Agricultural Systems Journal Impact Factor & Information

Current impact factor: 2.91

Impact Factor Rankings

2015 Impact Factor Available summer 2016
2014 Impact Factor 2.906
2011 Impact Factor 2.899

Additional details

5-year impact 3.43
Cited half-life 8.20
Immediacy index 0.53
Eigenfactor 0.01
Article influence 1.04
ISSN 1873-2267

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: The Republic of Ireland was one of a minority of EU member states to include direct controls on chemical phosphorus (P) fertilisers in its EU Nitrates Directive National Action Plan, first introduced in 2006. This study estimates farm gate phosphorus balances and use efficiencies across 150 specialist dairy farms over the seven year period since these controls were introduced (2006-2012) using nationally representative data. Results indicate that P balances declined by 50% over the study period from 11.9 in 2006 to 6.0kgha-1 in 2012. This decline was driven by a reduction in chemical fertiliser imports of 6.5kgha-1. This is equivalent to a reduction of 281kg of P and represents a cost saving of €812 per annum across the average farm. Phosphorus use efficiency also improved over the period from 60% in 2006 to 78% in 2012, peaking in 2011 at 88.3%. This was achieved while increasing milk solids output per hectare and per cow. Results of a random effects panel data model indicated that P balance and use efficiency are significantly influenced by factors such as fertiliser prices, stocking rates, land use potential, use of milk recording technology, contact with extension services and rainfall patterns.
    Agricultural Systems 02/2016; 142:1-8. DOI:10.1016/j.agsy.2015.10.007
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    ABSTRACT: It has been suggested that during the first half of the 21st century food production will need to increase by 50-70% using nearly the same amount of land, and under increasing pressures of climate change, to meet the demand of an increasingly crowded world. The challenge is significant, though there are also opportunities, particularly in sub-Saharan Africa where productivity gaps are largest. Here we report results from a participatory modeling exercise that aimed to identify feasible pathways for the sustainable intensification of agriculture in Manica Province, Mozambique. We used a combination of farmer questionnaires (n=52) and a cropping systems model (APSIM) to derive the likely causes and magnitude of existing gaps in maize yield, and agronomic nitrogen use efficiency. Results showed highly variable (i.e. season to season and site-to-site - 35% and 42% CV respectively) maize yields - regardless of nitrogen input use. Variability in soil fertility status and basic agronomic management (primarily sowing density) were the main drivers explaining site-to-site variability, while rainfall explained much of the season-to-season variability. Best-practice sowing densities (1 to 4.5pl./m2) were dependent on farmers' N inputs and agro-ecology. In most cases, the highest simulated yields were observed at sowing densities far below those recommended by the local extension services (4.4pl./m2). Estimates of returns on N inputs indicated that N fertilization was highly profitable for medium- and higher-performing farmers. Poor performing farmers could still make profits from investing in N fertilizers, but returns were lower than those of the better performers. We identified important knowledge gaps among the poorest performing smallholder. These gaps in knowledge related to simple principles of good agronomic practice - e.g. suitable plant populations, row spacing and sowing dates. We estimate that if these issues were addressed (i.e. with present levels of on farm investment) maize production could be increased by 120% from 309kg/ha to 682kg/ha, among 17% of the population of farmers. We also calculated that by re-investing a fraction (a third) of the proceeds from improving productivity, a further increase in productivity of 64% could be achieved, lifting yields from 682kg/ha to 1118kg/ha. We conclude that as a first stepping stone in lifting productivity, focus should aim to provide the poorer performing farmers simple recommendations for basic agronomic management that account for the specificities of local climate and soil conditions, before costly technological innovations (e.g. fertilizers, herbicides) are introduced.
    Agricultural Systems 02/2016; 142:9-22. DOI:10.1016/j.agsy.2015.10.010

  • Agricultural Systems 02/2016; 142:70-83. DOI:10.1016/j.agsy.2015.11.008

  • Agricultural Systems 02/2016; 142:41-50. DOI:10.1016/j.agsy.2015.11.004
  • Annachiara Forte · Amalia Zucaro · Gionata De Vico · Angelo Fierro ·

