Extended grazing: A detailed analysis of Irish dairy farms

Profitability and factors affecting grazing season length were econometrically analyzed using a representative sample of Irish dairy farms. The objective of this study was to explore what potential exists on Irish dairy farms to extend the grazing season and to quantify the possible economic benefits that result from lengthening the grazing season. Regression results indicate that location factors affect the length of the grazing season, but even when physical factors are controlled, farmer characteristics, such as education, also affect the grazing season length. The results of a panel data analysis show that significant cost reductions can be achieved by extending the grazing season. Overall, the findings indicate that lengthening the grazing season offers a cost-saving alternative on many Irish dairy farms, which could contribute to strengthening the competitiveness of the Irish dairy sector

Financial benchmarking on dairy farms: Exploring the relationship between frequency of use and farm performance

peer-reviewedThe importance of financial benchmarking has increased in recent years as European Union milk quota abolition has facilitated rapid change in the dairy sector. This study evaluates the association between usage frequency of a financial benchmarking tool [Profit Monitor (PM)] and farm changes on spring-calving pasture-based dairy farms. To this end, physical and financial data for 5,945 dairy farms, representing 20,132 farm years, for the years 2010 to 2018 were used. Farms were categorized by frequency of annual financial benchmarking over the 9-yr period into frequent PM users (7–9 yr), infrequent PM users (4–6 yr), low PM users (1–3 yr), and nonusers. We use a mixed model framework and econometric models to characterize farms and to explore characteristics and determinants of economic performance and user groups. The most frequent users of the financial benchmarking tool had the greatest increase in intensification (measured by change in farm stocking rate), productivity (measured by change in milk production per hectare), and financial performance (measured by change in farm gross output and net profit per hectare) across the study period. Infrequent and low PM users of the benchmarking tool were intermediate for all variables measured, whereas nonusers had the least change. Empirical results indicated that economic performance was positively associated with dairy specialization and pasture utilization for all groups. Despite considerable fluctuations over the observation period, the overall change in total farm net profit between 2010 and 2018 was greatest for the frequent PM users (an increase of 70%, or €37,639), followed by farms in the infrequent PM user category (a 71% increase corresponding to an increase of €28,008 in net profit); meanwhile, low PM user and nonuser categories showed increases of 69% (€26,270) and 42% (€10,977), respectively. The results of this study also clearly indicated the existence of a strong positive association between frequency of financial benchmarking and greater technical and financial efficiency. The econometric analysis revealed that financial benchmarking users are more likely than nonusers to have larger herds, and that regional differences exist in usage rates. Finally, the study concludes by suggesting that the development of simplified financial benchmarking technologies and their support are required to increase benchmarking frequency, which may also help to facilitate a more sustainable and resource efficient dairy industry

Socioeconomic determinants of organic cotton adoption in Benin, West Africa

Organic cotton relies on ecological processes and the use of natural resources to sustain the production system, unlike conventional cotton, mainly characterized by massive utilization of synthesis chemicals. In West Africa, where rural livelihoods are particularly vulnerable, organic cotton is expected to contribute not only to poverty reduction but also to strengthen households’ resilience. The objective of this study was to assess institutional and socioeconomic factors determining farmers’ decisions to adopt organic cotton. For this purpose, we applied a probit model on empirical data collected from producers of the Centre and the Northern parts of Benin. Overall, we found that organic cotton adoption is mainly determined by farmers’ socioeconomic characteristics, the physical distance between farm and house, and contact with extension and advisory services. Organic farming is more attractive to women compared to conventional farming. This because such type of cotton farming enables women to hold a separate cotton farm and thus increase their economic independence, whereas with the conventional system they depend mainly on the farm of the (male) head of the household. Older, less educated and low-income farmers who express environmental concern are more likely to adopt organic cotton. Subsequently, organic cotton should be considered as a prospective policy option to reach the poor and strengthen their livelihoods conditions while contributing to preserve the environment and natural resources. Furthermore, farmers who have their farm near home are more likely to adopt organic farming than those who have the farm far from their home. It also came out that organic farmers have more contacts with advisory and extension services. Finally, the study noted that there is still a need to enhance the extension system by: (1) exploring, designing, and upgrading innovative pedagogic tools such as videos and mobile phone technology to foster learning; and (2) strengthening organic farmer’s organizations and the linkage with agricultural research organizations for technology development

