Journal articles: 'Whole-farm'

1

Turvey, Calum G. "Whole Farm Income Insurance." Journal of Risk and Insurance 79, no. 2 (July 8, 2011): 515–40. http://dx.doi.org/10.1111/j.1539-6975.2011.01426.x.

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Turvey, Calum Greig, and J. Lowenberg-DeBoer. "Farm-to-Farm Productivity Differences and Whole-Farm Production Functions." Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie 36, no. 2 (July 1988): 295–312. http://dx.doi.org/10.1111/j.1744-7976.1988.tb03277.x.

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Jagger, Craig. "Whole-Farm vs. Part-Farm Voluntary Land Retirement Programs." North Central Journal of Agricultural Economics 8, no. 1 (January 1986): 41. http://dx.doi.org/10.2307/1349080.

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Schils, R. L. M., M. H. A. de Haan, J. G. A. Hemmer, A. van den Pol-van Dasselaar, J. A. de Boer, A. G. Evers, G. Holshof, J. C. van Middelkoop, and R. L. G. Zom. "DairyWise, A Whole-Farm Dairy Model." Journal of Dairy Science 90, no. 11 (November 2007): 5334–46. http://dx.doi.org/10.3168/jds.2006-842.

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S. Watkins, R. ""Payneham Vale": integrated whole farm Planning." Pacific Conservation Biology 9, no. 1 (2003): 65. http://dx.doi.org/10.1071/pc030065.

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IN 1908, Ron's grandfather, Issac Gray, took up an uncleared block of land 15 km north of Frankland in the south-west of Western Australia (see Fig. 1, Hobbs 2003). During that time he ran a few cattle in the bush and clearing of the native woodlands of Wandoo (white gum) Eucalyptus wandoo, J arrah E. marginata and Marri (Redgum) E. calophylla was slow and tedious. Ron's parents took over the farm in 1947, and with the advent of the bulldozer, clearing of Watkin's property and surrounding district began in earnest during the 1950s. Clearing continued as fast "as money permitted", until almost the last natural vegetation was knocked down in 1978 (Fig. 1). Annual pastures with some cropping (for supplementary feed) were the main source of fodder for sheep and cattle.

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Anderson, Kim B., and John E. Ikerd. "Whole Farm Risk-Rating Microcomputer Model." Journal of Agricultural and Applied Economics 17, no. 1 (July 1985): 183–87. http://dx.doi.org/10.1017/s0081305200017209.

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AbstractThe Risk-Rating Model is designed to give extension specialists, teachers, and producers a method to analyze production, marketing, and financial risks. These risks may be analyzed either individually or simultaneously. The risk associated with each enterprise, for all combinations of enterprises, and for any combination of marketing strategies is estimated. Optimistic, expected, and pessimistic returns above variable cost and/or total cost are presented in the results. The probability that total return will be equal to or greater than variable cost and/or total cost is also estimated.

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Fraser, D. "Site mapping for whole farm planning." Cartography 21, no. 2 (December 1992): 1–8. http://dx.doi.org/10.1080/00690805.1992.9713943.

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Zulauf, Carl. "Whole farm safety net programs: an emerging US farm policy evolution?" Renewable Agriculture and Food Systems 35, no. 4 (August 20, 2019): 435–38. http://dx.doi.org/10.1017/s1742170519000279.

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AbstractThe 2018 farm bill is the latest in a history that dates to 1933. Commodity assistance is the only program in all farm bills, but with evolutionary changes. Current farm commodity programs largely make payments to farms, a stark contrast to the 1930s when they limited supply, put a floor under market price, and dampened price increases via public stocks. Crop insurance, which began as an experimental pilot program in 1938, now has its own farm bill title. Almost all commodity and insurance programs have provided assistance based on a calculation specific to an individual commodity's price and/or yield. However, an evolutionary change to whole farm commodity programs may be in its infant stages. They provide assistance for variation in a farm's aggregate revenue across multiple crops. Whole farm experiments currently exist in both the commodity and crop insurance titles. Analysis of a whole farm commodity program finds that its payments differ by year from actual payments made by current commodity programs and are smaller in total.

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9

Christie, K. M., C. J. P. Gourley, R. P. Rawnsley, R. J. Eckard, and I. M. Awty. "Whole-farm systems analysis of Australian dairy farm greenhouse gas emissions." Animal Production Science 52, no. 11 (2012): 998. http://dx.doi.org/10.1071/an12061.

