Ammonia (NH3) from intensive agriculture is a primary precursor for secondary fine particulate matter (PM2.5), necessitating mitigation under the EU National Emission Ceilings (NEC) Directive. This study evaluated a novel feed-based intervention assessed under real-scale commercial conditions in weaning and growing pig units. Indoor NH3 concentrations were monitored at high frequency (2 h resolution), and treatment effects were analyzed using a Circular Block Bootstrap (CBB) approach to account for diurnal cyclicity and temporal autocorrelation. In the weaning unit, where pits were fully emptied before the trial, the mean indoor NH3 concentration decreased from 7.51 ppm to 1.37 ppm, representing an 81.7% reduction. In the growing unit, which operated under pre-existing slurry and an overflow system, a significant reduction of 20.9% was observed (from 5.45 ppm to 4.31 ppm). These results demonstrate the intervention’s efficacy in preventing NH3 release from fresh excreta and suggest that its impact in systems managed under slurry overflow can be further optimized by initially activating pre-existing material. This infrastructure-free solution offers a scalable, economically sustainable pathway to align livestock production with zero-pollution targets while supporting multiple Sustainable Development Goals related to human health, worker welfare, and environmental protection.

Ammonia (NH3) is a major anthropogenic pollutant originating from agricultural activity, particularly livestock operations. NH3 emissions from livestock slurry storage pose risks to environmental quality and human health. Reducing NH3 emissions aligns with several United Nations Sustainable Development Goals (SDGs), including SDG 3, SDG 12, SDG 14, and SDG 15. This study evaluates the performance of the commercially available SOP® LAGOON additive under real-scale farm conditions for mitigating NH3 emissions. Two adjacent slurry storage tanks of a dairy farm in Northern Italy were monitored from 27 May to 7 September: one treated with SOP® LAGOON and one left untreated (serving as a control). In the first month, the treated tank showed a 77% reduction in NH3 emissions. Emissions from the treated tank remained consistently lower than those from the control throughout the monitoring period, reaching an 87% reduction relative to the baseline levels by the end of the period. The results suggest that SOP® LAGOON is an effective and scalable strategy for reducing NH3 emissions from liquid manure storage, with practical implications for farmers and policy makers in regard to designing sustainable manure management practices.

Grapevine is one of the most important perennial fruit crops worldwide, and it is particularly impacted by the effects of climate change. This study evaluated the commercial natural fertilizer Resonant - SOP Inside Fortify White in two commercial vineyards, focusing on its impact on vine growth, yield, and grape quality. The findings show that treated vines consistently exhibited enhanced vegetative growth, evidenced by significantly longer shoots (increases ranging from +11 % to +50 %) and reduced occurrence of blind buds along the fruiting cane. Furthermore, an increased leaf area and leaf chlorophyll content, alongside improved water stress tolerance was measured. Additionally, pruning wood amounts were higher for treated vines in both vineyards, +40 % and +13 %. At harvest, treated vines showed higher yield per vine, +16 % in both sites, compared to untreated vines, with comparable TSS, pH, acidity and with increased YAN values (+63 % and +61 %). The findings of this study suggest that the application of the natural fertilizer Resonant - SOP Inside Fortify White may represent a sustainable solution to optimize nitrogen absorption, vine balance, and yield without compromising grape quality.

Reducing methane (CH4) is a key objective to address climate change quickly. Manure management and storage play a significant role. In this context, a real-scale trial was performed to measure the ability of the commercial additive SOP LAGOON to reduce carbon-based greenhouse gas (GHG) emissions from liquid manure over approximately 4 months. Gas emissions were measured at a commercial dairy farm from two slurry tanks, one treated with the abovementioned product (SL) and the other used as the untreated control (UNT). After 3 and 4 months from the first additive applications, the SL storage tank showed lower and statistically significantly different emissions concerning the UNT (up to −80% for CH4 and −75% for CO2, p < 0.001), confirming and showing improved results from those reported in the previous small-scale works. The pH of the UNT tank was lower than that of the SL on two dates, while the other chemical characteristics of the slurry were not affected. In this work, SOP LAGOON proved to be an effective additive to help the farmers mitigate the contribution of stored liquid manure to global CH4 emissions, potentially improving the overall sustainability of the dairy industry.