Measuring total factor productivity on Irish dairy farms: a Fisher index approach using farm-level data

peer reviewedThis paper presents a Fisher index measure of the total factor productivity (TFP) performance of Irish dairy farms over the period 2006–2016 using the Teagasc National Farm Survey (NFS) data. The removal of milk quotas in 2015 has led to an increase of over 30% in dairy cow numbers since 2010, and although suckler cow numbers have dropped slightly, the total number of cows in Ireland reached an all-time high of 2.5 million head in 2016. This large increase adds to the environmental pressures attributed to agricultural output and puts the focus firmly on how efficiently the additional agricultural output associated with higher cow numbers is produced. The primary purpose of this paper is to identify a standardised measure of the TFP performance of Irish dairy farms that can be routinely updated using Teagasc NFS data. We found that relative to 2010 the TFP of Irish dairy farms has increased by almost 18%; however, in one production year 2015, when milk quota was removed, the TFP measure increased by 7% and TFP continued to grow by 2.5% in the production year 2016. It would seem therefore that the removal of the European dairy quota system has resulted in a windfall gain for Irish dairy farmers but that productivity gains are continuing. Future data will be required to investigate the longer-term TFP performance of Irish dairy farms in the post-milk quota era

An ecological future for weed science to sustain crop production and the environment. A review

Sustainable strategies for managing weeds are critical to meeting agriculture's potential to feed the world's population while conserving the ecosystems and biodiversity on which we depend. The dominant paradigm of weed management in developed countries is currently founded on the two principal tools of herbicides and tillage to remove weeds. However, evidence of negative environmental impacts from both tools is growing, and herbicide resistance is increasingly prevalent. These challenges emerge from a lack of attention to how weeds interact with and are regulated by the agroecosystem as a whole. Novel technological tools proposed for weed control, such as new herbicides, gene editing, and seed destructors, do not address these systemic challenges and thus are unlikely to provide truly sustainable solutions. Combining multiple tools and techniques in an Integrated Weed Management strategy is a step forward, but many integrated strategies still remain overly reliant on too few tools. In contrast, advances in weed ecology are revealing a wealth of options to manage weedsat the agroecosystem levelthat, rather than aiming to eradicate weeds, act to regulate populations to limit their negative impacts while conserving diversity. Here, we review the current state of knowledge in weed ecology and identify how this can be translated into practical weed management. The major points are the following: (1) the diversity and type of crops, management actions and limiting resources can be manipulated to limit weed competitiveness while promoting weed diversity; (2) in contrast to technological tools, ecological approaches to weed management tend to be synergistic with other agroecosystem functions; and (3) there are many existing practices compatible with this approach that could be integrated into current systems, alongside new options to explore. Overall, this review demonstrates that integrating systems-level ecological thinking into agronomic decision-making offers the best route to achieving sustainable weed management

The development and geographic distribution of organic farming in Ireland

This paper explores the development and spatial distribution of organic farming in Ireland. The focus is on the impact of policy, agricultural systems, soil quality, market access, information provision and the influence of neighbouring organic farmers on this development. Geocoded data on organic farms are mapped and spatial concentration is estimated using a location quotient. The results suggest that while organic farming is spread over most of the country, there is evidence of three main spatial clusters. Furthermore, the spatial distribution of organic farming appears to be based on the interaction of a number of determining factors. While certain agricultural systems and soil qualities provide favourable conversion conditions, regional supports, information provision and the impact of pioneering organic farmers may influence spatial clustering of organic farming. In addition, while the availability of organic market outlets is important for organic farming, no clear spatial effect is evident. The paper concludes with a discussion of some policy recommendations aimed at increasing the size of the organic sector

Understanding the uptake of organic farming: accounting for heterogeneities among Irish farmers

This paper examines the decisions of Irish farmers to convert to organic farming by applying the theory of planned behaviour to control for social influence and technical constraints. Cluster analysis and principal component analysis are utilised to account for sample heterogeneity and to identify heterogeneities in farmer beliefs regarding adoption of organic methods. The results indicate that the impact of economic incentives and technical barriers varies, while social acceptance of organic farming constrains adoption. These findings suggest that policy incentives mainly based on subsidy payments may be insufficient to increase the organic sector in the presence of social and technical barriers. -------------------------------------------------------------------------------

Adoption of organic farming: Are there differences between early and late adoption?

Based on the fact that not all farmers adopt a technology at the same time, it is argued in this paper that the distinction between groups is important because early, medium and late adopters respond differently to economic and non-economic factors when they consider whether to take up organic farming or not. The individual effects on adoption between the groups are identified by the use of multinomial logit analysis. The results provide evidence that there are significant differences in the characteristics between the adopter groups. The findings also reveal that the factors that affect adoption play a different role for early, medium and late adopters, particularly with regard to farming intensity, age, information gathering as well as attitudes of the farmer. More specifically, early adopters were the youngest to adopt organic farming and their decisions were found to be less profit related compared to other groups. Late adoption is constrained by risk considerations, while environmental attitudes and social learning were identified to be important determinants for all adopter groups. Overall, the findings strongly suggest, that for policy measures to be effective, the current state of diffusion has to be taken into account