Agronomy for Sustainable Development最新文献

Agriculture is a key contributor to gaseous emissions causing climate change, the degradation of water quality, and biodiversity loss. The extant climate change crisis is driving a focus on mitigating agricultural gaseous emissions, but wider policy objectives, beyond net zero, mean that evidence on the potential co-benefits or trade-offs associated with on-farm intervention is warranted. For novelty, aggregated data on farm structure and spatial distribution for different farm types were integrated with high-resolution data on the natural environment to generate representative model farms. Accounting for existing mitigation effects, the Catchment Systems Model was then used to quantify global warming potential, emissions to water, and other outcomes for water management catchments across England under both business-as-usual and a maximum technically feasible mitigation potential scenario. Mapped spatial patterns were overlain with the distributions of areas experiencing poor water quality and biodiversity loss to examine potential co-benefits. The median business-as-usual GWP20 and GWP100, excluding embedded emissions, were estimated to be 4606 kg CO₂ eq. ha⁻¹ (inter-quartile range 4240 kg CO₂ eq. ha−¹) and 2334 kg CO₂ eq. ha⁻¹ (inter-quartile range 1462 kg CO₂ eq. ha⁻¹), respectively. The ratios of business-as-usual GHG emissions to monetized farm production ranged between 0.58 and 8.89 kg CO₂ eq. £⁻¹ for GWP20, compared with 0.53–3.99 kg CO₂ eq. £⁻¹ for GWP100. The maximum mitigation potentials ranged between 17 and 30% for GWP20 and 19-27% for GWP100 with both corresponding medians estimated to be ~24%. Here, we show for the first time that the co-benefits for water quality associated with reductions in phosphorus and sediment loss were both equivalent to around a 34% reduction, relative to business-as-usual, in specific management catchment reporting units where excess water pollutant loads were identified. Several mitigation measures included in the mitigation scenario were also identified as having the potential to deliver co-benefits for terrestrial biodiversity.

Crop cultivar mixtures commonly increase productivity in the short term and stabilize or enhance productivity in the long term. However, these effects can be highly variable, likely due to limited research that has experimentally addressed intraspecific diverse effects over time and simultaneously explored their underlying mechanisms. We explored the effects of cultivar mixtures on the temporal yield stability and crop productivity trends in a 7-year (2016–2022) field experiment with maize in Northwest China. Further, we investigated the mechanisms underlying the enhanced productivity and temporal stability, which may be attributed to complementarity effects and asynchrony derived from functional trait dissimilarity among the maize cultivars in the mixtures. Across all cultivar mixtures over the 7 years, grain yield and aboveground biomass increased by 5.6% and 3.6%, respectively, compared to the monocultures. To investigate changes in temporal yield stability over the 7 years, we calculated stability using 3-year rolling windows. Our results showed that temporal yield stability in cultivar mixtures increased during the later years (2019–2022), compared to the monocultures. Over the 7 years, grain yield and aboveground biomass outperformed monocultures by 35% and 38%, respectively, compared to the first year. Complementarity effects were strong and increased over time. The mean values of functional traits changed in response to mixtures, leading to plant height and ear height traits correlating positively with complementarity effects, which were correlated with temporal yield stability. Asynchrony, or variation in the responses of cultivars to environmental fluctuations, was negatively correlated with the temporal deviation in yield. These results, for the first time, indicated that large differences in mean trait values among cultivars, or those that express dynamic trait responses to diversity, can increase complementarity effects and asynchrony, producing more productive and stable crops. This increases our understanding of how intraspecific diversity might contribute to sustainable agroecosystems.

Climate change-driven extreme events are reducing barley productivity. The high use of mineral fertilizers, combined with low nutrient use efficiency, leads to environmental and economic concerns. Indigenous arbuscular mycorrhizal fungi (AMF) inoculants offer a sustainable alternative, especially in intensive farming systems where AM colonization and diversity are low. However, poor adaptation to local conditions limits inoculant success. Few studies have tested indigenous AMF inoculated on field crops, with limited research on barley. No research has yet explored how barley genotype and environment modulate field inoculation outcomes in terms of crop productivity. Key factors such as AM fungal abundance and community structure shifts remain unidentified. This study evaluated the agroecological effects of an indigenous AM fungal consortium on three barley varieties (Atlante, Atomo, and Concerto) over 2 years. In 2020, Atomo and Concerto responded positively to inoculation in terms of root colonization, with grain yield increases of 64% and 37%, respectively. In 2021, only Concerto showed enhanced root colonization, while grain yield increased by 78% in Concerto and 134% in Atlante. Multivariate analysis revealed a strong impact of environment on barley productivity, with a significant third-order interaction among AMF, genotype, and environment. Inoculation slightly altered AM composition but strongly influenced community structure, particularly at different plant growth stages. Root colonization was strongly correlated with barley productivity, with root length containing arbuscules being the best predictor. Changes in the AM community structure, rather than composition, drove barley response, with Glomus and Septoglomus, present in the inoculum, being main players. These findings support the use of indigenous AMF for sustainable biofertilization and highlight the importance of selecting genotypes with a stable AM response across environments. Our results disclose for the first time the role of barley genotype and plant growth stage on AM host preference with and without indigenous AM fungal inoculants.

