Nutrient budgets on organic farms: a review of published

This report was presented at the UK Organic Research 2002 Conference. On organic farms it is important that a balance between inputs and outputs of nutrients is achieved. This paper collates nutrient budgets collated at the farm scale for 88 farms in 9 temperate countries. The majority of budgets were compiled for dairy farms (56). All the nitrogen budgets showed an N surplus (average 83 kg N ha-1 year-1). The phosphorus (P) and potassium (K) budgets showed both surpluses and deficits (average 3.4 kg P ha-1 year-1; 13.7 kg K ha-1 year-1). For all nutrients as nutrient inputs increased the surplus increased more significantly than the nutrient outputs. Overall, the data illustrate the diversity of management systems in place on organic farms, which consequently lead to significant variability in nutrient use efficiency and potential nutrient sustainability between farms. There are opportunities for almost all organic farmers to improve the efficiency of nutrient cycling on the farm and increase short-term productivity and long-term sustainability

Utilising the concept of nutrients as a currency within organic farming system

This report was presented at the UK Organic Research 2002 Conference.Within organic systems, the successful management of nutrients at the field level is crucial for maximising production and minimising the environmental impacts. This requires that the farmer makes the best possible use of nutrients excreted by the grazing or housed livestock. In addition, the farmer must successfully manage the nutrients built-up in the ley phase of the crop rotation over the whole of the arable phase period. To analyse these complex flows, a nutrient budget model has been developed that describes the spatial and temporal flows within the organic farming system. The concept is analogous to treating nutrients as a currency where the flow of nutrients represents a cashflow. A spatial nutrient budget permits the analyses of the performance of the nutrient flows to be examined for the housing, manure, livestock, rotational land and permanent pasture to be analysed separately. This analysis will allow the farmer to better understand the weaknesses in the system, and hence take preventative measures

Do Farm Management Practices Alter Soil Biodiversity and Ecosystem Function? Implications for Sustainable Land Management

Maintaining ecosystem functions is a key issue for sustainable farming, while recent reviews (Hole et al, 2005, Fuller et al 2005) have highlighted that a wide range of taxa, including birds and mammals, benefit from organic management of land, there is a need to bring together the evidence for the impact of agricultural management practices on belowground biodiversity. A focus simply on the biodiversity of below-ground species is however not enough and there is a need to consider the contribution of below-ground biological processes to the maintenance and enhancement of a range of ecosystem services. A recent literature review on the impacts of land management practices on soil ecology and function shows clearly that farm management practices do alter below-ground biodiversity and ecosystem function. The data indicate that reducing the intensity of use of mechanical and manufactured inputs and (re)-discovering cost-effective ways to integrate biological inputs, will benefit below–ground biodiversity, particularly in lowland grassland and cropping systems. Benefits are seen from both organic and integrated systems; the evidence base is not strong enough to conclusively distinguish the benefits of these approaches from one another in lowland arable system

Reporting and Assessing the Quality of Diagnostic Accuracy Studies for Cervical Cancer Screening and Management.

ObjectiveWe adapted the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool for studies of cervical cancer screening and management and used the adapted tool to evaluate the quality of studies included in a systematic review supporting the 2019 Risk-Based Management Consensus Guidelines.MethodsWe evaluated the quality of all studies included in our systematic review for postcolposcopy (n = 5) and posttreatment (n = 23) surveillance using QUADAS-2 criteria. Subsequently, we adapted signaling questions to indications of cervical cancer screening and management. An iterative process was carried out to evaluate interrater agreement between 2 study authors (M.A.C. and N.W.). Discrepant ratings were discussed, and criteria were adapted accordingly. We also evaluated the influence of study quality on risk estimates and between study variation using stratified subgroup meta-analyses.ResultsTwelve signaling questions for bias assessment that were adapted to or newly developed for cervical cancer screening and management are described here. Interrater agreement on bias assessment increased from 70% to 83% during the adaptation process. Detailed assessment of bias and applicability showed that all studies on postcolposcopy management and 90% of studies on posttreatment management had high risk of bias in at least 1 domain. Most commonly, high risk of bias was observed for the patient selection domain, indicating the heterogeneity of study designs and clinical practice in reported studies.ConclusionsThe adapted QUADAS-2 will have broad application for researchers, evidence evaluators, and journals who are interested in designing, conducting, evaluating, and publishing studies for cervical cancer screening and management

