Organic farming is a holistic production management system that promotes and enhances agroecosystem health, including biodiversity, biological cycles and soil biological activity, and consequently, it is an efficient and promising approach for sustainable agriculture within a circular and green economy. There has been a rise in the consumption of organic vegetables in the last years because of their organoleptic properties, higher nutritive value and lower risk of chemical residues harmful to health. The recent scientific evidence regarding the use of the major elements responsible for organic vegetable crop production indicates plant material, soil management and crop nutrition, soil disinfection, crop management and pest, disease and weed management. These techniques are the focus of this study. In general, the main outcomes of this review demonstrate that a great effort of innovation and research has been carried out by industry, researchers and farmers in order to reduce the environmental impact of the established and innovative horticultural practices while satisfying the requirements of consumers. However, research-specific studies should be carried out in different farming systems and pedoclimatic conditions to achieve the highest efficiency of these horticultural practices.

Olive mill wastes (OMW) management by composting allows to obtain valuable fertilizing products, but also implies significant fluxes of greenhouse gases (GHG). For a proper OMW composting, high C- and N co-substrates are necessary, but little is known concerning their effect on GHG emissions in OMW-industrial scale composting. In this study, different co-composting agents (cattle manure (CM), poultry manure (PM), sheep manure (SM) and pig slurry solid fraction (PSSF) as N sources and olive leaves (OLW) and urban pruning residues (UPR) as bulking agents and C sources) were used for OMW composting at industrial scale. Physico-chemical and chemical properties in the composting samples, and GHG (CO₂, CH₄ and N₂O) fluxes were monitored in 12 industrial-scale windrows. GHG emissions were firstly influenced by N source, with the highest accumulated global warming potential (GWP) associated with PM (512 kg CO₂eq pile^-1), since PM composts were associated with the greatest N₂O (0.33 kg pile^-1) and CH₄ emissions (15.67 kg pile^-1). Meanwhile, PSSF was associated with the highest CO₂ emissions (1113 kg pile^-1). UPR as a bulking agent facilitated 10 % greater mineralization of the biomass than OLW, however this C-source was not associated with higher GHG emissions. The results showed that while mineralization dynamics may be impacted by C sources, GHG emissions were mainly conditioned by the characteristics of nutrient-heavy feedstocks (PM and SM). Moreover, manures as nitrogen-laden co-substrates had widely differing effects on total GWP, and that of individual gases, but further research is necessary to understand the mechanisms explaining such differences.

Optical Earth Observation is often limited by weather conditions such as cloudiness. Radar sensors have the potential to overcome these limitations, however, due to the complex radar-surface interaction, the retrieving of crop biophysical variables using this technology remains an open challenge. Aiming to simultaneously benefit from the optical domain background and the all-weather imagery provided by radar systems, we propose a data fusion approach focused on the cross-correlation between radar and optical data streams. To do so, we analyzed several multiple-output Gaussian processes (MOGP) models and their ability to fuse efficiently Sentinel-1 (S1) Radar Vegetation Index (RVI) and Sentinel-2 (S2) vegetation water content (VWC) time series over a dry agri-environment in southern Argentina. MOGP models not only exploit the auto-correlations of S1 and S2 data streams independently but also the inter-channel cross-correlations. The S1 RVI and S2 VWC time series at the selected study sites being the inputs of the MOGP models proved to be closely correlated. Regarding the set of assessed models, the Convolutional Gaussian model (CONV) delivered noteworthy accurate data fusion results over winter wheat croplands belonging to the 2020 and 2021 campaigns ($NRMS{E}_{wheat2020}$ = 16.1%; $NRMS{E}_{wheat2021}$ = 10.1%). Posteriorly, we removed S2 observations from the S1 & S2 dataset corresponding to the complete phenological cycles of winter wheat from September to the end of December to simulate the presence of clouds in the scenes and applied the CONV model at the pixel level to reconstruct spatiotemporally-latent VWC maps. After applying the fusion strategy, the phenology of winter wheat was successfully recovered in the absence of optical data. Strong correlations were obtained between S2 VWC and S1 & S2 MOGP VWC reconstructed maps for the assessment dates (${\overline{R^2}}_{wheat-2020}$ = 0.95, ${\overline{R^2}}_{wheat-2021}$ = 0.96). Altogether, the fusion of S1 SAR and S2 optical EO data streams with MOGP offers a powerful innovative approach for cropland trait monitoring over cloudy high-latitude regions.

