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@article{Edwards CB:1970,
author = {Edwards CB, Jordan DL, Owen MD, Dixon PM, Young BG, Wilson RG, Weller SC, Shaw DR, },
title = {{Benchmark study on glyphosate-resistant crop systems in the United States. Economics of herbicide resistance management practices in a 5 year field-scale study.
        }},
journal = {Pest management science},
year = {2014},
month = {nov},
pmid = {24664628},
abstract = {BACKGROUND: Since the introduction of glyphosate-resistant (GR) crops, growers have often relied on glyphosate-only weed control programs. As a result, multiple weeds have evolved resistance to glyphosate. A 5 year study including 156 growers from Illinois, Iowa, Indiana, Nebraska, North Carolina and Mississippi in the United States was conducted to compare crop yields and net returns between grower standard weed management programs (SPs) and programs containing best management practices (BMPs) recommended by university weed scientists. The BMPs were designed to prevent or mitigate/manage evolved herbicide resistance.
RESULTS: Weed management costs were greater for the BMP approach in most situations, but crop yields often increased sufficiently for net returns similar to those of the less expensive SPs. This response was similar across all years, geographical regions, states, crops and tillage systems.
CONCLUSIONS: Herbicide use strategies that include a diversity of herbicide mechanisms of action will increase the long-term sustainability of glyphosate-based weed management strategies. Growers can adopt herbicide resistance BMPs with confidence that net returns will not be negatively affected in the short term and contribute to resistance management in the long term.
},
added = {2018-07-19T13:46:56GMT+00:00},
uri = {\url{http://www.ncbi.nlm.nih.gov/pubmed/24664628}}
}

@article{Pandolfi F:1970,
author = {Pandolfi F, Stoddart K, Wainwright N, Kyriazakis I, Edwards SA, },
title = {{The 'Real Welfare' scheme: benchmarking welfare outcomes for commercially farmed pigs.
        }},
journal = {Animal : an international journal of animal bioscience},
year = {2018},
month = {mar},
pmid = {28249629},
abstract = {Animal welfare standards have been incorporated in EU legislation and in farm assurance schemes, based on scientific information and aiming to safeguard the welfare of the species concerned. Recently, emphasis has shifted from resource-based measures of welfare to animal-based measures, which are considered to assess more accurately the welfare status. The data used in this analysis were collected from April 2013 to May 2016 through the 'Real Welfare' scheme in order to assess on-farm pig welfare, as required for those finishing pigs under the UK Red Tractor Assurance scheme. The assessment involved five main measures (percentage of pigs requiring hospitalization, percentage of lame pigs, percentage of pigs with severe tail lesions, percentage of pigs with severe body marks and enrichment use ratio) and optional secondary measures (percentage of pigs with mild tail lesions, percentage of pigs with dirty tails, percentage of pigs with mild body marks, percentage of pigs with dirty bodies), with associated information about the environment and the enrichment in the farms. For the complete database, a sample of pens was assessed from 1928 farm units. Repeated measures were taken in the same farm unit over time, giving 112 240 records at pen level. These concerned a total of 13 480 289 pigs present on the farm during the assessments, with 5 463 348 pigs directly assessed using the 'Real Welfare' protocol. The three most common enrichment types were straw, chain and plastic objects. The main substrate was straw which was present in 67.9% of the farms. Compared with 2013, a significant increase of pens with undocked-tail pigs, substrates and objects was observed over time (P0.3). The results from the first 3 years of the scheme demonstrate a reduction of the prevalence of animal-based measures of welfare problems and highlight the value of this initiative.},
added = {2018-07-19T13:45:19GMT+00:00},
uri = {\url{http://www.ncbi.nlm.nih.gov/pubmed/28249629}}
}