Soil health metrics reflect yields in long-term cropping system experiments

Soil health metrics with strong links to ecological function and agricultural productivity are needed to ensure that future management of agricultural systems meets sustainability goals. While ecological metrics and crop yields are often considered separately from one another, our work sought to assess the links between the two in an agricultural context where productivity is a key consideration. Here, we investigated the value of soil health tests in terms of their relevance to agricultural management practices and crop yields at contrasting long term cropping systems experiments. One site was on a sandy loam Leptic Podzol and the other on a sandy clay loam Endostagnic Luvisol. Furthermore, the experiments had different management systems. One contained legume-supported rotations with different grass-clover ley durations and organic amendment usage, while the other compared a range of nutrient input options through fertiliser and organic amendments on the same rotation without ley periods. Metrics included field tests (earthworm counts and visual evaluation of soil structure scores) with laboratory analysis of soil structure, chemistry and biology. This analysis included bulk density, macroporosity, pH, available phosphorus, exchangeable potassium, soil organic matter and potentially mineralizable nitrogen. Using a novel combination of long-term experiments, management systems and distinctive soil types, we demonstrated that as well as providing nutrients, agricultural management which resulted in better soil organic matter, pH, potassium and bulk density was correlated with higher crop yields. The importance of ley duration and potentially mineralizable nitrogen to yield in legume-supported systems showed the impact of agricultural management on soil biology. In systems with applications of synthetic fertiliser, earthworm counts and visual evaluation of soil structure scores were correlated with higher yields. We concluded that agricultural management altered yields not just through direct supply of nutrients to crops, but also through the changes in soil health measured by simple metrics

New approach combining food value with nutrient budgeting provides insights into the value of alternative farming systems

Sustainable farming systems provide food for humans while balancing nutrient management. Inclusion or exclusion of livestock has nutrient management implications, as livestock produce food from otherwise inedible crops and their manure is a valuable soil conditioner. However, plant-based diets are becoming more widespread due to perceived environmental benefits. We measure both food production in terms of nourishment to humans (in this study measured by protein, fat, starch and sugar production) and nutrient sustainability in terms of fertiliser use of six rotational farming systems with differences in nutrient management approaches. The arable practices included were the application of synthetic fertilisers, a range of organic amendments, incorporation of crop residues and legume cultivation. Livestock and associated products were included in some systems but excluded in others. The production of protein, fat, starch and sugar was combined with the balance of nitrogen (N), phosphorus (P) and potassium (K) into an overall measure of nutrient use efficiency of human macronutrient production. Across all systems considered, N use efficiency (5-13 kg protein/kg applied N) was lower than P (84-772 kg protein/kg applied P) or K (63-2060 kg protein/kg applied K), and combining synthetic fertiliser use with organic amendment applications raised production significantly while balancing P and K management, regardless of which organic amendment was used. Legume-supported rotations without livestock produced more protein, starch and sugar per unit area than those with livestock. Nutrient balances and nutrient use efficiencies were more sensitive to management changes than purely food production. Using this approach allowed us to identify areas for improvement in food production based on the specific nutritional value of offtakes as opposed to yield overall.Peer reviewe

Whole-farm yield map datasets – data validation for exploring spatiotemporal yield and economic stability

CONTEXT: Statistical methods used for delineation of field management zones and yield stability are frequently only applied to relatively small areas, with few studies performing rotational, whole-farm economic spatiotemporal appraisals. To enable accurate economic analysis, yield map datasets must contain minimal errors while cleaning procedures are often used to remove errors, it is rare that cleaned data is validated before its application. OBJECTIVE: The objective of this study was to process, validate and combine spatial statistical approaches for a rotational yield map dataset from a whole-farm across 7 crops in a winter wheat based rotation. Developing a framework for using validated yield map datasets to support precision agriculture techniques that are applicable for farm-level decision making. METHODS: The rotational completeness of a 10 year combine yield map dataset for a 435 ha farm in Eastern England was assessed. The dataset was cleaned statistically, and its accuracy assessed by comparison with recorded yields from trailer weigh cells. The cleaned, validated, and corrected yield map dataset was used to identify management zones across the whole farm using fuzzy clustering. The temporal stability of management zones and economic performance across the rotation was also assessed. RESULTS AND DISSCUSION: Data cleaning methods removed 16% of data points, improving the degree of spatial correlation within the individual yield maps. Independent validation demonstrated varied accuracy of yield maps from combine harvester data and errors in wheat ranged from 0.53 to 1.53 t/ha RMSE. These errors have implications for researchers using combine yield data to develop and validate precision agriculture technologies. This data set required correction before yield data can be applied with confidence for on-farm decision making. Compared to the zones with the highest margin in each field, 34% of zones had an average annual margin loss of >£100 ha. The temporal stability of the resulting management zones also varied. Areas with the lowest economic performance and greatest yield stability across years will potentially see the greatest economic and environmental benefits from precision agriculture techniques. SIGNIFICANCE: The accuracy of combine yield map data should not be assumed. The application of these datasets, including for the identification of management zones or in developing precision agriculture techniques should attempt to address this through data cleaning and validation procedures. Only then should it be used for on farm decision making, such as identifying areas with the most economic benefit by applying precision agriculture tools such as variable rate nutrient applications.This work was supported by the UK Natural Environment Research Council through the CENTA Doctoral Training Partnership [NERC Ref: NE/L002493/1], together with the AHDB Strategic Cereal Farm East program PR: 2151003

Whole-farm yield map datasets – Data validation for exploring spatiotemporal yield and economic stability