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The Australian dairy industry contributes ~1.6% of the nation’s greenhouse gas (GHG) emissions, emitting an estimated 9.3 million tonnes of carbon dioxide equivalents (CO2e) per annum. This study examined 41 contrasting Australian dairy farms for their GHG emissions using the Dairy Greenhouse Gas Abatement Strategies calculator, which incorporates Intergovernmental Panel on Climate Change and Australian inventory methodologies, algorithms and emission factors. Sources of GHG emissions included were pre-farm embedded emissions associated with key farm inputs (i.e. grains and concentrates, forages and fertilisers), CO2 emissions from electricity and fuel consumption, methane emissions from enteric fermentation and animal waste management, and nitrous oxide emissions from animal waste management and nitrogen fertilisers. The estimated mean (±s.d.) GHG emissions intensity was 1.04 ± 0.17 kg CO2 equivalents/kg of fat and protein-corrected milk (kg CO2e/kg FPCM). Enteric methane emissions were found to be approximately half of total farm emissions. Linear regression analysis showed that 95% of the variation in total farm GHG emissions could be explained by annual milk production. While the results of this study suggest that milk production alone could be a suitable surrogate for estimating GHG emissions for national inventory purposes, the GHG emissions intensity of milk production, on an individual farm basis, was shown to vary by over 100% (0.76–1.68 kg CO2e/kg FPCM). It is clear that using a single emissions factor, such as milk production alone, to estimate any given individual farm’s GHG emissions, has the potential to either substantially under- or overestimate individual farms’ GHG emissions.

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Hardaker, J. Brian, Louise H. Patten, and David J. Pannell. "UTILITY-EFFICIENT PROGRAMMING FOR WHOLE-FARM PLANNING*." Australian Journal of Agricultural Economics 32, no. 2-3 (August 12, 1988): 88–97. http://dx.doi.org/10.1111/j.1467-8489.1988.tb00677.x.

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Mas, K., G. Pardo, E. Galán, and A. del Prado. "Assessing dairy farm sustainability using whole-farm modelling and life cycle analysis." Advances in Animal Biosciences 7, no. 3 (October 28, 2016): 259–60. http://dx.doi.org/10.1017/s2040470016000340.

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Chang, H. H., and R. N. Boisvert. "Distinguishing between Whole-Farm vs. Partial-Farm Participation in the Conservation Reserve Program." Land Economics 85, no. 1 (December 26, 2008): 144–61. http://dx.doi.org/10.3368/le.85.1.144.

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13

Spears, R. A., A. J. Young, and R. A. Kohn. "Whole-Farm Phosphorus Balance on Western Dairy Farms." Journal of Dairy Science 86, no. 2 (February 2003): 688–95. http://dx.doi.org/10.3168/jds.s0022-0302(03)73648-0.

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Spears, R. A., R. A. Kohn, and A. J. Young. "Whole-Farm Nitrogen Balance on Western Dairy Farms." Journal of Dairy Science 86, no. 12 (December 2003): 4178–86. http://dx.doi.org/10.3168/jds.s0022-0302(03)74033-8.

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15

Robb, James G., John A. Smith, and Daryl E. Ellis. "Estimating Field Machinery Cost: A Whole Farm Approach." Journal of Natural Resources and Life Sciences Education 27, no. 1 (1998): 25–29. http://dx.doi.org/10.2134/jnrlse.1998.0025.

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Bakhshi, Samira, and Richard S. Gray. "Acreage Response to Whole Farm Income Stabilisation Programmes." Journal of Agricultural Economics 63, no. 2 (March 27, 2012): 385–407. http://dx.doi.org/10.1111/j.1477-9552.2011.00332.x.

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17

Hoag, Dana L. "Budget Planner: User-Oriented Whole-Farm Budgeting Software." Journal of Agricultural and Applied Economics 21, no. 1 (July 1989): 163–69. http://dx.doi.org/10.1017/s0081305200001035.

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AbstractBudget Planner is a whole-farm or enterprise budgeting software program that is simple to use for farmers, extension agents, and other budgeters who are sometimes inexperienced, but that also provides the detail necessary to be accurate. Program defaults eliminate repetitive questions that change little from budget to budget. Defaults can be temporarily overridden, or they can be permanently changed with a detailed modify program. The program leads a user through a sequence similar to that a producer might utilize. Input forms were created to enlarge the user clientele and eventually increase computer use by farmers and extension agents.

