Injection of the insertion of the deep digital flexor tendon in horses using radiographic guidance

Insertional tendinopathies of the DDFT have been reported both as the sole lesion and as part of a multifocal lesion (Dyson et al. 2003). Computed tomography (CT) and magnetic resonance imaging allow specific diagnosis of deep digital flexor tendon lesions within the hoof capsule; however, direct intralesional treatment of such lesions is difficult because of the hoof's rigid structure. A technique designed to mimic intralesional injection of insertional tendinopathies of the DDFT in the standing horse using radiographic guidance was assessed. Radiographic and contrast CT imaging and sectioning of the limbs confirmed accurate injection in all cases although inadvertant administration of injectate into adjacent structures was also evident.     

Transmissible gastroenteritis in neonatal dogs: experimental intestinal infection with transmissible gastroenteritis virus.

Fourteen neonatal dogs (4 through 11 days of age) were exposed orally to the Purdue strain of transmissible gastroenteritis (TGE) virus, and six dogs of similar age were noninoculated controls. Clinical signs of enteric disease did not develop. Both exposed and control dogs had normal fecal passages and appetite throughout the experiment. Jejunal epithelium from dogs euthanatized at 12, 24, 48, and 96 hours and at 10 days after exposure did not exhibit morphologic alterations detectable by light microscopy. Electron microscopic examination indicated that jejunal epithelial cells contained TGE viral particles as early as 12 hours after dogs were exposed. There were no apparent morphologic alterations or signs of desquamation of virus-infected cells, however. Results of pig transmission studies indicated that viable TGE virus was in jejunal tissue of the dogs as early as 12 hours and as late as 10 days after exposure to the virus.     

The Post‐Cervical Insemination does not Impair the Reproductive Performance of Primiparous Sows

The study evaluated the reproductive performance of primiparous sows submitted to post‐cervical insemination (PCAI) compared with cervical artificial insemination (CAI). Difficulty with catheter introduction, the occurrence of bleeding or semen backflow during insemination, and volume and sperm cell backflow up to 60 min after insemination were also evaluated. Sows were homogenously distributed, according to body weight loss in lactation, lactation length, weaned piglets, weaning‐to‐oestrus interval and total born in previous farrowing, in two treatments: PCAI (n = 165) with 1.5 × 10⁹ sperm cells in 45 ml (2.4 ± 0.04 doses per sow) and CAI (n = 165) with 3 × 10⁹ sperm cells in 90 ml (2.5 ± 0.04 doses per sow). During PCAI, sows were inseminated in the absence of boars. Transabdominal real‐time ultrasonography was performed at oestrus onset, immediately before the first insemination and at 24 h after last insemination. There was no difference (P > 0.05) between treatments in farrowing rate (91.5% × 89.1%) and litter size (12.5 × 11.9 piglets born, respectively for PCAI and CAI sows). Successful passage of the intrauterine catheter in all the inseminations was possible in 86.8% (165/190) of sows initially allocated to PCAI treatment. Difficulty of introducing the catheter in at least one insemination did not affect the reproductive performance of PCAI sows (P > 0.05). Bleeding during insemination did not affect (P > 0.05) the farrowing rate in both treatments, but litter size was reduced in CAI and PCAI sows (P ≤ 0.06). Percentage of spermatozoa present in backflow within 1 h after insemination was greater in CAI than PCAI sows (P < 0.01). More than 85% of primiparous sows can be successfully post‐cervical inseminated with doses containing 1.5 × 10⁹ sperm cells in the absence of the boar during insemination without impairing the reproductive performance.     

Selecting cotton yield response function to estimate profit-maximizing potassium fertilization rates for cotton production in Tennessee

Recent research has shown that stochastic yield response functions fit data better than deterministic yield response functions; however, little research exists comparing profit-maximizing fertilizer rates for upland cotton (Gossypium hirsutum L.) using stochastic and deterministic yield response functions. The objective of this research was to determine the most appropriate yield response functional form from which to determine the profit-maximizing potassium (K) rate for cotton in Tennessee. Data were used from a nine-year K fertilizer experiment in Jackson, Tennessee. Quadratic, quadratic-plus-plateau, linear response plateau, and linear response stochastic plateau response functions were estimated to determine the yield response function that best fit the data. The linear response stochastic plateau function was the most suitable yield response function for the data. The profit-maximizing K rate ranged from 65.2 to 74.3 kg K ha^?1. Misspecification of the yield response function recommended over-application of K fertilizer and decreased the producer's short-term profits.     

Potassium carryover dynamics and optimal application policies in cotton production

Information about soil nutrient carryover dynamics can assist cotton producers with the optimal management of potassium (K) fertilizer. Optimal K management promotes cotton plant health, may decrease input costs, and increases cotton lint yields. A dynamic programming model was developed to determine optimal K application rates and economic returns under different soil information scenarios based on cotton yield response to K fertilizer and fertilizer carryover estimates from a multi-year field trial. A Monte Carlo analysis was conducted to simulate the impact of stochastic input and lint prices and cotton yield on K management over a five-period planning horizon. Results suggest that soil test data could provide important information about K carryover potential, which may lead to more efficient fertilizer use and higher profit margins for cotton producers.     

Advances in modeling machine-soil-plant interactions

Modern agriculture involves mechanized operations which affect crop growth and yields through changes in the soil environment. Field research to study the phenomena involved in the soil-machine-crop system is usually site-specific with respect to edaphic, climatic and management factors. Field experiments are often expensive to conduct, and generalization to other sites or practices is usually tenuous at best. Computer-based techniques to simulate machine-soil-plant (or crop) systems can test many combinations of site characteristics and management practices, and screen the most promising combinations. Once these promising combinations are validated, the simulation techniques, together with stochastically-supported data bases can be used to predict tillage management systems suitable for specific sites and crops.Current efforts to model plant response to soil conditions created by tillage and machines have serious shortcomings, because the link between tool action, subsequent soil structure, and the parameters that describe fluxes of water, heat and gas need further development for deterministic modeling. Machine-soil models focus on efficiency of the tillage operation, while soil-plant models focus on soil structure and related parameters influencing plant growth. While current models for simulating the machine-soil-crop system have limitations, an approach to bridge between the two model applications offers great promise and should be a high research priority. When used with improved measurements of tool action and of soil structural properties before and after tillage and traffic, including position or placement of the crop residues, current models can be doubly effective for improving tillage management.