@article{Zuliani A:1970,
author = {Zuliani A, Mair M, Kraševec M, Lora I, Brscic M, Cozzi G, Leeb C, Zupan M, Winckler C, Bovolenta S, },
title = {{A survey of selected animal-based measures of dairy cattle welfare in the Eastern Alps: Toward context-based thresholds.
        }},
journal = {Journal of dairy science},
year = {2018},
month = {jan},
pmid = {29224861},
abstract = {In the Alps, traditional dairy farms are small-scale operations where vertical transhumance from valley indoor housing systems to highland pasture-based systems is still practiced in summer. Vertical transhumance implies a substantial change of environment, available resources, and management practices from one season to another. In such systems, animal-based welfare measures need to be monitored throughout the year to capture the variation of welfare outcomes, based on which targeted welfare management plans can be implemented. Because the Welfare Quality assessment approach has been tailored to indoor housing and intensive farming systems, the European Food Safety Authority recently developed a welfare assessment protocol for small-scale dairy cattle farms adapted after the Welfare Quality framework. The aim of this study was to assess nonbehavioral animal-based measures as defined by this protocol at different time points for transhumant systems in the Alps. In total, 18 animal-based measures were assessed before, during, and after the mountain pasture period in a sample of 67 small-scale dairy cattle farms practicing vertical transhumance in neighboring provinces of Austria, Italy, and Slovenia. Significant differences between assessments were identified for dirtiness of legs and teats, hairless patches, lesions and swellings, claw condition, ocular discharge, and diarrhea whereas BCS, lameness/severe lameness, vulvar discharge, nasal discharge, and hampered respiration were unchanged between seasons. In addition, a benchmarking exercise was carried out to identify relative boundaries (worst quartile thresholds) for each animal-based measure and to contribute to the discussion about achievable welfare outcomes for the 2 husbandry conditions that characterize a transhumant system. Worst quartile thresholds indicated a high prevalence of dirtiness (>80%) when cows were kept indoors, high prevalence of hairless patches (65%) before pasture turnout, and high prevalence of very lean cows (>13%) throughout the assessments. On the other hand, the best quartile thresholds for most clinical conditions suggested that high welfare standards (zero prevalence) are widely achievable in mountain farms practicing vertical transhumance during all assessments. The thresholds identified through benchmarking should serve as the basis for an effective context-based welfare management strategy promoting continuous welfare improvement on-farm.},
added = {2018-07-19T13:44:42GMT+00:00},
uri = {\url{http://www.ncbi.nlm.nih.gov/pubmed/29224861}}
}

@article{Long NV:1970,
author = {Long NV, Assefa Y, Schwalbert R, Ciampitti IA, },
title = {{Maize Yield and Planting Date Relationship: A Synthesis-Analysis for US High-Yielding Contest-Winner and Field Research Data.
        }},
journal = {Frontiers in plant science},
year = {2018},
month = {jan},
pmid = {29312377},
abstract = {For maize (<i>Zea mays</i> L.), early planting date could be of advantage to high yields but a review of planting date effect on high-yielding data is not yet available. Following this rationale, a synthesis-analysis was conducted from the farmer annual maize contest-winner data (<i>n</i> = 16171 data points; 2011-2016 period); cordially provided by the National Corn Growers Association and a scientific literature dataset collected from research publications since the last three decades. The main objectives of this study were to: (i) identify spatial yield variability within the high-yielding maize dataset; (ii) understand the impacts of planting date on yield variability; (iii) explore the effect of management practices on maize yield-planting date relationship, and (iv) utilize the yield-planting date dataset collected via farmer contest-winner as a benchmarking data to be compared to the compendium of scientific literature available for yield-planting date relationship for the primary US maize producing regions. Major findings of this study are: (i) significant correlation between planting date and latitude, (ii) maize yield was maximized when planting window was 89-106 day of the year (DOY) for the 30-35&#176;N, 107-118 DOY for the 35-40&#176;N, &lt;119 DOY for 40-45&#176;N, and &lt;129 DOY for 45-50&#176;N, and (iii) both, yield contest and literature datasets portrayed that planting date becomes a more relevant factor when planting late, presenting a relatively smaller planting window in high-compared to low-latitudes.},
added = {2018-07-19T13:44:11GMT+00:00},
uri = {\url{http://www.ncbi.nlm.nih.gov/pubmed/29312377}}
}