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Lien, Gudbrand. "Assisting whole-farm decision-making through stochastic budgeting." Agricultural Systems 76, no. 2 (May 2003): 399–413. http://dx.doi.org/10.1016/s0308-521x(02)00079-3.

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19

Abadi Ghadim, A. K. "Water repellency: a whole-farm bio-economic perspective." Journal of Hydrology 231-232 (May 2000): 396–405. http://dx.doi.org/10.1016/s0022-1694(00)00211-0.

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20

Rawnsley, R. P., D. F. Chapman, J. L. Jacobs, S. C. Garcia, M. N. Callow, G. R. Edwards, and K. P. Pembleton. "Complementary forages – integration at a whole-farm level." Animal Production Science 53, no. 9 (2013): 976. http://dx.doi.org/10.1071/an12282.

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A high proportion of the Australian and New Zealand dairy industry is based on a relatively simple, low input and low cost pasture feedbase. These factors enable this type of production system to remain internationally competitive. However, a key limitation of pasture-based dairy systems is periodic imbalances between herd intake requirements and pasture DM production, caused by strong seasonality and high inter-annual variation in feed supply. This disparity can be moderated to a certain degree through the strategic management of the herd through altering calving dates and stocking rates, and the feedbase by conserving excess forage and irrigating to flatten seasonal forage availability. Australasian dairy systems are experiencing emerging market and environmental challenges, which includes increased competition for land and water resources, decreasing terms of trade, a changing and variable climate, an increasing environmental focus that requires improved nutrient and water-use efficiency and lower greenhouse gas emissions. The integration of complementary forages has long been viewed as a means to manipulate the home-grown feed supply, to improve the nutritive value and DM intake of the diet, and to increase the efficiency of inputs utilised. Only recently has integrating complementary forages at the whole-farm system level received the significant attention and investment required to examine their potential benefit. Recent whole-of-farm research undertaken in both Australia and New Zealand has highlighted the importance of understanding the challenges of the current feedbase and the level of complementarity between forage types required to improve profit, manage risk and/or alleviate/mitigate against adverse outcomes. This paper reviews the most recent systems-level research into complementary forages, discusses approaches to modelling their integration at the whole-farm level and highlights the potential of complementary forages to address the major challenges currently facing pasture-based dairy systems.

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Bell, L. W., H. Dove, S. E. McDonald, and J. A. Kirkegaard. "Integrating dual-purpose wheat and canola into high-rainfall livestock systems in south-eastern Australia. 3. An extrapolation to whole-farm grazing potential, productivity and profitability." Crop and Pasture Science 66, no. 4 (2015): 390. http://dx.doi.org/10.1071/cp14202.

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Dual-purpose crops can provide valuable winter forage in livestock production systems and increase subsequent pasture availability. Using experimental measurements of sheep grazing on pasture only or dual-purpose crops of wheat, canola, and wheat and canola in combination, and their associated effects on subsequent pasture grazing, we estimated for two different years the whole-farm changes in whole-farm sheep grazing days (SGD), relative farm production and farm economic impact. The increased winter feed supply and higher grazing intensity on dual-purpose crops allowed 2–3 times the area of pasture to be spelled, which together enabled increases in potential year-round pasture stocking rate. Up to 20% of farm area could be allocated to dual-purpose crops while still obtaining the same number of SGD per farm ha with additional grain production (5.0–5.4 t wheat ha–1 and 1.9–3.6 t canola ha–1) adding significantly to farm profitability and production. Allocating 10–20% of the farm to a combination of dual-purpose wheat and canola grazed in sequence could increase whole-farm SGD by 10–15%, increase farm output by >25% and increase estimated farm profit margin by >AU$150 farm ha–1 compared with pasture-only livestock systems. The long crop-grazing period from wheat and canola in combination providing a large pasture-spelling benefit was a key factor enabling these economic and productivity increases. Introducing wheat or canola alone on up to 30% of the farm is likely to reduce SGD per farm ha, but still significantly increase whole-farm productivity (10–20%) and estimated profit margin ($50–100 farm ha–1). Over the two very different experimental growing seasons, the estimated relative changes in whole-farm productivity and estimated profit margin were similar, indicating that these benefits are likely to be consistent over a range of years. Together, these findings suggest that once whole-farm livestock feed-base effects are considered, large economic and productivity benefits can be attributed to dual-purpose crops when integrated into livestock production systems in Australia’s southern high-rainfall zone.

