs in the 0.4\u0026ndash;2.9% range. The total N mineralisation during the five crop cycles evaluated was 1182.4 kg ha\u003csup\u003e-1\u003c/sup\u003e. The total SOC loss during the three years of the experiment was 11.3 Mg ha\u003csup\u003e-1\u003c/sup\u003e, resulting in a C:N ratio of 9.6.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMass N balance components and net soil N mineralisation (NMn) for each tomato crop\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eCrop\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBalance component (kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAut-19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpr-19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAut-20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAut-21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSpr-21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNwater\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNuptake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e325.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e298.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e178.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e191.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e174.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNleached\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.5*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNMn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e307.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e286.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e190.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e211.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e187.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e*Nleached for Aut-19 was estimated considering the regression curve between N leaching and drainage (Berrueta et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Drainage was calculated as the difference between total irrigation water and ETc obtained from the VegSyst model (Berrueta et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eN annual mineralisation rate estimated ranged from 4.6\u0026ndash;8.0%. Higher values (8.0% and 7.4%) were observed in spring crops (Spr-19 and Spr-21, respectively) compared to autumn crops, with annual mineralisation rates of 6.4%, 4.6% and 5.8% for Aut-19, Aut-20 and Aut-21, respectively. These differences were related to growing season variation in air mean temperatures (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Spring crops showed 3 \u0026ordm;C more than autumn on average air temperature (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Tomato yield and N utilisation efficiency\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTomato yield decreased from 18 kg m\u003csup\u003e-2\u003c/sup\u003e in Aut-19 and Spr-19 to 11\u0026ndash;12 kg m\u003csup\u003e-2\u003c/sup\u003e in the subsequent growing seasons (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). The yield gap between actual yield and yield without nutrient limitations increased from 1.0 kg m\u003csup\u003e-2\u003c/sup\u003e in Aut-19 to 6.4 kg m\u003csup\u003e-2\u003c/sup\u003e in Spr-21. N utilisation efficiency ranged between 559 and 699 kg fruit per kg of N uptake. The concentration of N in plant biomass ranged between 2.23 and 2.85%. Higher N concentration was observed in Aut-19 and Spr-19.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eActual yield, yield without nutrient limitations, N utilisation efficiency and average N content in dry matter for each tomato crop.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAut-19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpr-19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAut-20\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAut-21\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSpr-21\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActual yield (kg m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYield without nutrient limitations (kg m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e) \u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e17.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN utilisation efficiency (kg fruit per kg of N uptake)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e559.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e607.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e699.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e601.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e661.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage N content (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003csup\u003e*\u003c/sup\u003eYield without nutrient limitation: tomato yield measured in Treatment 2 (see section 2.1).