@article{Häsler B:1970,
author = {Häsler B, Alarcon P, Raboisson D, Waret-Szkuta A, Rushton J, },
title = {{Integration of production and financial models to analyse the financial impact of livestock diseases: a case study of Schmallenberg virus disease on British and French dairy farms.
        }},
journal = {Veterinary record open},
year = {2015},
month = {sep},
pmid = {26392883},
abstract = {AIMS AND OBJECTIVES: The aim of the study was to investigate and compare the financial impact of Schmallenberg disease for different dairy production types in the United Kingdom and France.
MATERIALS AND METHODS: Integrated production and financial models for dairy cattle were developed and applied to Schmallenberg virus (SBV) disease in a British and French context. The five main production systems that prevail in these two countries were considered. Their respective gross margins measuring the holding's profitability were calculated based on public benchmarking, literature and expert opinion data. A partial budget analysis was performed within each production model to estimate the impact of SBV in the systems modelled. Two disease scenarios were simulated: low impact and high impact.
RESULTS: The model gross margin obtained per cow space and year ranged from £1014 to £1484 for the UK and from £1037 to £1890 for France depending on the production system considered. In the UK, the net SBV disease costs in £/cow space/year for an average dairy farm with 100 milking spaces were estimated between £16.3 and £51.4 in the high-impact scenario and between £8.2 and £25.9 in the low-impact scenario. For France, the net SBV disease costs in £/cow space/year ranged from £19.6 to £48.6 in the high-impact scenario and £9.7 to £22.8 in the low-impact scenario, respectively.
CONCLUSION: The study illustrates how the combination of production and financial models allows assessing disease impact taking into account differing management and husbandry practices and associated price structures in the dairy sector. It supports decision-making of farmers and veterinarians who are considering disease control measures as it provides an approach to estimate baseline disease impact in common dairy production systems in the UK and France.
},
added = {2018-07-19T13:43:32GMT+00:00},
uri = {\url{http://www.ncbi.nlm.nih.gov/pubmed/26392883}}
}

@article{Van Passel S:1970,
author = {Van Passel S, Van Huylenbroeck G, Lauwers L, Mathijs E, },
title = {{Sustainable value assessment of farms using frontier efficiency benchmarks.
        }},
journal = {Journal of environmental management},
year = {2009},
month = {aug},
pmid = {19553001},
abstract = {Appropriate assessment of firm sustainability facilitates actor-driven processes towards sustainable development. The methodology in this paper builds further on two proven methodologies for the assessment of sustainability performance: it combines the sustainable value approach with frontier efficiency benchmarks. The sustainable value methodology tries to relate firm performance to the use of different resources. This approach assesses contributions to corporate sustainability by comparing firm resource productivity with the resource productivity of a benchmark, and this for all resources considered. The efficiency is calculated by estimating the production frontier indicating the maximum feasible production possibilities. In this research, the sustainable value approach is combined with efficiency analysis methods to benchmark sustainability assessment. In this way, the production theoretical underpinnings of efficiency analysis enrich the sustainable value approach. The methodology is presented using two different functional forms: the Cobb-Douglas and the translog functional forms. The simplicity of the Cobb-Douglas functional form as benchmark is very attractive but it lacks flexibility. The translog functional form is more flexible but has the disadvantage that it requires a lot of data to avoid estimation problems. Using frontier methods for deriving firm specific benchmarks has the advantage that the particular situation of each company is taken into account when assessing sustainability. Finally, we showed that the methodology can be used as an integrative sustainability assessment tool for policy measures.},
added = {2018-07-19T13:35:44GMT+00:00},
uri = {\url{http://www.ncbi.nlm.nih.gov/pubmed/19553001}}
}