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D. S. Chianese, C. A. Rotz, and T. L. Richard. "Whole-Farm Greenhouse Gas Emissions: A Review with Application to a Pennsylvania Dairy Farm." Applied Engineering in Agriculture 25, no. 3 (2009): 431–42. http://dx.doi.org/10.13031/2013.26895.

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Jones, Philip, and Andrew Salter. "Modelling the economics of farm-based anaerobic digestion in a UK whole-farm context." Energy Policy 62 (November 2013): 215–25. http://dx.doi.org/10.1016/j.enpol.2013.06.109.

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Deak, Atila, Marvin H. Hall, Matt A. Sanderson, Al Rotz, and Michael Corson. "Whole-Farm Evaluation of Forage Mixtures and Grazing Strategies." Agronomy Journal 102, no. 4 (July 2010): 1201–9. http://dx.doi.org/10.2134/agronj2009.0504.

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Rotz, C. A., F. Taube, M. P. Russelle, J. Oenema, M. A. Sanderson, and M. Wachendorf. "Whole-Farm Perspectives of Nutrient Flows in Grassland Agriculture." Crop Science 45, no. 6 (November 2005): 2139–59. http://dx.doi.org/10.2135/cropsci2004.0523.

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Kearney, M., P. Crosson, E. O. Riordan, and J. Breen. "65. Whole-farm modelling of dairy beef production systems." Animal - science proceedings 13, no. 1 (April 2022): 43. http://dx.doi.org/10.1016/j.anscip.2022.03.066.

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Stirling, Sofía, Santiago Fariña, David Pacheco, and Ronaldo Vibart. "Whole-farm modelling of grazing dairy systems in Uruguay." Agricultural Systems 193 (October 2021): 103227. http://dx.doi.org/10.1016/j.agsy.2021.103227.

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Veselinović, Janko, Todor Marković, and Željko Kokot. "Economic and legal characteristics of whole farm revenue insurance." Zbornik radova Pravnog fakulteta, Novi Sad 52, no. 1 (2018): 181–97. http://dx.doi.org/10.5937/zrpfns52-16542.

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Petersen, S. O., S. G. Sommer, F. Béline, C. Burton, J. Dach, J. Y. Dourmad, A. Leip, et al. "Recycling of livestock manure in a whole-farm perspective." Livestock Science 112, no. 3 (December 2007): 180–91. http://dx.doi.org/10.1016/j.livsci.2007.09.001.

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Schilizzi, Steven G. M., and Fabien Boulier. "‘Why do farmers do it?’ Validating whole-farm models." Agricultural Systems 54, no. 4 (August 1997): 477–99. http://dx.doi.org/10.1016/s0308-521x(96)00095-9.

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Vadas, Peter A., J. Mark Powell, Geoff E. Brink, Dennis L. Busch, and Laura W. Good. "Whole-farm phosphorus loss from grazing-based dairy farms." Agricultural Systems 140 (November 2015): 40–47. http://dx.doi.org/10.1016/j.agsy.2015.08.007.

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Lal, H., J. W. Jones, R. M. Peart, and W. D. Shoup. "FARMSYS—A whole-farm machinery management decision support system." Agricultural Systems 38, no. 3 (January 1992): 257–73. http://dx.doi.org/10.1016/0308-521x(92)90069-z.

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33

Barlow, K., D. Nash, and R. B. Grayson. "Phosphorus export at the paddock, farm-section, and whole farm scale on an irrigated dairy farm in south-eastern Australia." Australian Journal of Agricultural Research 56, no. 1 (2005): 1. http://dx.doi.org/10.1071/ar04166.

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Phosphorus (P) exported from agricultural land contributes to the eutrophication of inland water systems. Although P export has been extensively researched at the paddock scale, our understanding of farm-scale export is limited. This paper presents the results of a 3-year monitoring project that investigated P export at the paddock, farm-section, and whole farm scales on an irrigated dairy farm in south-eastern Australia. Annual average concentrations of 2.2–11 mg P/L, and annual loads of 2.5–23 kg P/ha were measured at the paddock and farm-section scale over the 3 years, with the quality of irrigation water applied having no significant effect on P export in surface runoff. At the farm scale, effective management of the water reuse system significantly reduced phosphorus export by up to 98%. During the 3-year period, P concentrations and loads exported in surface runoff consistently decreased between the paddock and farm-section scales (e.g. P-28 exported 13.8 kg P/ha, whereas S-4 exported 6.7 kg/ha in 2001), with the decrease in P export described using a scaling factor. Our results suggest that data on paddock-scale P export can rarely be proportionally assigned to predict section- or farm-scale export, at least on irrigated dairy farms in south-eastern Australia.