Maize is the second most important cereal crop in European agriculture and a widely used raw material for feed, food, and energy production. Climate change studies over Europe predict a significant negative change in maize production. Finding appropriate and feasible adaptation strategies is a top priority for agriculture in the twenty-first century. Long-term agricultural experiments provide a useful resource for evaluating biological, biogeochemical, and environmental aspects of agricultural sustainability and for predicting future global changes. For the first time, we have been able to formulate a response to the question of which sowing date or hybrid choice strategies will prove beneficial in the future for the Pannonian region, based on sufficiently long experimental data. The objective of the study was to analyze a 30-year period of a multi-factorial long-term experiment at Martonvásár (Hungary) searching for traces of climate change as well as for favorable combinations of agro-management factors that can be used as adaptation options in the future. To analyze and extrapolate the data both in space and time, a multivariate statistical (response surface) model and a process-based crop simulation model were used. The results of the study yielded the following conclusions: (1) intensification of fertilization would not promote sustainable development in the region, (2) late hybrids have no perspective in the Pannonian climatic zone, and (3) earlier planting may become an effective adaptation option in the future. Our comprehensive methodology combines long-term historical weather and climate projection data with statistical and simulation models for the first time to provide agricultural stakeholders with more reliable adaptation strategies. It is essential to facilitate effective knowledge transfer to encourage farmers to adopt the proposed new practices. The collection of more detailed data for the entire Carpathian Basin will allow for the improvement of the models and projections.

This virtual issue reports on the use of digital technologies in On-Farm Experimentation (OFE) in varied farming systems across the world. The authors investigated diverse questions across contrasted environments and scientific domains, with methodologies that included review, empirical studies, interviews, and reflexive accounts. The contributions thus showcase the multiplicity of research directions that are relevant to OFE. This includes addressing the two intertwined types of research objects in OFE: the farmers’ questions (how to improve management) and the methodologies required to address these (how to improve research through OFE)—with the notable support of digital tools. The issue includes a systematic review exploring OFE practices and farmer-researcher relationships as reported in the scientific literature; a meta-analysis comparing experimental scales in the USA; reflexive analyzes on a feed assessment tool and a tree crop decision support system rooted in OFE that are connecting farmers and researchers in Africa; a retrospective on a large CGIAR program combining citizen sciences and OFE; the use of video recordings and work analysis to characterize farmers’ knowledge in French vineyards; and in the same sector in Australia, two accounts of the use of digital tools in spatially explicit OFE: one an investigation into farmers’ and consultants’ perceptions, the other a retrospective on the roles of precision agriculture. Findings from these examples validate the use of varied digital tools to scale the design, implementation, and learning stages of OFE processes. These include how to better harness and bridge the knowledge of farmers, researchers and other parties, examples of data management and analytics, the improved interpretation of results, and capitalizing on experiences. The international conference this issue was part of also led to acknowledgement of a lack of policy linkages, required to scale OFE endeavors by incentivizing institutional change toward more farmer-centric research practices and responsible digital deployment.

Pulse crops are commonly used to improve nitrogen management and diversify cereal-based cropping systems. However, integrated assessments of diversified rotations with pulse crops using plant, soil, and environmental quality indicators remain limited and relatively underexplored. A comprehensive evaluation of such diversified rotations based on agronomic performance, economic returns, and environmental sustainability over time is essential for enhancing cropping system resilience. An eight-year study (two cycles of 4-year rotation) was conducted at two locations to determine the effects of diversification with pulses on ecosystem services indicators including productivity, resource use efficiency, soil carbon, soil nitrogen, carbon footprint, and economic returns. Four cropping systems were evaluated, including a low-diversified rotation of lentil-wheat-lentil-wheat, a moderately diversified rotation of pea-wheat-lentil-wheat, a highly diversified rotation of pea-mustard-lentil-wheat, and a wheat monocrop control. At the 4-year rotation level, diversified rotations increased yield by 22–36%, water use efficiency by 31–42%, energy productivity by 78–86%, and economic returns by 46–65%, compared to the wheat monocrop. Additionally, diversified rotations resulted in net CO₂ withdrawal when accounting for carbon sequestration in the soil. There was no difference between moderately and highly diversified rotations, suggesting that a large portion of diversification benefits can be achieved at the moderately diversified rotation level. Compared with the wheat monocrop, diversified rotations reduced nitrogen fertilizer inputs and resulted in a 10–31% lower partial nitrogen balance at the end of 8-year rotations. Moreover, diversifying cropping systems with pulse crops had no adverse effect on soil organic carbon, despite relatively low straw returns from pulse crops. These results, assessed using multiple system indicators at both the crop phase and rotation levels, reveal that diversifying rotations with pulse crops, even at a moderate level, can effectively improve the ecosystem services, contributing to the sustainability of cropping systems.