Introducing smart and sustainable tools for climate change adaptation and mitigation is a major need to support agriculture’s productivity potential. We assessed the effects of the processed gypsum seed dressing SOP® COCUS MAIZE+ (SCM), combined with a gradient of N fertilization rates (i.e., 0%, 70% equal to 160 kg N ha−1, and 100% equal to 230 kg N ha−1) in maize (Zea mays L.), on: (i) grain yield, (ii) root length density (RLD) and diameter class length (DCL), (iii) biodiversity of soil bacteria and fungi, and (iv) Greenhouse Gases (GHGs, i.e., N2O, CO2, and CH4) emission. Grain yield increased with SCM by 1 Mg ha−1 (+8%). The same occurred for overall RLD (+12%) and DCL of very fine, fine, and medium root classes. At anthesis, soil microbial biodiversity was not affected by treatments, suggesting earlier plant-rhizosphere interactions. Soil GHGs showed that (i) the main driver of N losses as N2O is the N-fertilization level, and (ii) decreasing N-fertilization in maize from 100% to 70% decreased N2O emissions by 509 mg N-N2O m−2 y−1. Since maize grain yield under SCM with 70% N-fertilization was similar to that under Control with 100% N-fertilization, we concluded that under our experimental conditions SCM may be used for reducing N input (−30%) and N2O emissions (−23%), while contemporarily maintaining maize yield. Hence, SCM can be considered an available tool to improve agriculture’s alignment to the United Nation Sustainable Development Goals (UN SDGs) and to comply with Europe’s Farm to Fork strategy for reducing N-fertilizer inputs.

Ammonia and odour emissions from one lagoon (Lagoon 1: pig slurry) and three tanks (Tank 2: cow slurry; Tank 3: digestate from pig slurry and energy crops; Tank 4: digestate from pig and cow slurries plus energy crop) used for slurry storage were sampled for two years (2015-2017) in livestock farms that differed for animal breeding and manure management (anaerobic digestion). On average, the ammonia emission rate (AER) was higher for Tank 3 (AER of 30.68 +/- 28.1 g N-NH3 m(-2) d(-1)) than for Lagoon 1 and Tank 2 and 4, i.e. 9.29 +/- 14.89 gN-NH3 m(-2) d(-1), 9.38 +/- 13.75 g N-NH3 m(-2) d(-1), 15.74 +/- 21.91 g N-NH3 m(-2) d(-1), respectively. PLS regression analysis (R-2 = 0.544; R-Adj.(2) = 0.484) indicated that temperature was the main predictor of ammonia emitted, followed by concentration in the slurry of total ammonia and the relative percentage of volatile solids (VS). On the other hand, PLS analysis (R-2 = 0.529, R-adj.(2) = 0.417) indicated that odour emissions from animal slurry storages depended similarly upon total solids and VS (both referred to fresh weight) slurry contents, TAN/TKN ratio and degrees of biological stability (measured by anaerobic biogas potential - ABP), resulting in the Specific Odours Emission Rates (SOER) of 12,124 +/- 7,914 and 35,207 +/- 41,706 OUE m(-2) h(-1), 65,430 +/- 45,360 and 43,971 +/- 53,350 OUE m(-2) h(-1), for Lagoon 1 and Tanks 2, 3 and 4. These results suggest covering the tanks to limit both ammonia and odour emissions. (C) 2019 Elsevier Ltd. All rights reserved.

Feed additives have received increasing attention as a viable means to reduce enteric emissions from ruminants, which contribute to total anthropogenic methane (CH4) emissions. The aim of this study was to investigate the efficacy of the commercial feed additive SOP STAR COW (SOP) to reduce enteric emissions from dairy cows and to assess potential impacts on milk production. Twenty cows were blocked by parity and days in milk and randomly assigned to one of two treatment groups (n = 10): supplemented with 8 g/day SOP STAR COW, and an unsupplemented control group. Enteric emissions were measured in individual head chambers over a 12-h period, every 14 days for six weeks. SOP-treated cows over time showed a reduction in CH4 of 20.4% from day 14 to day 42 (p = 0.014), while protein % of the milk was increased (+4.9% from day 0 to day 14 (p = 0.036) and +6.5% from day 0 to day 42 (p = 0.002)). However, kg of milk protein remained similar within the SOP-treated cows over the trial period. The control and SOP-treated cows showed similar results for kg of milk fat and kg of milk protein produced per day. No differences in enteric emissions or milk parameters were detected between the control and SOP-treated cows on respective test days.