CONTEXT Statistical methods used for delineation of field management zones and yield stability are frequently only applied to relatively small areas, with few studies performing rotational, whole-farm economic spatiotemporal appraisals. To enable accurate economic analysis, yield map datasets must contain minimal errors while cleaning procedures are often used to remove errors, it is rare that cleaned data is validated before its application. OBJECTIVE The objective of this study was to process, validate and combine spatial statistical approaches for a rotational yield map dataset from a whole-farm across 7 crops in a winter wheat based rotation. Developing a framework for using validated yield map datasets to support precision agriculture techniques that are applicable for farm-level decision making. METHODS The rotational completeness of a 10 year combine yield map dataset for a 435 ha farm in Eastern England was assessed. The dataset was cleaned statistically, and its accuracy assessed by comparison with recorded yields from trailer weigh cells. The cleaned, validated, and corrected yield map dataset was used to identify management zones across the whole farm using fuzzy clustering. The temporal stability of management zones and economic performance across the rotation was also assessed. RESULTS AND DISSCUSION Data cleaning methods removed 16% of data points, improving the degree of spatial correlation within the individual yield maps. Independent validation demonstrated varied accuracy of yield maps from combine harvester data and errors in wheat ranged from 0.53 to 1.53 t/ha RMSE. These errors have implications for researchers using combine yield data to develop and validate precision agriculture technologies. This data set required correction before yield data can be applied with confidence for on-farm decision making. Compared to the zones with the highest margin in each field, 34% of zones had an average annual margin loss of >£100 ha. The temporal stability of the resulting management zones also varied. Areas with the lowest economic performance and greatest yield stability across years will potentially see the greatest economic and environmental benefits from precision agriculture techniques. SIGNIFICANCE The accuracy of combine yield map data should not be assumed. The application of these datasets, including for the identification of management zones or in developing precision agriculture techniques should attempt to address this through data cleaning and validation procedures. Only then should it be used for on farm decision making, such as identifying areas with the most economic benefit by applying precision agriculture tools such as variable rate nutrient applications

New approach combining food value with nutrient budgeting provides insights into the value of alternative farming systems

Sustainable farming systems provide food for humans while balancing nutrient management. Inclusion or exclusion of livestock has nutrient management implications, as livestock produce food from otherwise inedible crops and their manure is a valuable soil conditioner. However, plant-based diets are becoming more widespread due to perceived environmental benefits. We measure both food production in terms of nourishment to humans (in this study measured by protein, fat, starch and sugar production) and nutrient sustainability in terms of fertiliser use of six rotational farming systems with differences in nutrient management approaches. The arable practices included were the application of synthetic fertilisers, a range of organic amendments, incorporation of crop residues and legume cultivation. Livestock and associated products were included in some systems but excluded in others. The production of protein, fat, starch and sugar was combined with the balance of nitrogen (N), phosphorus (P) and potassium (K) into an overall measure of nutrient use efficiency of human macronutrient production. Across all systems considered, N use efficiency (5-13 kg protein/kg applied N) was lower than P (84-772 kg protein/kg applied P) or K (63-2060 kg protein/kg applied K), and combining synthetic fertiliser use with organic amendment applications raised production significantly while balancing P and K management, regardless of which organic amendment was used. Legume-supported rotations without livestock produced more protein, starch and sugar per unit area than those with livestock. Nutrient balances and nutrient use efficiencies were more sensitive to management changes than purely food production. Using this approach allowed us to identify areas for improvement in food production based on the specific nutritional value of offtakes as opposed to yield overall

Spatial-temporal variability in nitrogen use efficiency: Insights from a long-term experiment and crop simulation modeling to support site specific nitrogen management

Within-field soil heterogeneity can lead to large variation in nitrogen use efficiency (NUE). Crop simulation models provide a multi-faceted approach to management considering both soil and plant interactions. However, research using crop models for investigating within field variation in NUE is limited, in part because of challenges quantifying spatially variable soil model parameters. Here soil apparent electrical conductivity (ECa) and measured soil properties were used to map spatial variations in soil characteristics across a Long-Term Experiment in Norfolk, England. The relationship between plot ECa across the 3 ha experiment and agronomic data across three different nitrogen rates (0, 110, and 220 kg N ha-1) over five wheat years (2010–2020) was quantified. The Sirius crop model was parameterized for two soils representing the extremes of ECa. Sirius was validated using recorded plot data. Site-specific optimal nitrogen and associated leaching risks were simulated across 29 years of weather data. Variation in soil properties had significant impact on measured NUE. At 220 kg N ha-1 mean observed yields across 5 years ranged from 9.0 to 10.7 t ha-1 and grain protein from 11.6% to 11% on the low EC and high EC plots, respectively. On average fertiliser grain N recovery was 19.7 kg N ha-1 lower on the low ECa plots. Sirius simulated the variation in yield, grain protein and grain N recovery to a good level of accuracy with RRMSE of 19.5%, 15.4% and 19.5%, respectively. Simulated optimal nitrogen on the low EC soils was on average 12 kg N ha-1 lower, with >1 in 4 years with optimal nitrogen <200 kg N ha-1. Our work demonstrated that using a combination of proximal soil EC scans and targeted soil sampling we can optimize the data requirements for model parameterisation to support site-specific N management