@article{Kragten S:1970,
author = {Kragten S, De Snoo GR, },
title = {{Benchmarking farmer performance as an incentive for sustainable farming: environmental impacts of pesticides.
        }},
journal = {Communications in agricultural and applied biological sciences},
year = {2004},
month = {may},
pmid = {15151309},
abstract = {Pesticide use in The Netherlands is very high, and pesticides are found across all environmental compartments. Among individual farmers, though, there is wide variation in both pesticide use and the potential environmental impact of that use, providing policy leverage for environmental protection. This paper reports on a benchmarking tool with which farmers can compare their environmental and economic performance with that of other farmers, thereby serving as an incentive for them to adopt more sustainable methods of food production methods. The tool is also designed to provide farmers with a more detailed picture of the environmental impacts of their methods of pest management. It is interactive and available on the internet: www.agriwijzer.nl. The present version has been developed specifically for arable farmers, but it is to be extended to encompass other agricultural sectors, in particular horticulture (bulb flowers, stem fruits), as well as various other aspects of sustainability (nutrient inputs, 'on-farm' biodiversity, etc.). The benchmarking methodology was tested on a pilot group of 20 arable farmers, whose general response was positive. They proved to be more interested in comparative performance in terms of economic rather than environmental indicators. In their judgment the benchmarking tool can serve a useful purpose in steering them towards more sustainable forms of agricultural production. The benchmarking results can also be used by other actors in the agroproduction chain, such as food retailers and the food industry.},
added = {2018-07-19T13:35:06GMT+00:00},
uri = {\url{http://www.ncbi.nlm.nih.gov/pubmed/15151309}}
}

@article{Iribarren D:1970,
author = {Iribarren D, Hospido A, Moreira MT, Feijoo G, },
title = {{Benchmarking environmental and operational parameters through eco-efficiency criteria for dairy farms.
        }},
journal = {The Science of the total environment},
year = {2011},
month = {mar},
pmid = {21371738},
abstract = {Life Cycle Assessment (LCA) is often used for the environmental evaluation of agri-food systems due to its holistic perspective. In particular, the assessment of milk production at farm level requires the evaluation of multiple dairy farms to guarantee the representativeness of the study when a regional perspective is adopted. This article shows the joint implementation of LCA and Data Envelopment Analysis (DEA) in order to avoid the formulation of an average farm, therefore preventing standard deviations associated with the use of average inventory data while attaining the characterization and benchmarking of the operational and environmental performance of dairy farms. Within this framework, 72 farms located in Galicia (NW Spain) were subject to an LCA+DEA study which led to identify those farms with an efficient operation. Furthermore, target input consumption levels were benchmarked for each inefficient farm, and the corresponding target environmental impacts were calculated so that eco-efficiency criteria were verified. Thus, average reductions of up to 38% were found for input consumption levels, leading to impact reductions above 20% for every environmental impact category. Finally, the economic savings arising from efficient farming practices were also estimated. Economic savings of up to 0.13€ per liter of raw milk were calculated, which means extra profits of up to 40% of the final raw milk price.},
added = {2018-07-19T13:34:53GMT+00:00},
uri = {\url{http://www.ncbi.nlm.nih.gov/pubmed/21371738}}
}

@article{Joelsson A:1970,
author = {Joelsson A, Kyllmar K, },
title = {{Implementation of best management practices in agriculture: modelling and monitoring of impacts on nitrogen leaching.
        }},
journal = {Water science and technology : a journal of the International Association on Water Pollution Research},
year = {2002},
month = {jun},
pmid = {12079123},
abstract = {In Kattegat and the coastal water of the Baltic Sea, high nitrogen input from agricultural land is considered to be the main reason for eutrophication. International agreements and governmental programs have set a target to reduce the anthropogenic nitrogen load by 50 percent. Improved nitrogen removal in treatment plants and efforts in agriculture have so far not decreased nitrogen transport to a sufficient extent. In this project the impact of agricultural practices on nitrogen leaching was investigated in two small agricultural catchments in Southwest Sweden. The root-zone leaching was estimated by an indexing technique. Simultaneously the transports in the stream outlets were monitored. During 1995 and 1999 the agricultural practices in the catchments were surveyed. Field data from the first survey indicated that fertilisation did not always match crop requirements, the area of undersown catch crop can be increased and autumn cultivation can be reduced. The second survey was preceded by an advisory campaign where each farmer was visited and presented with an environmental plan including fertilisation, cultivation, and crop rotation for the farm. The plan summarised the best management practices that could be realised under actual conditions. Results from the second survey showed that some changes in the agricultural practices were carried out after the advisory campaign. The nitrogen leaching from the root-zone was then estimated by the indexing technique, both for the time before and after the advisory program. The results showed that the estimated nitrogen leaching, as a mean value for 330 fields, decreased from 53 to 50 kgN ha(-1), due to adjustments of the agricultural practices. Monitoring of stream transports showed values of the same magnitude after correction for retention and other sources. In this short time perspective, decreases in transport due to changes in agricultural practices could not be separated from influence of weather conditions. In comparison to results from the Swedish monitoring programme for agriculture, the measured transports were normal for the region, where annual variation in precipitation and runoff is large. Theoretically, nitrogen leaching could be reduced by one third without any major economic constraints for the farmers. In general, the farmers were positive to advice and willing to try new farming techniques even if some measurements were not fully implemented during the investigation period.},
added = {2018-07-19T13:34:25GMT+00:00},
uri = {\url{http://www.ncbi.nlm.nih.gov/pubmed/12079123}}
}