The agricultural area in the Po Valley is prone to high nitrous oxide (N2O) emissions as it is characterized by irrigated maize-based cropping systems, high amounts of nitrogen supplied, and elevated air temperature in summer. Here, two monitoring campaigns were carried out in maize fertilized with raw digestate in a randomized block design in 2016 and 2017 to test the effectiveness of the 3, 4 DMPP inhibitor Vizura® on reducing N2O-N emissions. Digestate was injected into 0.15 m soil depth at side-dressing (2016) and before sowing (2017). Non-steady state chambers were used to collect N2O-N air samples under zero N fertilization (N0), digestate (D), and digestate + Vizura® (V). Overall, emissions were significantly higher in the D treatment than in the V treatment in both 2016 and 2017. The emission factor (EF, %) of V was two and four times lower than the EF in D in 2016 and 2017, respectively. Peaks of NO3-N generally resulted in N2O-N emissions peaks, especially during rainfall or irrigation events. The water-filled pore space (WFPS, %) did not differ between treatments and was generally below 60%, suggesting that N2O-N emissions were mainly due to nitrification rather than denitrification.

An evaluation of the effect of the conservation agriculture (CA) on agro-environmental aspects is needed at the farm scale in intensive production systems, which are likely prone to reduce soil fertility. Here, as part of the HelpSoil LIFE + Project and involving 20 farms in the Po valley (Northern Italy), we have estimated the soil organic carbon (SOC) content, SOC stock, crop yield, biological fertility, soil biodiversity, and economic efficiency under different agricultural systems (CA and conventional, CvtA) at the beginning (March 2014) and end (October 2016) of the experimental period. CA was mostly represented by no-till practice (NT) coupled with the cultivation of winter cover crops. Minimum tillage (MT) was considered as CA or CvtA practice according to the farm design. The CA practices have been implemented on the monitored farms at different times (Long-term = before 2006, Medium-term = between 2006 and 2013, Short-term = after 2013). A direct comparison between CA and CvtA of soil-related variables, yields, and costs was performed on 14 out of the 20 farms; data were statistically treated with a linear mixed model. Overall, CA resulted in significantly higher SOC content, SOC stock, biological fertility, QBS-ar, and earthworms for the Medium-term group. Considering the effect of tillage practices observed on the 20 farms, SOC content was the highest in NT for the Long-term group. The biological fertility index was higher in NT and MT compared to CvtA within the Long-term and Medium-term groups in 2016. QBS-ar was the higher in MT and NT than CvtA for the Long-term and Medium-Term groups. The number of earthworms was the highest under NT for the Long-term group. Maize, winter wheat, and soybeans yields were generally 1 t ha(-1) higher in CvtA than in CA, but this did not reach statistical significance. The cost for herbicides was 18% more expensive in NT, whereas the fuel consumption and total costs for weeding operations did not differ between NT and CvtA. The overall outcome of the analysis was that CA is a viable solution for intensive farms in the monitored area, but further skills need still to be acquired in to enhance its economic feasibility.

A two-year experiment was carried out in a paddy field to investigate the effects of the use of defecation lime derived from treated sewage sludge on soil total and soil phytoavailable heavy metals concentration.Heavy metals concentration was determined also in raw rice.Four treatments were arranged in a completely randomized block design: not fertilised (T0), organic fertilisation + chemical fertilisers (T1), defecation lime + chemical fertilisers (T2), defecation lime at pre-sowing (T3).For T3, the pH value increased significantly at the end of the second year, increasing from 5.8 to 6.11.T3 resulted in the highest soil organic carbon content (9.4 g kg -1 ), suggesting the potential of defecation lime both as soil corrective material and soil amendment.The application of defecation lime in the paddy field did not result in an increased phytoavailable amount of heavy metals in soil.