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Egan, A. F. "Farm woodlots in northern New England, USA: Characteristics, management, and contributions to the whole farm system." Renewable Agriculture and Food Systems 22, no. 1 (March 2007): 67–73. http://dx.doi.org/10.1017/s1742170507001627.

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AbstractFarms and forests dominate the rural landscape of the northern New England states of Maine, New Hampshire and Vermont, among the most heavily forested states in the US. However, we know little about the stewardship of farm woodlots and their contributions to the whole farm system, despite region-wide increases in farm forest acreage. Using a mail survey, this study found that almost half of respondents had a written management plan for their forestland, most of which had been written by a forester, and approximately three-quarters took an active role in the management of their woodlots. Farm woodlot harvesting and management contributed over 7% of total farm income. Variables such as respondent's state of residence, age, education and type of farm were investigated in order to better understand farmers’ forest stewardship behavior. Implications for effective outreach to farm forest owners are offered.

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35

Rotz, C. Alan, Michael R. Reiner, Sarah K. Fishel, and Clinton Dean Church. "Whole Farm Performance of Centrifuge Extraction of Phosphorus from Dairy Manure." Applied Engineering in Agriculture 38, no. 2 (2022): 321–30. http://dx.doi.org/10.13031/aea.14863.

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HighlightsA centrifuge can be used to extract manure phosphorus to a more concentrated form for easier transport.Extraction for more efficient transport to distant cropland reduced production costs in a scraped manure system.Use of a centrifuge in a flush manure system was less practical and economical due to handling of much more material.The cost of producing highly concentrated phosphorus material for export was greater than phosphate fertilizer prices.Abstract. As the size of dairy farms has increased, feeds produced on the farm as well as those purchased from off-farm sources can be transported long distances to feed the herd. Transporting the manure back to the cropland used to produce the feed can be difficult and uneconomical. Technology such as a centrifuge can be used to extract nutrients into a more concentrated form for more efficient transport. A dairy farm with 2000 cows and 1400 ha of land in Pennsylvania was simulated with the Integrated Farm System Model to evaluate the feasibility of extracting phosphorus (P) to reduce transport requirements on farm or to produce a concentrated P product for off-farm use. On this farm where manure must be transported to distant cropland to obtain uniform distribution, P extraction with a centrifuge provided a better ratio of nitrogen and P contents for use on nearby cropland and reduced transport costs for nutrients applied to more distant cropland. The centrifuge was found to be more practical and economical when used with manure scraped from the barn floor than with flushed manure because much less material was handled. Moving less material through the centrifuge both improved extraction efficiency and reduced electricity consumption, providing more economical P extraction. To avoid long-term accumulation of soil P on the farm with less land (2000 cows and 1100 ha) where concentrate feed (27% of total feed) was imported, centrifuge extraction provided a material with a high P concentration exported from the farm for other uses. Extracting the P for off-farm use cost about $2.51/kg P, which was greater than the price of phosphate fertilizer, but the extract also included other nutrients and micronutrients of value to crops. A centrifuge provides a useful tool for extracting and concentrating manure P, but the economic benefit to the producer depends upon the value of the full array of nutrient contents in the product, other manure handling practices, and the end use of the extracted material. Reducing the risk of eutrophication of surface waters provides additional benefit to society. Keywords: Dairy farm, Integrated Farm System Model, Manure handling, Manure management.

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Janzen, H. H., D. A. Angers, M. Boehm, M. Bolinder, R. L. Desjardins, J. Dyer, B. H. Ellert, et al. "A proposed approach to estimate and reduce net greenhouse gas emissions from whole farms." Canadian Journal of Soil Science 86, no. 3 (May 1, 2006): 401–18. http://dx.doi.org/10.4141/s05-101.