\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.1. SOC mineralisation in greenhouse tomato production overcomes model predictions\u003c/h2\u003e \u003cp\u003eDuring 3 years of experiments with tomato monoculture (5 cycles in 3 years) grown in greenhouse conditions, SOC mineralisation measured was 11300 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, decreasing by 25.6%. These values are significantly higher than SOC mineralisation measured in field-grown crops (Mazzili et al., 2015; Cortazzo, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Frerichs and Daum, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Observed SOC mineralisation was 57% above the simulated mineralisation rate estimated by a simulation model parameterised for open field cropping systems. Under intensive farming systems, the decrease in SOC is a major cause of soil fertility loss (Scotti et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). SOC plays a key role in the soil ecosystem. Decomposing microbes use SOC as substrates providing mineral nutrients to plants. SOC improves soil structure and porosity, increasing aeration and water holding capacity (Abiven et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), reduces heavy metal toxicity (Park et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) and contributes to natural suppressiveness of soil-borne diseases (Bonanomi et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The loss of SOC can be associated to an imbalance between the amount of organic matter inputs and the amount of organic C outflows, mainly regulated by soil moisture, temperature and tillage (Parton et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Scotti et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Rapid SOC mineralisation under greenhouse systems could be due to i) higher soil temperatures, ii) the constant soil moisture and avoidance of soil water logging because of daily irrigation controlled by tensiometer and the use of plastic mulching, which provides favourable conditions for soil microbial and fungal activities (Aerts, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). Moreover, the intensive tillage (twice a year) promotes organic C mineralisation by favouring gas exchanges among different soil layers (Paustian et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) and by the breakdown of soil aggregates and, therefore, exposure of organic matter to microorganisms (Balesdent et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2000\u003c/span\u003e, Kumar et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). All above-ground crop residues were completely removed from the greenhouse during the experiment, which is a common practice in greenhouses to limit phytopathological problems (Agrios, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). The limited fraction of plant debris that is integrated into the soil (e.g. dead roots, exudates and a fraction of the leaf litter) has high organic C biochemical quality due to low lignin content, abundant labile C fraction and low C:N ratio (Scotti et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) resulting in rapid mineralisation following incorporation (White et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe experiment was conducted in fine-textured soil, typical of the southern region of Uruguay. Soil texture significantly influences SOC mineralisation because of substrate availability since clay protects it chemically and physically from decomposition (Hassink, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). Sandy soils, like those in the country\u0026rsquo;s northern region (Silvera and Barbaz\u0026aacute;n, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), could present even higher SOC loss rates.\u003c/p\u003e \u003cp\u003eSOC mineralisation rate decreased in subsequent years, from 14.0% in the first to 5.3% in the third year. The elevated SOC mineralisation rate in the first year could be related to previous crops cultivated in the plot under study. Annual winter and summer forage crops were rotated with four or five years of grass and legume pastures. These crops produce significant plant debris that was integrated into the soil before the experiment began and could increase the mineralisation rate during the first year after soil tillage (Chen et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Reduction of soil N supply and loss of crop yield\u003c/h2\u003e \u003cp\u003eObserved SOC depletion implied a reduction of soil N mineralisation to sustain tomato growth without N fertilisation. Mineralised N was 1182.4 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e during the experiment. NMn decreased from 2019 (594.0 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003eyear\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) compared to 2021 with a NMn of 398.3 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Soil N mineralisation contributed to more than 90% of N outputs in the N mass balance. N leached was between 15.6 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e year\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 42.4 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e year\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The reduction in N availability for tomato growth in 2020 and 2021 caused a significant reduction in tomato yield. The tomato yield gap (to yield without nutrient limitations) increased from 5% in Aut-19 to 35% in Spr-21. These results coincide with what was obtained by Fu et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) for tomato monoculture. Vegetables production poses a significant challenge in terms of N management because crops require large quantities of N fertiliser to maximise yields. At the same time, vegetable production systems are highly vulnerable for SOC decrease and N mineralisation and also for N loss by lixiviation (Congreves and Van Eerd, 2015; Berrueta et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). It should be noted that the yields obtained in 2019 without applying fertilisers, both in autumn and spring, are close to the maximum attainable in the region (Berrueta et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), indicating the potential of a soil with high SOC content to sustain high yielding crops.