Rapeseed is one of the most important sources of vegetable oils, and its cultivation in Europe is expanding due to the economic incentives to grow energy crops. Given the unique characteristics of this crop, simulation studies targeting yield predictions and scenario analysis should be performed using specific models rather than using generic crop simulators adapted to rapeseed via calibration. This study presents a new model - WOFOST-GTC - which implements a dynamic representation of the rapeseed canopy architecture and includes modelling approaches to simulate oil content and composition. We reduced the number of model parameters to 35, compared to the 97 parameters of the original WOFOST model, from which it derives. WOFOST-GTC was developed using data collected in dedicated field experiments carried out in northern Italy in 2012-2013. The model ability to reproduce the underlying processes was evaluated using data collected in Europe between 1993 and 2013. In particular, dynamics involved with production and oil quality were evaluated on 7 and 18 datasets, respectively. The aboveground biomass and photosynthetic area index at different depths in the canopy were accurately simulated (R-2 = 0.86 and 0.78, respectively). Despite the lower complexity, WOFOST-GTC proved to be as accurate as the original WOFOST model. The simulation of the seed oil content (R-2 = 0.76) and of the oleic (R-2 = 0.95), linoleic (R-2 = 0.88) and alpha-linolenic acid (R-2 = 0.95) fractions was accurate. Hence, we propose WOFOST-GTC as a suitable simulation model to analyse the rapeseed production and oil quality under different weather and management scenarios. (C) 2016 Elsevier B.V. All rights reserved.

The lack of standardized information on the evaluation of in vivo field methods is an important source of uncertainty in the interpretation of field data. The same words precision and accuracy can be frequently found in the agronomic and ecological literature, although often used without a real attempt to give these terms rigorous and shared meanings. On the contrary, standard protocols for determining accuracy and precision of analytical methods were successfully proposed in the last two decades and are now routinely used, especially within the chemical community. A first attempt to compile a standard guideline for in vivo field methods, derived by adapting the ISO 5725 protocol for the validation of analytical methods, is here presented. The concepts of levels, reference material, and inter-laboratory test derived from the protocol are redefined, and the underlying assumptions behind the adaptation of the ISO norm are introduced and discussed. Applicability and effectiveness of the proposed procedure are shown by means of a case study where the accuracy -i.e., trueness and precision, the latter composed by repeatability and reproducibility of two diagnostic methods for indirect estimates of plant nitrogen nutritional status (chlorophyll meter and leaf color chart) was determined. The chlorophyll meter was more precise than leaf color chart, with precision value expressed as relative standard deviations lower than 6%. On the other hand, trueness indices showed better performances for leaf color chart, thus demonstrating the suitability of this method for supporting low-income farmers in managing topdressing fertilization, although at the price of performing a large number of reading replicates. However, these results are not aimed at drawing conclusions on techniques for supporting fertilization: the one presented is indeed just a case study used to assess the possibility of adopting the proposed procedure, as well as to highlight potential limits for its application. In this regard, the identification of reference values needed for trueness quantification is surely the most delicate issue, since the absence of conventional true values leads to the need of finding the most suitable solution according to the specific variable investigated and to the specific contexts in which the method under evaluation is applied. Hence, in light of both the encouraging results and the underlined limits, we just aim here at opening a discussion on the need for standardizing approaches and terminology for the evaluation of indirect field methods. (c) 2014 Elsevier B.V. All rights reserved.

ABSTRACTPlant height has a deep influence on the productivity of many crops, as it involves susceptibility to lodging, crop–weed competition, and the achievement of favorable harvest index. Nevertheless, modellers have practically ignored related ecophysiological processes, especially those modulated by management practices. The aim of this study was to analyze and model the processes involved with the effects of management on rice (Oryza sativa L.) elongation. Data were collected in two greenhouse experiments (2010–2011) where three factors (floodwater level, N fertilization, sowing density) were arranged in a split‐plot design with three replicates. The model proposed demonstrated its suitability in reproducing both the dynamics involved with tissue elongation in the different phenological phases and the effects of submergence and N luxury consumption on elongation rates. Relative root mean square error (RRMSE) ranged between 4.23 and 12.41% for different treatments and years. The inclusion of algorithms for the impact of agronomic practices on plant height in cropping system models would increase their suitability for scenario analyses and for in silico ideotyping studies, owing to the great interest shown by geneticists in related traits. Moreover, this study—performed with students of a Cropping Systems MS course—demonstrated once more the power of modeling within educational activities. In this case, models were not the subject of the teaching but tools for analyzing processes and formalizing new knowledge.