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Greenhouse gas emissions from farms can be suppressed in two ways: by curtailing the release of these gases (especially N2O and CH4), and by storing more carbon in soils, thereby removing atmospheric CO2. But most practices have multiple interactive effects on emissions throughout a farm. We describe an approach for identifying practices that best reduce net, whole-farm emissions. We propose to develop a “Virtual Farm”, a series of interconnected algorithms that predict net emissions from flows of carbon, nitrogen, and energy. The Virtual Farm would consist of three elements: descriptors, which characterize the farm; algorithms, which calculate emissions from components of the farm; and an integrator, which links the algorithms to each other and the descriptors, generating whole-farm estimates. Ideally, the Virtual Farm will be: boundary-explicit, with single farms as the fundamental unit; adaptable to diverse farm types; modular in design; simple and transparent; dependent on minimal, attainable inputs; internally consistent; compatible with models developed elsewhere; and dynamic (“seeing”into the past and the future). The Virtual Farm would be constructed via two parallel streams - measurement and modeling - conducted iteratively. The understanding built into the Virtual Farm may eventually be applied to issues beyond greenhouse gas mitigation. Key words: CO2, N2O, CH4, agroecosystems, models, climate change

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Čengić-Džomba, Senada, Velid Zilkić, Emir Džomba, and Dženan Hadžić. "WHOLE FARM NITROGEN BALANCE ON POULTRY FARMS IN CENTRAL BOSNIA REGION." Radovi Šumarskog fakulteta Univerziteta u Sarajevu 21, no. 1 (October 1, 2016): 223–30. http://dx.doi.org/10.54652/rsf.2016.v1.i1.298.

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UDK 636.2:66.074.32(497.6) At livestock farms most part of nitrogen arrives as purchased products (fertilizer, animal feed and purchased animals). Within the boundaries of the farm, nitrogen recycles between the livestock and crop components. Finally, nitrogen exit a livestock operation unit preferably as managed outputs (meat, crops and manure) sold off the farm. Difference between the inputs and the managed outputs represents an itrogen balance that can be an indicator of environmentally sustainable production. Nitrogen (im)balance consider only amount of the nutrient that cross the border of the farm. In ideal conditions the nitrogen input/output ratio should be 1:1. Some nitrogen exits the farm as losses to the environment (nitrates in groundwater, ammonia volatilized into the atmosphere, and nitrogen into groundwater and surface water). A study was conducted on five small poultry farm in order to determine whole farm nitrogen balance as difference between total nitrogen inputs (one day chickens, litter, animal feed) and outputs (meat, dead animals and manure). Selected farms differ according to capacity (ranging from 5,000 to 40,000 birds), producers of poultry feed, type and length of manure storage as well as other sensible farming practice which could influence on nitrogen balance. Collection of data on all farms is done using a questionnaire. Nitrogen content in all substrates (feed, manure, litter) was determinate by Kjeldahl procedure. The results of the whole farm nitrogen balance with the recommendations of its balancing in order to reduce the negative environmental implications are presented in the paper.

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Franzen, D. W., J. F. Giles, L. J. Reitmeier, A. J. Hapka, N. R. Cattanach, and A. C. Cattanach. "Use of Whole Field Research to Change Farm Management Practices." Journal of Natural Resources and Life Sciences Education 33, no. 1 (2004): 161–65. http://dx.doi.org/10.2134/jnrlse.2004.0161.

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39

Rotz, C. A., D. R. Mertens, D. R. Buckmaster, M. S. Allen, and J. H. Harrison. "A Dairy Herd Model for Use in Whole Farm Simulations." Journal of Dairy Science 82, no. 12 (December 1999): 2826–40. http://dx.doi.org/10.3168/jds.s0022-0302(99)75541-4.

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Mangudo, Pablo, Mauricio Arroqui, Claudia Marcos, and Claudio F. Machado. "Rescue of a whole-farm system: crystal clear in action." International Journal of Agile and Extreme Software Development 1, no. 1 (2012): 6. http://dx.doi.org/10.1504/ijaesd.2012.048306.

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41

Soberon, Melanie A., Quirine M. Ketterings, Caroline N. Rasmussen, and Karl J. Czymmek. "Whole Farm Nutrient Balance Calculator for New York Dairy Farms." Natural Sciences Education 42, no. 1 (May 20, 2013): 57–67. http://dx.doi.org/10.4195/nse.2012.0020.

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42

Pannell, David J., and Thomas L. Nordblom. "Impacts of risk aversion on whole‐farm management in Syria." Australian Journal of Agricultural and Resource Economics 42, no. 3 (September 1998): 227–47. http://dx.doi.org/10.1111/1467-8489.00048.