\u003c/p\u003e \u003cp\u003eUncertainty in predicting N mineralisation from soil is a critical restriction to making precise fertiliser N recommendations for crops. We obtained annual N mineralisation rates between 4.6% and 8.0%, which varied according to the growing season. A higher N mineralisation rate was observed for spring crops (7.7% on average) than autumn (5.6% on average). This difference could be related to higher mean temperature during crop growth during spring crops. During the spring growing season, mean temperatures were 3 \u0026ordm;C higher than in autumn. Temperature plays a crucial role in N mineralisation because the enzymatic and chemical reactions during organic matter decomposition are highly temperature-dependent (Davidson and Janssens, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Dessureault-Rompr\u0026eacute; et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Frerichs and Daum, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Alternatives to avoid losses of SOC and N supply in greenhouse soils\u003c/h2\u003e \u003cp\u003eIdentification of long-term sustainable management strategies is essencial to plan farming systems that efficiently maintain or increase soil health to improve crop yields and reduce input use, and to capture C and N in the soil (Lal, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). In this scenario, restoring depleted SOC and maintaining it at a satisfactory level is critical. Practices such as organic fertilisation (Triberti et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Scotti et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), inclusion of green manure in crop rotations (Poeplau and Don, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and incorporation of crop residues into soils (Lehtinen et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) sustain SOC level by increasing C input. The responsiveness to improved management practices is expected to be lower for soils with already high C reserves (Powlson et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Alliaume et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Minasny et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), mainly if soil C content is high in relation to the clay content (Merante et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). According to Hassink and Whitmore\u0026rsquo;s (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e1997\u003c/span\u003e) equation, the saturation SOC content according to the mineral composition of the soil and the content of clays that protect the SOC from microorganisms is 3.4% for the soil under study. SOC measured is far from saturation SOC content, even at the beginning of the experiment. There is ample room for C sequestration in the soil.\u003c/p\u003e \u003cp\u003eIncreasing interest arises in identifying organic amendments that can maximise the stable SOC recovery, with an improvement of soil health, while allowing adequate release of mineral nutrients to sustain crop yields in sustainable agricultural management (Scotty et al., 2015). Temperature and soil moisture depend largely on irrigation management and cannot be majorly modified under greenhouse cultivation systems. Thus, a suitable alternative is to control organic C quality (Scotty et al., 2013). Compost applications and green manure have proven to be useful practices to reduce the negative impact of intensive vegetable production on SOC (Jackson et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Scotty et al., 2013; Cogger et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; White et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Compost application is the most effective to increase total SOC stocks (White et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, high green manure frequency increased the proportion of labile C in the total SOC stock, potentially increasing nutrient availability and thus likely impacting crop yields more than compost (White et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Organic amendments, especially those that increase the concentrations of easily available C in the soil, could increase soil N mineralisation rates (Kim et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eReduced tillage can represent a sustainable tool for reducing C and N output and improving soil fertility in intensive agriculture (Alliaume et al.,2014; Scarlato et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Long-term soil management studies involving plough-tillage and no-tillage practices, as well as undisturbed native soils, have demonstrated that tillage can cause a significant reduction in soil organic matter content and mineralisation of N and C (McCarty et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Six et al.,1999; Kristensen et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThis study obtained SOC and N mineralisation measurements for greenhouse systems with tomato monoculture, a common system in greenhouses in Uruguay. SOC in 0-20cm soil layer decreased almost 26% in three years. This reduction implied lower levels of N supply from the soil, and with no N fertilisation, reduced tomato yield significantly. These estimates indicate the amount of organic matter required to maintain SOC and soil health and maintain N supply by soil to sustain crop growth. Maintaining SOC levels in the soil proved to be very important in reducing the need for fertiliser input to obtain high-yielding crops under intensive horticulture. Annual mineralisation rates vary according to the growing season and should be accounted for in better-estimating N supply by the soil to improve fertilisation plans, avoiding excess N synthetic fertilisation and making N leaching less likely.