    Agricultural Systems 02/2016; 142:99-111. DOI:10.1016/j.agsy.2015.11.010

  • Agricultural Systems 02/2016; 142:51-69. DOI:10.1016/j.agsy.2015.11.005

  • Agricultural Systems 02/2016; 142:23-32. DOI:10.1016/j.agsy.2015.11.002
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    ABSTRACT: Herbicide-resistant weeds are an increasing global problem in crop production systems. To lessen the incidence of herbicide resistance and to prevent the spread of herbicide-resistant weeds many farmers in Australia have adopted weed seed control measures at grain harvest. One new option is known as the Harrington Seed Destructor (HSD). It is a machine that intercepts crop residue from the harvester and then mechanically destroys embedded weed seeds. In this study, the RIM (Ryegrass Integrated Management) model was used to investigate the economic worth of the HSD within integrated weed management strategies applicable to different weed environments, rotations, sizes of cropping programmes and crop yields. Use of the HSD generated increased returns compared to many other weed management strategies in several scenarios, but especially when non-selective herbicide resistance occurred and large areas of high-yielding crops were grown. Emerging trends in grain farming that include larger areas sown to crops, a greater incidence of herbicide-resistant weeds and higher crop yields, when combined with further manufacturing improvement of the HSD, will only further favour the use of the HSD as a key component of integrated weed management.
    Agricultural Systems 02/2016; 142:33-40. DOI:10.1016/j.agsy.2015.11.003