@article{Bazeley KJ:1970,
author = {Bazeley KJ, Barrett DC, Williams PD, Reyher KK, },
title = {{Measuring the growth rate of UK dairy heifers to improve future productivity.
        }},
journal = {Veterinary journal (London, England : 1997)},
year = {2016},
month = {jun},
pmid = {27256019},
abstract = {Sub-optimal heifer growth is associated with higher disease rates and reduced future performance and longevity in the dairy herd. This report describes a system for measuring heifer growth from birth to first calving that was used on commercial dairy farms in South West England, in order to gather benchmarking data to feed back to farmers. Weights (n = 8443) were collected from 20 farms. There was a marked variation in individual and herd mean growth rates. Overall, calves gained no weight in the first 8 days after birth and had a very low growth rate (median 0.12 kg/day) up to 30 days, a period when feed conversion efficiency is high and calves are vulnerable to disease. Heifers whose growth rate up to 180 days was low were significantly less likely to achieve target service weight (374 kg) by 420 days. Monitoring heifer growth during the rearing period enables farmers to improve heifer growth rates and so impact both the efficiency of heifer rearing and, potentially, the productivity and performance of the adult herd. },
added = {2018-07-19T13:33:44GMT+00:00},
uri = {\url{http://www.ncbi.nlm.nih.gov/pubmed/27256019}}
}

@article{Tremblay M:1970,
author = {Tremblay M, Hess JP, Christenson BM, McIntyre KK, Smink B, van der Kamp AJ, de Jong LG, Döpfer D, },
title = {{Customized recommendations for production management clusters of North American automatic milking systems.
        }},
journal = {Journal of dairy science},
year = {2016},
month = {jun},
pmid = {27157582},
abstract = {Automatic milking systems (AMS) are implemented in a variety of situations and environments. Consequently, there is a need to characterize individual farming practices and regional challenges to streamline management advice and objectives for producers. Benchmarking is often used in the dairy industry to compare farms by computing percentile ranks of the production values of groups of farms. Grouping for conventional benchmarking is commonly limited to the use of a few factors such as farms' geographic region or breed of cattle. We hypothesized that herds' production data and management information could be clustered in a meaningful way using cluster analysis and that this clustering approach would yield better peer groups of farms than benchmarking methods based on criteria such as country, region, breed, or breed and region. By applying mixed latent-class model-based cluster analysis to 529 North American AMS dairy farms with respect to 18 significant risk factors, 6 clusters were identified. Each cluster (i.e., peer group) represented unique management styles, challenges, and production patterns. When compared with peer groups based on criteria similar to the conventional benchmarking standards, the 6 clusters better predicted milk produced (kilograms) per robot per day. Each cluster represented a unique management and production pattern that requires specialized advice. For example, cluster 1 farms were those that recently installed AMS robots, whereas cluster 3 farms (the most northern farms) fed high amounts of concentrates through the robot to compensate for low-energy feed in the bunk. In addition to general recommendations for farms within a cluster, individual farms can generate their own specific goals by comparing themselves to farms within their cluster. This is very comparable to benchmarking but adds the specific characteristics of the peer group, resulting in better farm management advice. The improvement that cluster analysis allows for is characterized by the multivariable approach and the fact that comparisons between production units can be accomplished within a cluster and between clusters as a choice. },
added = {2018-07-19T13:33:34GMT+00:00},
uri = {\url{http://www.ncbi.nlm.nih.gov/pubmed/27157582}}
}