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis work was supported by the Instituto Nacional de Investigaci\u0026oacute;n Agropecuaria (INIA) from Uruguay.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eC. B. led the field research and data curation. C.B. and S.D. did formal analysis and wrote the main manuscript. Both authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors wish to thank all the Wilson Ferreira Aldunate experimental station (INIA Uruguay) field and laboratory staff for their excellent collaboration and assistance during field experiments.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAbiven, S., Menassero, S., Chenu, C., 2009. The effect of organic inputs over time on soil aggregate stability - a literature analysis. Soil Biol. Biochem. 41, 1-12. https://doi.org/10.1016/j.soilbio.2008.09.015.\u003c/li\u003e\n \u003cli\u003eAerts, R., 1997. Climate, leaf litter chemistry and leaf litter decomposition in terrestrial ecosystems: a triangular relationship. Oikos 79, 439-449. h\u003cu\u003ettps://doi.org/10.2307/3546886.\u003c/u\u003e\u003c/li\u003e\n \u003cli\u003eAgrios, G.N., 2005. Plant diseases caused by fungi, in: Plant Pathology, fifth ed. 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Winter cover crops increase readily decomposable soil carbon, but compost drives total soil carbon during eight years of intensive, organic vegetable production in California. \u003cem\u003ePLoS One\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e(2), p.e0228677. https://doi.org/10.1371/journal.pone.0228677.\u003c/li\u003e\n \u003cli\u003eWright, A.F., Bailey, J.S., 2001. Organic carbon, total carbon, and total nitrogen determinations in soils of variable calcium carbonate contents using a Leco CN-2000 dry combustion analyser. Commun. Soil Sci. Plant Anal. 32(19-20), 3243-3258. https://doi.org/10.1081/CSS-120001118.\u003c/li\u003e\n \u003cli\u003eYuan, X.M., Tong, Y.A., Yang, X.Y., Li, X.L., Zhang, F.S., 2000. Effect of organic manure on soil nitrate nitrogen accumulation. Soil Environ. Sci. 9, 197\u0026ndash;200.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Solanum lycopersicum, Nitrogen supply, Soil degradation, Mineralisation rate","lastPublishedDoi":"10.21203/rs.3.rs-6058670/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6058670/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eUnderstanding and predicting soil organic carbon (SOC) dynamics and the capacity of soil to supply nitrogen (N) to plants agroecosystems has been widely addressed. Many soil properties like texture, moisture, temperature, pH, and cropping practices such as tillage modify SOC and organic N dynamics. This complexity justifies quantifying SOC and N mineralisation in the field. This study aims to determine the evolution of SOC and N mineralisation in greenhouse tomato monoculture over five tomato growing seasons. The amount of SOC mineralised per crop cycle was assessed as the difference between the amount of SOC at the beginning of one crop cycle and the next. SOC mineralisation rate was compared with mineralisation in open-field cropping systems simulated by a model calibrated and validated in Uruguay. An N mass balance was carried out to determine the evolution of N mineralisation and the net soil N mineralisation. Rapid SOC mineralisation under greenhouse systems was evidenced. The total SOC loss during the three years of the experiment was 11.3 Mg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (25.6%), overcoming open-field model predictions (6.6 Mg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 14.6%). Annual mineralised soil N (NMn) was higher in 2019, 594 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, compared to 2021 (398.3 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and was the primary source of N for plant growth. We obtained annual N mineralisation rates between 4.6% and 8.0%, which varied according to the growing season. A higher N mineralisation rate was observed for spring crops with higher temperatures than autumn. SOC and N mineralisation depletion without fertilisation causes a significant reduction in tomato yield. This knowledge will contribute to estimating better soil N supply in greenhouse crops to improve fertilisation plans, not only to improve crop yield but also to minimise environmental burden and fertiliser costs. In addition, soil organic amendments should be planned to maintain SOC content and prevent soil degradation.\u003c/p\u003e","manuscriptTitle":"Soil organic carbon and nitrogen mineralisation dynamics in successive greenhouse tomato crops","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-27 12:04:01","doi":"10.21203/rs.3.rs-6058670/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2e1d4637-d6f9-4700-8113-6a6af038b1bf","owner":[],"postedDate":"March 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":46212497,"name":"Earth and environmental sciences/Biogeochemistry/Carbon cycle"},{"id":46212498,"name":"Earth and environmental sciences/Biogeochemistry/Element cycles"}],"tags":[],"updatedAt":"2025-06-09T22:23:20+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-27 12:04:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6058670","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6058670","identity":"rs-6058670","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}