Cover crops (CC) have the potential to reduce the dependency of rice (Oryza sativa L.) production on chemical N fertilizers and the associated environmental and economic risks. While extensively studied in tropical and subtropical systems, their potential in Mediterranean lowlands remains underexplored. This study evaluated whether CC could reduce chemical N fertilization in a Mediterranean rice system (Ebro Delta, Spain). Rice was grown during three seasons (2020–2023) preceded by a bare fallow, hairy vetch (Vicia villosa Roth), or ryegrass (Lolium multiflorum Lam.) during the winter period, and with 4 different fertilizer N rates (0, 120, 180, and 240 kg N ha⁻¹) under a split-plot design. Besides testing rice productivity, we developed a simple but effective indicator to assess the economic impact of cover crops by adapting the marginal net return of grain production to include cover cropping costs. Differences in biomass accumulation between the CC species were variable across years, with ryegrass being more dependent on precipitation, but also negatively affected by the N fertilization for the rice from the previous season. Due to its sole reliance on soil N uptake, ryegrass never produced more biomass N than hairy vetch. Rice yields were 13% lower and N use efficiency 16% lower after ryegrass than after bare fallow across fertilization levels. Hairy vetch tended to improve rice development (i.e., NDVI and panicle density) but did not translate into higher yields or N use efficiency compared to bare fallowing, potentially due to inhibited N mineralization under anaerobic conditions in flooded environments. Consequently, CC implementation significantly reduced profitability, showing how economic incentives are needed to encourage adoption. Implementing hairy vetch as CC increased the soil total N by 10%, potentially benefiting long-term rice production. These findings offer practical insights for agronomists and policymakers focused on enhancing the sustainability of Mediterranean rice systems.

Strategic design decisions regarding wine label, plant material, vine age renewal, and planting choices are crucial for winegrowers when planning their future vineyards that will influence grapevine yield in the long term. However, the repercussions of these choices have mostly been studied in experimental vineyards and small datasets. Therefore, we are missing a comprehensive analysis of a large diversity of vineyard situations that can robustly provide avenues for improving vineyard design and ensure sustainable wine production. To fill this research gap, we analyzed a big sample of vineyards using random plot data (n = 3507) from surveys conducted among winegrowers of the Languedoc-Roussillon viticultural region. We carried out a data analysis that focused on examining the relationship between grapevine yield and (i) diverse vineyard management frameworks (wine label, organic management, irrigation), (ii) plant material (varieties, rootstocks), and (iii) planting choices (planting density, vine age as a proxy for vine lifespan and renewal). Our findings indicate that wine label greatly affected yield; in conjunction with vine age, they explained up to 40% of the total yield variance. Most cultivated varieties exhibited similar yield levels for the same type of wine label. Notably, SO4 rootstock displayed the best yield performance across multiple cultivated varieties. We observed an adverse effect of vine aging on grapevine yield, particularly in highly productive vineyards. In contrast, the impact of vine age on the yield of low-yield plots was almost negligible. Plots under organic farming presented lower yields, although they were scarce in the sample. Unexpectedly, planting density did not significantly affect yield. Overall, these results underscore the significance of conducting big data analysis from winegrowers at a regional level, when it comes to assessing the influence of vineyard design and plant material on yield.

Accurate calculation of nitrogen requirements is essential in rice fields utilizing both local manure and mineral fertilizers to mitigate nitrogen deficiencies and yield losses associated with reducing chemical fertilizer use. Traditional approaches often fail to effectively integrate organic and mineral fertilizers or adapt to the complexities of real-farm conditions. To tackle these challenges, this study introduced a novel application of the Nitrogen Fertilizer Optimization Algorithm (NFOA), leveraging remote optical sensors and Sentinel-2 satellite imagery to deliver precise, data-driven nitrogen recommendations for the effective integration of organic fertilization in rice cultivation. Fertilizer prescription maps generated by the NFOA delivered precise nitrogen recommendations tailored for diverse real-farm fields. The algorithm demonstrated strong predictive performance for yield responses to nitrogen application at critical phenological stages, such as panicle initiation and maximum tillering (R² = 0.71, p < 0.0001; R² = 0.73, p < 0.0001). Key findings demonstrate the model’s ability to optimize nitrogen inputs, achieving up to a 40% reduction in surplus nitrogen while maximizing yields. By promoting a balanced nitrogen input-output equilibrium, the NFOA offers significant environmental and economic benefits, even in the context of the complexities associated with organic fertilization. In conclusion, these findings suggest that the NFOA approach is suitable for calculating nitrogen fertilizer requirements in rice fields using organic fertilization strategies, effectively accommodating the high variability in nutrient content and availability of organic nitrogen to rice crops. However, further refinement is necessary to enhance its predictive accuracy by incorporating advanced spectral indices and accounting for detailed environmental and management factors.