Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2024
Abstract
Income comparisons between farm and non-farm households play a crucial role in many aspects of farm policy. Using household income data from tax returns of all Norwegian taxpayers in the period 2006–2015 we study these income differences. We find that the unconditional mean income is higher for farm households, but with important differences depending on the comparison group considered. We also find that the income difference is reduced when we control for differences in the personal characteristics of the different non-farm comparison sub-groups. This finding implies that income comparison using unconditional means, as frequently done in agricultural policy making, is potentially misleading. We also show that the income effect of personal characteristics is not the same for different comparison sub-groups, as has been assumed in previous studies of income disparities. Differences in personal characteristics, and the income effect of those characteristics, therefore need to be accounted for if income comparisons between farmers and non-farmers are to inform farm support policies.
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Authors
Melinda D. Smith Kate D. Wilkins Martin C. Holdrege Peter Wilfahrt Scott L. Collins Alan K. Knapp Osvaldo E. Sala Jeffrey S. Dukes Richard P. Phillips Laura Yahdjian Laureano A. Gherardi Timothy Ohlert Claus Beier Lauchlan H. Fraser Anke Jentsch Michael E. Loik Fernando T. Maestre Sally A. Power Qiang Yu Andrew J. Felton Seth M. Munson Yiqi Luo Hamed Abdoli Mehdi Abedi Concepción L. Alados Juan Alberti Moshe Alon Hui An Brian Anacker Maggie Anderson Harald Auge Seton Bachle Khadijeh Bahalkeh Michael Bahn Amgaa Batbaatar Taryn Bauerle Karen H. Beard Kai Behn Ilka Beil Lucio Biancari Irmgard Blindow Viviana Florencia Bondaruk Elizabeth T. Borer Edward W. Bork Carlos Martin Bruschetti Kerry M. Byrne James F. Cahill Dianela A. Calvo Michele Carbognani Augusto Cardoni Cameron N. Carlyle Miguel Castillo-Garcia Scott X. Chang Jeff Chieppa Marcus V. Cianciaruso Ofer Cohen Amanda L. Cordeiro Daniela F. Cusack Sven Dahlke Pedro Daleo Carla M. D'Antonio Lee H. Dietterich Tim S. Doherty Maren Dubbert Anne Ebeling Nico Eisenhauer Felícia M. Fischer Tai G.W. Forte Tobias Gebauer Beatriz Gozalo Aaron C. Greenville Karlo G. Guidoni-Martins Heather J. Hannusch Siri Vatsø Haugum Yann Hautier Mariet Hefting Hugh A.L. Henry Daniela Hoss Oscar Iribarne Forest Isbell Yari Johnson Samuel Jordan Eugene F. Kelly Kaitlin Kimmel Juergen Kreyling György Kröel-Dulay Johannes Ingrisch Alicia Kröpfl Angelika Kübert Andrew Kulmatiski Eric G. Lamb Klaus Steenberg Larsen Julie Larson Cintia V. Leder Anja Linstädter Jielin Liu Shirong Liu Alexandra G. Lodge Grisel Longo Alejandro Loydi Junwei Luan Jason Lawson Frederick Curtis Lubbe Craig Macfarlane Kathleen Mackie-Haas Andrey V. Malyshev Adrián Maturano-Ruiz Thomas Merchant Daniel B. Metcalfe Akira S. Mori Edwin Mudongo Gregory S. Newman Uffe N. Nielsen Dale Nimmo Yujie Niu Paola Nobre Rory C. O'Connor Romà Ogaya Gastón R. Oñatibia Ildikó Orbán Brooke Osborne Rafael Otfinowski Meelis Pärtel Josep Penuelas Pablo L. Peri Guadalupe Peter Alessandro Petraglia Catherine Picon-Cochard Valério D. Pillar Juan Manuel Piñeiro-Guerra Laura W. Ploughe Robert M. Plowes Cristy Portales-Reyes Suzanne M. Prober Yolanda Pueyo Sasha C. Reed Euan G. Ritchie Dana Aylén Rodríguez William E. Rogers Christiane Roscher Ana M. Sánchez Bráulio A. Santos María Cecilia Scarfó Eric W. Seabloom Baoku Shi Lara Souza Andreas Stampfli Rachel J. Standish Marcelo Sternberg Wei Sun Marie Sünnemann Michelle Tedder Pål Thorvaldsen Dashuan Tian Katja Tielbörger Alejandro Valdecantos Liesbeth van den Brink Vigdis Vandvik Mathew R. Vankoughnett Liv Guri Velle Changhui Wang Yi Wang Glenda M. Wardle Christiane Werner Cunzheng Wei Georg Wiehl Jennifer L. Williams Amelia A. Wolf Michaela Zeiter Fawei Zhang Juntao Zhu Ning Zong Xiaoan ZuoAbstract
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Abstract
Ensiling is a common mode of preservation of animal feed. In this process, the feed undergoes lactic acid fermentation in an anaerobic environment, which decreases pH and inhibits degradation of the feed and its nutritive value. Common silos include top loaded tower silos, side loaded bunker silos (also called horizontal silos), underground pit and trench silos, and bales and tubes wrapped in plastic film. Previous studies have revealed that the type of silo often have an impact on silage properties and feed value, but these effects can vary between silage materials. Silage density is another key factor for silage nutritive value and losses. Generally, high density results in smaller losses than low density, both in bunker silos