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Many communities in low- and middle-income countries globally lack sustainable, cost-effective and mutually beneficial solutions for infectious disease, food, water and poverty challenges, despite their inherent interdependence 1 – 7 . Here we provide support for the hypothesis that agricultural development and fertilizer use in West Africa increase the burden of the parasitic disease schistosomiasis by fuelling the growth of submerged aquatic vegetation that chokes out water access points and serves as habitat for freshwater snails that transmit Schistosoma parasites to more than 200 million people globally 8 – 10 . In a cluster randomized controlled trial (ClinicalTrials.gov: NCT03187366) in which we removed invasive submerged vegetation from water points at 8 of 16 villages (that is, clusters), control sites had 1.46 times higher intestinal Schistosoma infection rates in schoolchildren and lower open water access than removal sites. Vegetation removal did not have any detectable long-term adverse effects on local water quality or freshwater biodiversity. In feeding trials, the removed vegetation was as effective as traditional livestock feed but 41 to 179 times cheaper and converting the vegetation to compost provided private crop production and total (public health plus crop production benefits) benefit-to-cost ratios as high as 4.0 and 8.8, respectively. Thus, the approach yielded an economic incentive—with important public health co-benefits—to maintain cleared waterways and return nutrients captured in aquatic plants back to agriculture with promise of breaking poverty–disease traps. To facilitate targeting and scaling of the intervention, we lay the foundation for using remote sensing technology to detect snail habitats. By offering a rare, profitable, win–win approach to addressing food and water access, poverty alleviation, infectious disease control and environmental sustainability, we hope to inspire the interdisciplinary search for planetary health solutions 11 to the many and formidable, co-dependent global grand challenges of the twenty-first century. By harvesting aquatic vegetation that provides habitat for snails that harbour  Schistosoma parasites and converting it to compost and animal feed, a trial reduced schistosomiasis prevalence in children while providing wider economic benefits.

This research was developed to investigate whether inoculation with Azospirillum brasilense in combination with silicon (Si) can enhance N use efficiency (NUE) in wheat and to evaluate and correlate nutritional and productive components and wheat grain yield. The study was carried out on a Rhodic Hapludox under a no-till system with a completely randomized block design with four replications in a 2 × 2 × 5 factorial scheme: two liming sources (with Ca and Mg silicate as the Si source and limestone); two inoculations (control - without inoculation and seed inoculation with A . brasilense ) and five side-dress N rates (0, 50, 100, 150 and 200 kg ha −1 ). The results of this study showed positive improvements in wheat growth production parameters, NUE and grain yield as a function of inoculation associated with N rates. Inoculation can complement and optimize N fertilization, even with high N application rates. The potential benefits of Si use were less evident; however, the use of Si can favour N absorption, even when associated with A . brasilense . Therefore, studies conducted under tropical conditions with Ca and Mg silicate are necessary to better understand the role of Si applied alone or in combination with growth-promoting bacteria such as A . brasilense .

Phosphorus (P) is the second most important macronutrient that limits the plant growth, development and productivity. Inorganic P fertilization in podzol soils predominantly bound with aluminum and iron, thereby reducing its availability to crop plants. Dairy manure (DM) amendment to agricultural soils can improve physiochemical properties, nutrient cycling through enhanced enzyme and soil microbial activities leading to improved P bioavailability to crops. We hypothesized that DM amendment in podzol soil will improve biochemical attributes and microbial community and abundance in silage corn cropping system under boreal climate. We evaluated the effects of organic and inorganic P amendments on soil biochemical attributes and abundance in podzol soil under boreal climate. Additionally, biochemical attributes and microbial population and abundance under short-term silage corn monocropping system was also investigated. Experimental treatments were [P 0 (control); P 1 : DM with high P 2 O 5 ; P 2 : DM with low P 2 O 5 ; P 3 : inorganic P and five silage-corn genotypes (Fusion RR, Yukon R, A4177G3RIB, DKC 23-17RIB and DKC 26-28RIB) were laid out in a randomized complete block design in factorial settings with three replications. Results showed that P 1 treatment increased acid phosphatase (AP-ase) activity (29% and 44%), and soil available P (SAP) (60% and 39%) compared to control treatment, during 2016 and 2017, respectively. Additionally, P 1 treatments significantly increased total bacterial phospholipids fatty acids (ΣB-PLFA), total phospholipids fatty acids (ΣPLFA), fungi, and eukaryotes compared to control and inorganic P. Yukon R and DKC 26-28RIB genotypes exhibited higher total bacterial PLFA, fungi, and total PLFA in their rhizospheres compared to the other genotypes. Redundancy analyses showed promising association between P 1 and P 2 amendment, biochemical attributes and active microbial population and Yukon R and DKC 26-28RIB genotypes. Pearson correlation also demonstrated significant and positive correlation between AP-ase, SAP and gram negative bacteria (G − ), fungi, ΣB-PLFA, and total PLFA. Study results demonstrated that P1 treatment enhanced biochemical attributes, active microbial community composition and abundance and forage production of silage corn. Results further demonstrated higher active microbial population and abundance in rhizosphere of Yukon R and DKC 26-28RIB genotypes. Therefore, we argue that dairy manure amendment with high P 2 O 5 in podzol soils could be a sustainable nutrient source to enhance soil quality, health and forage production of silage corn. Yukon R and DKC 26-28RIB genotypes showed superior agronomic performance, therefore, could be good fit under boreal climatic conditions.