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43

Sterk, B., M. K. van Ittersum, C. Leeuwis, W. A. H. Rossing, H. van Keulen, and G. W. J. van de Ven. "Finding niches for whole-farm design models – contradictio in terminis?" Agricultural Systems 87, no. 2 (February 2006): 211–28. http://dx.doi.org/10.1016/j.agsy.2004.11.008.

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Watts, Myles J., Joseph Atwood, and Bruce R. Beattie. "Water degradation implications when whole-farm irrigation water is binding." Water Resources and Economics 9 (January 2015): 3–22. http://dx.doi.org/10.1016/j.wre.2014.11.004.

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45

McPhee, M. J., A. K. Bell, P. Graham, G. R. Griffith, and G. P. Meaker. "PRO Plus: a whole-farm fodder budgeting decision support system." Australian Journal of Experimental Agriculture 40, no. 4 (2000): 621. http://dx.doi.org/10.1071/ea99050.

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This paper describes PRO Plus, a whole-farm fodder budgeting decision support system for beef, sheep meat and wool producers. The program predicts the pasture mass available at the end of each month for individual paddocks based on pasture growth rates, number of stock, intake and the grazing plan where producers allocate mobs weekly to paddocks. Two case studies are presented that identify how the program can be used individually or in conjunction with other programs to make management decisions. PRO Plus is an integral component of the PROGRAZE Plus course and assists producers to improve the financial viability and sustainability of their farms through better pasture and grazing management.

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Cacho, O. J., J. D. Finlayson, and A. C. Bywater. "A simulation model of grazing sheep: II. Whole farm model." Agricultural Systems 48, no. 1 (January 1995): 27–50. http://dx.doi.org/10.1016/0308-521x(95)93644-s.

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Bailey, DeeVon, and James W. Richardson. "Analysis of Selected Marketing Strategies: A Whole‐Farm Simulation Approach." American Journal of Agricultural Economics 67, no. 4 (November 1985): 813–20. http://dx.doi.org/10.2307/1241821.

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Sonneveld, M. P. W., J. J. Schröder, J. A. de Vos, G. J. Monteny, J. Mosquera, J. M. G. Hol, E. A. Lantinga, F. P. M. Verhoeven, and J. Bouma. "A Whole-Farm Strategy to Reduce Environmental Impacts of Nitrogen." Journal of Environmental Quality 37, no. 1 (January 2008): 186–95. http://dx.doi.org/10.2134/jeq2006.0434.

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Shockley, Jordan, Carl R. Dillon, Tim Stombaugh, and Scott Shearer. "Whole farm analysis of automatic section control for agricultural machinery." Precision Agriculture 13, no. 4 (January 14, 2012): 411–20. http://dx.doi.org/10.1007/s11119-011-9256-z.

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Dong, Fengxia, Paul D. Mitchell, Deana Knuteson, Jeffery Wyman, A. J. Bussan, and Shawn Conley. "Assessing sustainability and improvements in US Midwestern soybean production systems using a PCA–DEA approach." Renewable Agriculture and Food Systems 31, no. 6 (November 20, 2015): 524–39. http://dx.doi.org/10.1017/s1742170515000460.

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AbstractDocumentation of on-farm sustainability in agricultural sectors is becoming an essential element to ensure market access. An assessment process was developed to help soybean farmers document practices and verifiable advances in community, environmental and economic sustainability. Technical difficulties in analyzing and summarizing such assessment data include a large number of practices, correlation in variables, and use of discrete measures. By combining non-negative principal components analysis and common-weight data envelopment analysis, we overcame these difficulties to calculate a composite sustainability index for each individual farm and for the farm group as a whole. Applying this method to assessment data from 410 US Midwestern soybean farmers gave average sustainability scores of 0.846 and 0.842 for the soybean-specific and whole-farm assessments, respectively. Scenario analysis examined the impact if the bottom 10% of growers adopted the top ten sustainability drivers identified by the analysis. The average sustainability score only increased by 2%, but the minimum score increased from 0.515 to 0.647 for the soybean-specific assessment, and from 0.624 to 0.685 for the whole-farm assessment, while the lowest 10th percentile increased from 0.635 to 0.819 for the soybean-specific assessment, and from 0.634 to 0.920 for the whole-farm assessment. These results suggest that significant advancements could be made through focused efforts to improve adoption of sustainable practices by soybean farmers at the lower end of the spectrum.

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Journal articles on the topic 'Whole-farm'

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