•We present the decision support system ValorE for livestock manure management.•Manure production, storage, treatment and land application domains are included.•Users and stakeholders can carry out comparative analysis at farm or territorial scale.•Different scenarios can be described by multidisciplinary indicators and by maps.•It is a complete tool for improving both farm strategy and decision making process.

The expected climate change will affect the maize yields in view of air temperature increase and scarce water availability. The application of biophysical models offers the chance to design a drought-resistant ideotype and to assist plant breeders and agronomists in the assessment of its suitability in future scenarios. The aim of the present work was to perform a model-based estimation of the yields of two hybrids, current vs ideotype, under future climate scenarios (2030-2060 and 2070-2100) in Lombardy (northern Italy), testing two options of irrigation (small amount at fixed dates vs optimal water supply), nitrogen (N) fertilization (300 vs 400 kg N ha(-1)), and crop cycle durations (current vs extended). For the designing of the ideotype we set several parameters of the ARMOSA process-based crop model: the root elongation rate and maximum depth, stomatal resistance, four stage-specific crop coefficients for the actual transpiration estimation, and drought tolerance factor. The work findings indicated that the current hybrid ensures good production only with high irrigation amount (245-565 mm y(-1)). With respect to the current hybrid, the ideotype will require less irrigation water (-13%, p<0.01) and it resulted in significantly higher yield under water stress condition (+15%, p<0.01) and optimal water supply (+2%, p<0.05). The elongated cycle has a positive effect on yield under any combination of options. Moreover, higher yields projected for the ideotype implicate more crop residues to be incorporated into the soil, which are positively correlated with the SOC sequestration and negatively with N leaching. The crop N uptake is expected to be adequate in view of higher rate of soil mineralization; the N fertilization rate of 400 kg N ha(-1) will involve significant increasing of grain yield, and it is expected to involve a higher rate of SOC sequestration.

Leaf area index (LAI) is a crucial variable in agronomic and environmental studies, because of its importance for estimating the amount of radiation intercepted by the canopy and the crop water requirements. Direct methods for LAI estimation are destructive, labor and time consuming, and hardly applicable in case of forest ecosystems. This led to the development of different indirect methods, based on models for light transmission into the canopy and implemented into dedicated commercial instruments (e.g., LAI-2000 and different models of ceptometers). However, these instruments are usually expensive and characterized by a low portability, and could require long and expensive maintenance services in case of damages. In this study, we present an app for smartphone implementing two methods for LAI estimation, based on the use of sensors and processing power normally present in most of the modern mobile phones. The first method (App-L) is based on the estimation of the gap fraction at 57.5° (to acquire values that are almost independent of leaf inclination) from luminance estimated above and below the canopy. The second method (App-G) estimates the gap fraction via automatic processing of images acquired below the canopy. The performances of the two methods implemented in the app were evaluated using data collected in a scatter-seeded rice field in northern Italy, and compared with those of the LAI-2000 and AccuPAR ceptometer, by determining the methods’ accuracy (trueness and precision, the latter represented by repeatability and reproducibility) and linearity. The performances of App-G (mean repeatability limit = 0.80 m2 m−2; mean reproducibility limit = 0.82 m2 m−2; RMSE = 1.04 m2 m−2) were similar to those shown by LAI-2000 and AccuPAR, whereas App-L achieved the best trueness value (RMSE = 0.37 m2 m−2), although it resulted the less precise, requiring a large number of replicates to provide reliable estimations. Despite the satisfactory performances, the app proposed should be considered just as an alternative to the available commercial instruments, useful in contexts characterized by low economic resources or when the highest portability is needed.

Intensive agriculture and livestock breeding represent critical factors in the environment, particularly in the Lombardy region where nitrate vulnerable zones represent 62% of Utilised Agricultural Area (UAA). The problem of reduction of nitrogen losses as leaching of nitrates into groundwater and ammonia emissions into atmosphere can be only addressed through a critical and scientific analysis of animal manure entire production chain. As consequence, the ValorE Decision Support System (DSS-Valorisation of Effluents) has been developed to run simulation both at farm and territorial scale. ValorE allows to define, simulation scenarios on the basis of different manure management options and evaluate these by synthetic indices which take into account environmental, economic, technical, multifunctional and normative aspects. The application of the DSS in a sample of selected farms highlighted its potentiality as a tool to support stockholders' decisions and how an intervention planned at district level could be a useful solution to improve livestock manure management.