Background The combination of mulch with N fertilizer application is a common agronomic technique used in the production of rainfed maize ( Zea mays L. ) to achieve higher yields under conditions of optimum planting density and adequate N supply. However, the combined effects of mulch, planting density, and N fertilizer application rate on plant N uptake and N translocation efficiency are not known. The objective of this study was to quantify the interaction effect of mulch, planting density, and N fertilizer application rate on maize grain yield, N uptake, N translocation, and N translocation efficiency. The experiment was arranged in a randomized complete block design with three factors (2 mulch levels × 2 planting densities × 4 N fertilizer application rates) replicated four times. Results There was a significant interaction among mulch, plant density, and N fertilizer on maize grain yield, kernel number per cob, N uptake, N translocation, and N translocation efficiency. Averaged over the 3 years of the study, total plant N uptake at silking ranged from 79 to 149 kg N ha − 1 with no mulch and from 76 to 178 kg N ha − 1 with mulch. The N uptake at silking in different plant organs ranked as leaf > grain > stem > cob. Averaged across all factors, the highest N translocation was observed in leaves, which was 59.4 and 88.7% higher than observed in stems and ears, respectively. The mean vegetative organ N translocation efficiency averaged over mulch, planting density, and N fertilizer application rate treatments decreased in the order of leaf > stem > cob. Conclusions Mulch, planting density, and N fertilizer application rate not only have significant effects on improving maize grain yield and NUE, but also on N uptake, N translocation, and N translocation efficiency. Our results showed clearly that under high planting density, the combination of mulch and moderate N fertilizer application rate was the optimal strategy for increasing maize grain yield and N use efficiency.

In order to address the question of how flavonoids affected root nodulation of faba bean in a wheat and faba bean intercropping system, we set up soil and hydroponic experiments comprising two cropping pattern treatments (intercropped and monocropped) and three nitrogen (N) supply treatments at the deficient (50% N), adequate (100% N), and excessive (150% N) levels with three replicates in a randomized complete block design. Across the three N treatments and two experiments, it was frequently observed that intercropping increased but N fertilization decreased the nodule number and nodule dry weight of faba bean. Six types of flavonoids were detected in the faba bean root secretion, but only genistein, hesperetin, and naringenin often had significant correlations with the nodule number and nodule dry weight. Intercropping increased faba bean root secretions of genistein, hesperetin, and naringenin compared to monoculture only at the deficient and adequate N supply levels. The differences in flavonoids of faba bean caused by the intercropped patterns, N supply levels, and their interactions were mainly significant at flowering stage. In conclusion, interspecies and N supply interactively altered the contents and proportions of flavonoids in faba bean root exudations under wheat and faba bean intercropping. These findings provide insight into flavonoids-nodule-yield interactions in cereal and legume intercropping systems.

The current trajectory for crop yields is insufficient to nourish the world’s population by 2050 1 . Greater and more consistent crop production must be achieved against a backdrop of climatic stress that limits yields, owing to shifts in pests and pathogens, precipitation, heat-waves and other weather extremes. Here we consider the potential of plant sciences to address post-Green Revolution challenges in agriculture and explore emerging strategies for enhancing sustainable crop production and resilience in a changing climate. Accelerated crop improvement must leverage naturally evolved traits and transformative engineering driven by mechanistic understanding, to yield the resilient production systems that are needed to ensure future harvests. Genetic strategies for improving the yield and sustainability of agricultural crops, and the resilience of crops in the face of biotic and abiotic stresses contingent on projected climate change, are evaluated.

Cropland is a main source of global nitrogen pollution 1 , 2 . Mitigating nitrogen pollution from global croplands is a grand challenge because of the nature of non-point-source pollution from millions of farms and the constraints to implementing pollution-reduction measures, such as lack of financial resources and limited nitrogen-management knowledge of farmers 3 . Here we synthesize 1,521 field observations worldwide and identify 11 key measures that can reduce nitrogen losses from croplands to air and water by 30–70%, while increasing crop yield and nitrogen use efficiency (NUE) by 10–30% and 10–80%, respectively. Overall, adoption of this package of measures on global croplands would allow the production of 17 ± 3 Tg (10 12  g) more crop nitrogen (20% increase) with 22 ± 4 Tg less nitrogen fertilizer used (21% reduction) and 26 ± 5 Tg less nitrogen pollution (32% reduction) to the environment for the considered base year of 2015. These changes could gain a global societal benefit of 476 ± 123 billion US dollars (USD) for food supply, human health, ecosystems and climate, with net mitigation costs of only 19 ± 5 billion USD, of which 15 ± 4 billion USD fertilizer saving offsets 44% of the gross mitigation cost. To mitigate nitrogen pollution from croplands in the future, innovative policies such as a nitrogen credit system (NCS) could be implemented to select, incentivize and, where necessary, subsidize the adoption of these measures. A meta-analysis of 1,521 field observations from the past two decades led to the identification of 11 key measures to cost-effectively mitigate nitrogen pollution from global croplands.

