Loser cows in Danish dairy herds: definition, prevalence and consequences

During the last few years, many Danish dairy farmers have expressed increasing concerns regarding a group of cows, which we have chosen to term ‘loser cows’. Until now, a loser cow has not been described scientifically. We defined a loser cow on the basis of a clinical examination of the cow. A total of 15,151 clinical examinations were made on 6,451 individual cows from 39 randomly selected, large Danish dairy herds with loose-housing systems using a clinical protocol. Scores for the clinical signs lameness, body condition, hock lesions, other cutaneous lesions, vaginal discharge, condition of hair coat and general condition were converted into a loser cow score. Cows with a loser cow score of 8 or more were classified as loser cows. The overall prevalence of loser cows was 2.15%, 4.50% and 2.98% during the first, second and third round of herd visits, respectively.

The associations between the loser cow state and milk production, mortality, morbidity, culling and workload for the farmer were evaluated using data from herd visits and from the Danish Cattle Database and a number of different statistical techniques. It was concluded that the loser cow state has significant negative consequences for both the farmer and the cow. On average, loser cows yielded 0.61 to 2.24 kg energy corrected milk less per day than non-loser cows depending on parity. Hazard ratio for death or euthanasia was 5.69 for loser cows compared to non-loser cows. Incidence rate ratio for disease treatments was 0.69 for non-loser cows compared to loser cows. Loser cows were often culled in an ‘unfavourable’ way and generally caused extra workload for the farmer.

A simplified version of the loser cow score was evaluated and is recommended for future research and use in practice.     

Acute oral toxicity of zinc phosphide: an assessment for wild house mice (Mus musculus)

Irregular plagues of house mice, Mus musculus, incur major economic impacts on agricultural production in Australia. The efficacy of zinc phosphide (ZnP), the only registered broadacre control agent for mice, is reported as increasingly variable. Have mice become less sensitive over time or are they taking a sub-lethal dose and developing aversion? In this laboratory study, the sensitivity of mice (wild caught; outbred laboratory strain) was assessed using oral gavage of a range of ZnP concentrations. The estimated LD₅₀ values (72–79 mg ZnP/kg body weight) were similar for each mouse group but are significantly higher than previously reported. The willingness of mice to consume ZnP-coated grains was determined. ZnP-coated grains (50 g ZnP/kg grain) presented in the absence of alternative food were consumed and 94% of wild mice died. Mice provided with alternative food and ZnP-coated wheat grains (either 25 or 50 g ZnP/kg grain) consumed toxic and non-toxic grains, and mortality was lower (33–55%). If a sublethal amount of ZnP-coated grain was consumed, aversion occurred, mostly when alternative food was present. The sensitivity of wild house mice to ZnP in Australia is significantly lower than previously assumed. Under laboratory conditions, ZnP-coated grains coated with a new higher dose (50 g ZnP/kg grain) were readily consumed. Consumption of toxic grain occurred when alternative food was available but was decreased. Our unambiguous findings for house mice indicate a re-assessment of the ZnP loading for baits used for control of many rodents around the world may be warranted.     

A comparative description of two farmer-managed irrigation systems in Nepal

The organization of two farmer-managed irrigation systems in the western hills of Nepal is described by examining the ways in which the activities of water allocation, water distribution, maintenance, and resource mobilization are performed. Due to the topography and environment, these two organizations are structured primarily to mobilize the large amount of labor required for maintenance of the intake and canal. Both organizations precisely define each member's water allocation. In one system, water is allocated in proportion to the area of an individual's land holding, while in the other water allocation is by purchased shares. These two cases were used to analyze the importance of the principle of water allocation for expansion of area irrigated and equity of access to irrigation. Evidence from the two systems shows that in this hill environment water allocation by purchased shares provides the individual incentive and an organizational mechanism for efficient development of irrigation resources. Expansion of area irrigated and equity of access to irrigation were found to be greater in the system which allocates water by purchased shares than where water was allocated in proportion to area irrigated.     

The impact of increasing farm size and mechanization on rural income and rice production in Zhejiang province,China

Economic growth in China’s agricultural sector lags behind growth in industry and services, creating an ever widening rural–urban income gap. Development of the non-agricultural sectors offers new opportunities for farmers in China’s more advanced provinces such as Zhejiang. Increased income in the urban sector creates markets for new products, and migrating farmers rent their land to those staying. Until now, the prevailing rice-based systems have been managed mainly using manual labour and animal traction, but the larger farms resulting from migration may facilitate, or even require mechanization. In this study, we use a simulation model of the farm household to analyse the effects of increasing farm size and the transition from rice to vegetable production, while also studying the effects of mechanization.     

Inverse Modeling to Quantify Irrigation System Characteristics and Operational Management

Remotely sensed (RS) data is a major source to obtain spatialdata required for hydrological models. The challenge for thefuture is to obtain besides the more direct observable data(landcover, leaf area index, digital elevation model andevapotranspiration), non-visible data such as soilcharacteristics, groundwater depth and irrigation practices.In this study we have explore the option of using inversemodeling to obtain these non-RS-visible data. For a commandarea in Haryana, India, we applied for the 2000–2001 rabiseason a RS-GIS-combined inverse modeling approach to derivenon-RS-visible data required in the regional application ofhydrological models. A Genetic Algorithm loaded stochasticphysically based soil-water-atmosphere-plant model (SWAP) wasdeveloped for the inverse problem and used in the study. Theresults showed good agreement with the inventoried data suchas soil hydraulic properties, sowing dates, groundwaterdepths, irrigation practices and water quality. The deriveddata could be used to predict the state of the system at anytime in the cropping season, which can be used to evaluateoperational management strategies.