  • Agricultural Systems 12/2015; 141:113-120. DOI:10.1016/j.agsy.2015.10.002
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    ABSTRACT: Quantifying the extent of agricultural land is important for addressing a large range of ecological, environmental, and economic questions. In many cases, answers focused on land use change require fine scale spatial data on the arrangement of crop types. Here we take advantage of the simultaneous availability of fine resolution, geospatial cropland data-the Cropland Data Layer, and comprehensive tabulated data-the USDA Census of Agriculture, to better understand the accuracy of geospatial data and thus, how geospatial data may be used in scientific research. We compared area estimates for cropland and major US crops (corn, soybeans, wheat and small grains) at the county level for the contiguous US in 2012 and for a subset of states in 2007. We find that accuracy of the Cropland Data Layer is high in regions dominated by a few crop types. However, elsewhere in the US accuracy is highly variable with common large areal overestimates and underestimates (+/-. 50% or more). Before employing the CDL and other geospatial data for applications such as measuring fine scale changes in land use, users should be wary of the potentially high misclassification error.
    Agricultural Systems 12/2015; 141:121-125. DOI:10.1016/j.agsy.2015.10.008
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    ABSTRACT: Legumes have been proposed as biorefinery feedstock primarily due to their low nitrogen fertilizer demand, low fossil energy-related greenhouse gas emissions and high protein content, enabling efficient protein feed, food or amino acid production. Grain legumes (pulses) occupy approx. 1.2% of the arable land in Sweden, with faba bean, which is used as a protein feed, being one of the most common. Utilization of the whole crop, including the beans and the remaining aboveground biomass, can enable co-production of feed, food and/or fuel in high quantities, as faba bean has potentially high total biomass yield. In this study, Consequential Life Cycle Assessment (CLCA) was used to analyze a change from the current use of faba bean as protein feed for dairy cows (Reference scenario) to two alternative uses where the whole crop is harvested: whole crop processing in a green biorefinery producing ethanol, protein concentrate feed and fuel briquettes (Biorefinery scenario), or with the whole crop used as roughage feed (Roughage scenario). Impacts on climate change, arable land use and primary fossil energy use were considered. The changed use of faba bean resulted in changes in the feedstuff requirements for dairy cows, which were highly influential for the results. Whole crop harvesting as opposed to bean harvesting with return of crop residues resulted in increased climate impact and energy use during the agricultural and processing stages. On including substitution effects of the products, the Biorefinery scenario resulted in +. 25, - 20% and - 100% change for climate impact, arable land use and energy use, respectively, in relation to the Reference situation. The increase in climate impact was primarily due to soil carbon changes and increased demand for marginal grain. When the whole faba bean crop was used as roughage (Roughage scenario), the corresponding changes were +. 164%, - 130% and +. 167% for climate change, arable land use and energy use, respectively. The increased impact was due to increased use of feed grain as a result of using the protein-rich roughage.
    Agricultural Systems 12/2015; 141:138-148. DOI:10.1016/j.agsy.2015.10.004
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    ABSTRACT: In most landscapes, accurate crop yield forecasting depends on a quantitative understanding of the relation between past weather, management and crop yield variability. We evaluated and improved the regression-based crop yield forecasting methodology currently employed in the MARS-Crop Yield Forecasting System (M-CYFS) for maize in Hungary. We quantified the effect of: 1) different statistical trends; 2) different crop growth simulation model outputs providing weekly predictors; 3) yield prediction lead times and 4) spatial aggregation on the forecast accuracy as evaluated against statistical yield from 1993 to 2012. The LOESS (locally weighted scatterplot smoothing) trend provided the lowest root mean square error (RMSE) in describing the yield timeseries compared to the quadratic and linear trend. Using the WOFOST crop model-based predictors to explain the yield residuals derivedwith each of the three trends, the lowestRMSEswere obtainedwith theWater Limited Leaf Area Index (WLLAI) and Water Limited Above Ground Biomass (WLB) predictors in combination with the LOESS trend. The LOESS trend was used to evaluate the effect of spatially aggregating subnational yield forecasts. During the first half of the crop cycle there are only marginal differences between the NUTS0 (national), NUTS1 (supra-regional), NUTS2 (regional), and NUTS3 (sub-regional) level. However, the NUTS0 forecast had a slightly lower accuracy fromthe start of flowering and onwards, indicating the possible benefit of maintaining spatial detail when aggregating data. The RMSE of the forecasts started to decrease in weeks 24 and 25. Even though therelative soil moisture decreased earliest, the best performing yield forecasts were associated with lead times of about 5-8 weeks before harvest and were obtained with the WLLAI and WLB as predictors. The best forecastswere associated with the critical phenological phases of flowering and grain-filling respectively occurring between weeks 27 to 30 andweeks 31 to 35. The best performing national forecastwas based on NUTS1 level forecasts with an r2 and a RMSE of respectively 0.8565 and 425.9 kg ha-1 using WLLAI as predictor. Finally, wecompared the regression-based forecasts with operational forecasts performed by the Ministry of Agriculture of Hungary and the JRC-MARS forecasts from 2007 to 2012.
    Agricultural Systems 12/2015; 141:94-106. DOI:10.1016/j.agsy.2015.10.001
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    ABSTRACT: This study explores the influences of agricultural systems on a social aspect of farming, namely work satisfaction. We use an individual activity choice model and hypothesize that different systems yield different levels of satisfaction with farming. Farmers of northeast (NE) Germany and Switzerland were surveyed with a joint questionnaire, as these study regions differ widely in terms of farm size and thus in economies of scale. Regression analysis was done in two separate models including different proxies for farm income, namely farm size (n. =. 1137) and perceived financial situation of the farm (n = 1158). The results show that in the large-scale industrialized agricultural system of NE Germany, farmers' work satisfaction is positively affected by both farm income proxies. Both of these elements have a significantly different effect on the work satisfaction of Swiss farmers. Their work satisfaction is not affected by farm size and the positive effect of the perceived financial situation of the farm is significantly less strong for Swiss farmers than for German ones. Thus, monetary return seems to play a major role in utility of farming for NE German farmers, whereas it is less important for Swiss ones. Additionally, the Swiss agricultural system seems to offer qualities besides economic returns for its farmers as they are generally more satisfied with their work despite the lower economic return compared with NE German farmers.
    Agricultural Systems 12/2015; 141:107-112. DOI:10.1016/j.agsy.2015.10.003
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    ABSTRACT: The abatement of ammonia (NH3) and particulate matter (PM) emissions in agriculture reduces damages to human health and biodiversity and provides benefits for society, but also imposes costs on farmers. As NH3 and PM emissions partly originate from the same activities as greenhouse gases, interactions may exist between NH3 and PM emission abatement and greenhouse gas emissions. This study is aimed at estimating the costs and benefits of NH3 and PM emission abatement measures, considering interactions with agricultural greenhouse gas emissions in Germany. We combined an economic-ecological farm model for estimating emission reductions and abatement costs with an integrated environmental impact assessment model for estimating the benefits for human health and biodiversity, with applications to three Federal States in Germany. We reasoned that benefits exceed costs and that synergies with greenhouse gas reduction exist. All NH3 and PM emission abatement measures affected greenhouse gases. In crop production, conservation tillage increased farmers' gross margins and reduced both PM emissions and, via soil carbon sequestration, also greenhouse gas emissions. The benefits depended on the soil type and its carbon sequestration potential, which differ across regions. The substitution of urea fertiliser for calcium ammonium nitrate reduced both NH3 and greenhouse gas emissions. In livestock production, the measures with the highest net benefits were chemical washers for exhaust-air purification, injection or cultivator manure application and concrete manure storage cover. Low-protein pig feeding increased farmers' gross margins and also achieved high net benefits, with the benefits of greenhouse gas emission reduction exceeding those of NH3 emission reduction. Low-protein poultry feeding and biofilters for air purification yielded negative net benefits and were therefore not recommended for implementation. The results confirm interactions of NH3 and PM emission abatement measures with greenhouse gas emissions and suggest that all relevant emission types be integrated in an analysis. Air pollution abatement and climate change mitigation have mainly been addressed in separate policies. Our results suggest that these policies are better integrated so as to stimulate synergies and to define the appropriate ambition level of emission reduction targets.
    Agricultural Systems 12/2015; 141:58-68. DOI:10.1016/j.agsy.2015.09.003