The treatment and valorization of organic solid waste has become a promising alternative to increase intensive crop productivity while reducing its environmental impact. Currently, reusing improved organic waste as novel biofertilizers is a vital tool to adapt semiarid agricultural regions to climate change, but this has been scarcely studied in aromatic crops. The present study aims to assess the greenhouse gas emissions, soil properties, and crop yield of a dill crop using a drip irrigation system with a normalized N application rate of 160 kg N ha⁻¹. We compare eight different fertilizing scenarios grouped into organic-based (manures and compost) and inorganic-based inputs (NPK commodities and slow-release formulations). GHG fluxes were measured during the 57-day fertigation period using static chambers. Key soil properties were measured previous to fertilizer applications and at harvest, coinciding with crop yield estimations. An increase in soil organic carbon was observed with stabilized organic treatments at 0–20 cm soil depth. The results show that stabilized organic-based materials lowered NO₃⁻ concentrations in dill biomass more than synthetic fertilizers, producing similar yields to those with synthetic fertilizers. In general, N₂O emissions were positively affected by the treatments. Local specific emission factors for N₂O were determined (0.08%), which were substantially lower than the default value (0.51%) of IPCC. The cumulative CO₂ emissions were high in all the organic scenarios compared to the control treatment (277 kg C-CO₂ ha⁻¹), probably due to differences in labile organic C contents. Organic-based treatments showed multiple positive effects on crop quality, crop yields, and GHG mitigation potential. The use of organic amendments is an optimized N fertilizing strategy to promote circular economy and sustainability.

Organic solid wastes are rarely considered when planning for rural production in Argentina. Onion production in the low valley of Río Colorado (Buenos Aires) generates between 12,000 and 20,000 Mg year⁻¹ of vegetal wastes (i.e., leaves, stems, skins, roots) from harvesting, cleaning and classification of bulbs, causing many problems with their management. The aim of this work is to study the effect of different doses of onion residue-bovine manure compost and onion residue-bovine manure compost tea on the soil physicochemical properties, microbial activity and agroecological onion production in sandy soil. Results showed that the highest dose of compost caused the highest effects on soil pH, electrical conductivity and nutrient content. Soil enzymatic activities were already high in the soil before the compost was applied, which may have contributed to the small effect caused by any dose on soil activity. A significant positive effect on bulb weight and organic onion yield were found as a result of the amendment and growing season. In conclusion, agroecological production of onion with the addition of a 300 kg N ha⁻¹ compost and compost tea guarantee yields comparable to those of conventional fertilization, as occurred during the two growing seasons of this study.

The reuse of effluents from intensive dairy farms combined with localized irrigation techniques (fertigation) has become a promising alternative to increase crop productivity while reducing the environmental impact of waste accumulation and industrial fertilizers production. Currently, the reuse of dairy effluents through fertigation by subsurface drip irrigation (SDI) systems is of vital importance for arid regions but it has been poorly studied. The present study aimed to assess the greenhouse gas (GHG) emissions, soil properties, and crop yield of a maize crop fertigated with either treated dairy effluent or dissolved granulated urea applied through an SDI system at a normalized N application rate of 200 kg N ha⁻¹. Fertilizer application was divided into six fertigation events. GHG fluxes were measured during fertigation (62-day) using static chambers. Soil properties were measured previous to fertilizer applications and at the harvest coinciding with crop yield estimation. A slight increase in soil organic matter was observed in both treatments for the 20–60 cm soil depth. Both treatments also showed similar maize yields, but the dairy effluent increased net GHG emissions more than urea during the fertigation period. Nevertheless, the net GHG emissions from the dairy effluent were lower than the theoretical CO₂eq emission that would have been emitted during urea manufacturing or the longer storage of the effluent if it had not been used, showing the need for life-cycle assessments. Local-specific emission factors for N₂O were determined (0.07%), which were substantially lower than the default value (0.5%) of IPCC 2019. Thus, the subsurface drip irrigation systems can lead to low GHG emissions, although further studies are needed.