and bales, but the density effect can also be influenced by properties of the ensiled material. The objectives of this literature review were to identify factors and conditions that can modify the effect of i) silage density, and ii) silo type on dry matter losses, leaching of nutrients, fermentation characteristics, silage feed value and mycotoxins contamination. A systematic literature search was carried out in in the Web of Science core collection platform of databases. Most studies showed positive correlations between silage density, and fermentation and feed value, and negative correlations with DM losses. The majority of these studies were conducted at laboratory scale and there was also a great variation in the magnitude of these effects. Further investigations at farm scale may provide more information about the consistency of these effects across experimental scales. The silo type comparisons indicate that silage bales, bags and tubes can be favourable for silage quality and dry matter preservation compared to bunker silos, but information on silo type effects on important crops such as maize is missing.
Authors
Rasmus Bang Bjørn Gunnar Hansen Mario Guajardo Jon Kristian Sommerseth Ola Flaten Leif Jarle AsheimAbstract
CONTEXT An important question for farmers is whether to run their farm conventionally or organically. This choice can significantly affect the farm's financial performance and its impact on the environment. OBJECTIVE The primary objective of this study is to compare the profitability of conventional and organic cattle systems and investigate how it is associated with individual farm characteristics, like forage production capacity, forage quality, milk quota, animal housing capacity, and their relative presences. METHOD We employ a whole farm optimization model, customized for Norwegian cattle farming. The primary goal of this model is to maximize the gross margin by optimizing decisions related to land usage and animal inventory while adhering to a set of constraints. We systematically solve more than 200,000 model instances, with varying farm characteristics. RESULTS AND CONCLUSIONS The results can be distilled to the following key points: If forage of good quality is readily available, but the livestock operation cannot be expanded due to animal housing and milk quota restrictions, organic may outcompete conventional farming. Otherwise, gross margin is maximized with conventional farming. These findings emphasize the crucial role of forage production capacity and quality in relation to available milk quota and infrastructure when considering the transition from conventional to organic farming. Extensive sensitivity analyses affirm the robustness of these conclusions. Regional regulatory factors, such as government farm payments, also play a significant role, and influence the optimal farming approach. Additionally, we show that increases in organic price premiums can markedly impact the competitiveness of organic farming, even in a system where government payments make out a significant part of the farm revenue. SIGNIFICANCE The model can support farmers to make informed decisions about converting to organic or conventional farming. It can also be used by policymakers to determine the level of support required to make it worthwhile for different types of farms to convert. We also show that existing government payment schemes give rise to regional differences in the incentives for organic farming in Norway. To ensure equal incentives for organic farming across the country, the organic payments would have to be regionally adjusted, in line with the other already regionally dependent government payments. This insight may be of significant interest to policymakers and other stakeholders.
Authors
Mario Guajardo Rasmus Bang Leif Jarle Asheim Ola Flaten Bjørn Gunnar Hansen Jon Kristian SommersethAbstract
No abstract has been registered
Authors
Mario Guajardo Rasmus Bang Leif Jarle Asheim Ola Flaten Bjørn Gunnar Hansen Jon Kristian SommersethAbstract
Interest for organic products and concerns regarding sustainable practices raise an important question for farmers: should they run their farms conventionally or organically? We address this question by means of a mathematical programming model, which aims to optimize gross margin of cattle farms. We implement the model using data from Norway, including government support stipulations and a number of other features. A computational study allows us to assess the economic performance of organic farming compared to conventional farming systems. We derive some insights into the conditions when organic outperforms conventional systems, and vice versa. These hold significant relevance not only to farmers, but also to farm advisors and policy makers.