@article{Parker Gaddis KL:1970,
author = {Parker Gaddis KL, Cole JB, Clay JS, Maltecca C, },
title = {{Benchmarking dairy herd health status using routinely recorded herd summary data.
        }},
journal = {Journal of dairy science},
year = {2016},
month = {jan},
pmid = {26709189},
abstract = {Genetic improvement of dairy cattle health through the use of producer-recorded data has been determined to be feasible. Low estimated heritabilities indicate that genetic progress will be slow. Variation observed in lowly heritable traits can largely be attributed to nongenetic factors, such as the environment. More rapid improvement of dairy cattle health may be attainable if herd health programs incorporate environmental and managerial aspects. More than 1,100 herd characteristics are regularly recorded on farm test-days. We combined these data with producer-recorded health event data, and parametric and nonparametric models were used to benchmark herd and cow health status. Health events were grouped into 3 categories for analyses: mastitis, reproductive, and metabolic. Both herd incidence and individual incidence were used as dependent variables. Models implemented included stepwise logistic regression, support vector machines, and random forests. At both the herd and individual levels, random forest models attained the highest accuracy for predicting health status in all health event categories when evaluated with 10-fold cross-validation. Accuracy (SD) ranged from 0.61 (0.04) to 0.63 (0.04) when using random forest models at the herd level. Accuracy of prediction (SD) at the individual cow level ranged from 0.87 (0.06) to 0.93 (0.001) with random forest models. Highly significant variables and key words from logistic regression and random forest models were also investigated. All models identified several of the same key factors for each health event category, including movement out of the herd, size of the herd, and weather-related variables. We concluded that benchmarking health status using routinely collected herd data is feasible. Nonparametric models were better suited to handle this complex data with numerous variables. These data mining techniques were able to perform prediction of health status and could add evidence to personal experience in herd management. },
added = {2018-07-19T13:33:08GMT+00:00},
uri = {\url{http://www.ncbi.nlm.nih.gov/pubmed/26709189}}
}

@article{Colditz IG:1970,
author = {Colditz IG, Ferguson DM, Collins T, Matthews L, Hemsworth PH, },
title = {{A Prototype Tool to Enable Farmers to Measure and Improve the Welfare Performance of the Farm Animal Enterprise: The Unified Field Index.
        }},
journal = {Animals : an open access journal from MDPI},
year = {2015},
month = {oct},
pmid = {26480317},
abstract = {Schemes for the assessment of farm animal welfare and assurance of welfare standards have proliferated in recent years. An acknowledged short-coming has been the lack of impact of these schemes on the welfare standards achieved on farm due in part to sociological factors concerning their implementation. Here we propose the concept of welfare performance based on a broad set of performance attributes of an enterprise and describe a tool based on risk assessment and benchmarking methods for measuring and managing welfare performance. The tool termed the Unified Field Index is presented in a general form comprising three modules addressing animal, resource, and management factors. Domains within these modules accommodate the principle conceptual perspectives for welfare assessment: biological functioning; emotional states; and naturalness. Pan-enterprise analysis in any livestock sector could be used to benchmark welfare performance of individual enterprises and also provide statistics of welfare performance for the livestock sector. An advantage of this concept of welfare performance is its use of continuous scales of measurement rather than traditional pass/fail measures. Through the feedback provided via benchmarking, the tool should help farmers better engage in on-going improvement of farm practices that affect animal welfare. },
added = {2018-07-19T13:32:51GMT+00:00},
uri = {\url{http://www.ncbi.nlm.nih.gov/pubmed/26480317}}
}