Precision agriculture technologies (PATs) transform crop production by enabling more sustainable and efficient agricultural practices. These technologies utilize data‐driven approaches to optimize the management of crops, soil, and resources, thus enhancing both productivity and environmental sustainability. This article reviewed the application of PATs for sustainable crop production and environmental sustainability around the globe. Key components of PAT include remote sensing, GPS‐guided equipment, variable rate technology (VRT), and Internet of Things (IoT) devices. Remote sensing and drones deliver high‐resolution imagery and data, enabling precise monitoring of crop health, soil conditions, and pest activity. GPS‐guided machinery ensures accurate planting, fertilizing, and harvesting, which reduces waste and enhances efficiency. VRT optimizes resource use by allowing farmers to apply inputs such as water, fertilizers, and pesticides at varying rates across a field based on real‐time data and specific crop requirements. This reduces over‐application and minimizes environmental impact, such as nutrient runoff and greenhouse gas emissions. IoT devices and sensors provide continuous monitoring of environmental conditions and crop status, enabling timely and informed decision‐making. The application of PAT contributes significantly to environmental sustainability by promoting practices that conserve water, reduce chemical usage, and enhance soil health. By enhancing the precision of agricultural operations, these technologies reduce the environmental impact of farming, while simultaneously boosting crop yields and profitability. As the global demand for food increases, precision agriculture offers a promising pathway to achieving sustainable crop production and ensuring long‐term environmental health.

Background The study focuses on enhancing the effectiveness of precision agriculture through the application of deep learning technologies. Precision agriculture, which aims to optimize farming practices by monitoring and adjusting various factors influencing crop growth, can greatly benefit from artificial intelligence (AI) methods like deep learning. The Agro Deep Learning Framework (ADLF) was developed to tackle critical issues in crop cultivation by processing vast datasets. These datasets include variables such as soil moisture, temperature, and humidity, all of which are essential to understanding and predicting crop behavior. By leveraging deep learning models, the framework seeks to improve decision-making processes, detect potential crop problems early, and boost agricultural productivity. Results The study found that the Agro Deep Learning Framework (ADLF) achieved an accuracy of 85.41%, precision of 84.87%, recall of 84.24%, and an F1-Score of 88.91%, indicating strong predictive capabilities for improving crop management. The false negative rate was 91.17% and the false positive rate was 89.82%, highlighting the framework's ability to correctly detect issues while minimizing errors. These results suggest that ADLF can significantly enhance decision-making in precision agriculture, leading to improved crop yield and reduced agricultural losses. Conclusions The ADLF can significantly improve precision agriculture by leveraging deep learning to process complex datasets and provide valuable insights into crop management. The framework allows farmers to detect issues early, optimize resource use, and improve yields. The study demonstrates that AI-driven agriculture has the potential to revolutionize farming, making it more efficient and sustainable. Future research could focus on further refining the model and exploring its applicability across different types of crops and farming environments.

Achieving food-system sustainability is a multidimensional challenge. In China, a doubling of crop production since 1990 has compromised other dimensions of sustainability 1 , 2 . Although the country is promoting various interventions to enhance production efficiency and reduce environmental impacts 3 , there is little understanding of whether crop switching can achieve more sustainable cropping systems and whether coordinated action is needed to avoid tradeoffs. Here we combine high-resolution data on crop-specific yields, harvested areas, environmental footprints and farmer incomes to first quantify the current state of crop-production sustainability. Under varying levels of inter-ministerial and central coordination, we perform spatial optimizations that redistribute crops to meet a suite of agricultural sustainable development targets. With a siloed approach—in which each government ministry seeks to improve a single sustainability outcome in isolation—crop switching could realize large individual benefits but produce tradeoffs for other dimensions and between regions. In cases of central coordination—in which tradeoffs are prevented—we find marked co-benefits for environmental-impact reductions (blue water (−4.5% to −18.5%), green water (−4.4% to −9.5%), greenhouse gases (GHGs) (−1.7% to −7.7%), fertilizers (−5.2% to −10.9%), pesticides (−4.3% to −10.8%)) and increased farmer incomes (+2.9% to +7.5%). These outcomes of centrally coordinated crop switching can contribute substantially (23–40% across dimensions) towards China’s 2030 agricultural sustainable development targets and potentially produce global resource savings. This integrated approach can inform feasible targeted agricultural interventions that achieve sustainability co-benefits across several dimensions. Spatial optimizations of high-resolution data from China on crop-specific yields, harvested areas, environmental footprints and farmer incomes shows that crop switching can enhance environmental sustainability and farmer incomes, and contribute substantially towards China’s agricultural sustainable development targets.