Mitigation of N2O emissions from grassland by nitrification inhibitor and Actilith F2 applied with fertilizer and cattle slurry

Abstract. Nitrous oxide (N₂O) is involved in both ozone destruction and global warming. In agricultural soils it is produced by nitrification and denitrification mainly after fertilization. Nitrification inhibitors have been proposed as one of the management tools for the reduction of the potential hazards of fertilizer-derived N₂O. Addition of nitrification inhibitors to fertilizers maintains soil N in ammonium form, thereby gaseous N losses by nitrification and denitrification are less likely to occur and there is increased N utilization by the sward. We present a study aimed to evaluate the effectiveness of the nitrification inhibitor dicyandiamide (DCD) and of the slurry additive Actilith F2 on N₂O emissions following application of calcium ammonium nitrate or cattle slurry to a mixed clover/ryegrass sward in the Basque Country. The results indicate that large differences in N₂O emission occur depending on fertilizer type and the presence or absence of a nitrification inhibitor. There is considerable scope for immediate reduction of emissions by applying DCD with calcium ammonium nitrate or cattle slurry. DCD, applied at 25 kg ha^–1, reduced the amount of N lost as N₂O by 60% and 42% when applied with cattle slurry and calcium ammonium nitrate, respectively. Actilith F2 did not reduce N₂O emissions and it produced a long lasting mineralization of previously immobilized added N.     

Insulin and glucose regulation.

Abnormally high or low blood glucose and insulin concentrations after standardized glucose tolerance tests can reflect disorders such as pituitary dysfunction, polysaccharide storage myopathies, and other clinical disorders. Glucose and insulin responses, however, are modified by the diet to which the animal has adapted, time since it was last fed, and what it was fed. Body fat (obesity), fitness level, physiologic status, and stress also alter glucose and insulin metabolism. Therefore, it is important to consider these factors when evaluating glucose and insulin tests, especially if only one sample it taken. This article describes the factors affecting glucose and insulin metabolism in horses and how they might influence the interpretation of standardized tests of glucose tolerance.     

MAGNETIC RESONANCE IMAGING FEATURES OF EQUINE NIGROPALLIDAL ENCEPHALOMALACIA

Magnetic resonance imaging (MR) was used to make a diagnosis of equine nigropallidal encephalomalacia in a horse. Equine nigropallidal encephalomalacia is a neurodegenerative disease that has many characteristics with Parkinson-like diseases in humans. Historically, horses were euthanized based on clinical signs and exposure to the toxic weed, yellow star thistle (Centaurea solstitialis). Previously, the disease has only been confirmed on necropsy. MR imaging can provide accurate and sensitive visualization of typical lesions seen in the brain of horses affected with equine nigropallidal encephalomalacia. Lesions were seen on T1-weighted, T2-weighted and proton density images. There was no contrast enhancement following Gd-DTPA administration. Lesions seen on MR were confirmed at necropsy. Using MR to confirm a diagnosis of equine nigropallidal encephalomalacia will prevent unnecessary suffering of horses and expense to owners that would otherwise incur, while further diagnostics are performed.     

Physical characteristics and chemical composition of Greater Rhea (Rhea americana) eggs from wild and captive populations.

1. Eggs from wild and captive populations of Greater Rhea (Rhea americana) were studied to determine their physical and chemical characteristics. 2. Significant differences were found among populations in almost all chemical parameters studied, whereas within physical parameters only shell weight (as a proportion of the entire egg) and density showed differences. 3. Eggs from wild populations had the highest protein and linolenic acid and the lowest total lipid contents, while cholesterol levels of these eggs and of those from the largest captive area were the lowest.     

Monthly model for genetic evaluation of laying hens 1. Fixed regression.

1. This paper addresses the possibility of using a monthly model for the genetic evaluation of laying hens, based on the definition of a test day model with fixed regression as used in dairy cattle, in which monthly records were treated as repeated measurements of the same trait. 2. Production records of 6450 hens, daughters of 180 sires and 1335 dams were analysed using an animal model with restricted maximum likelihood (REML). The traits considered were individual monthly egg production and cumulative egg production in 11 months. Four different models were fitted to various combinations of monthly and cumulative records. The covariates were derived from the regression of Ali and Schaeffer (1987). 3. Spearman rank correlations were computed to compare breeding values from different models. Two types of correlations were computed: between individual breeding values and between sire breeding values based on subsets of full-sib records. 4. The results indicated that a monthly model with nested covariates produced higher heritability and permanent environmental variance than the models with non-nested or without covariates. The estimates of heritability obtained from monthly model were lower than the estimates from the cumulative model. The monthly model resulted in higher correlations of sire breeding values between two subsets of full-sib records than those from cumulative models. 5. In conclusion, the monthly model with nested covariates appears to be better than the model with non-nested covariates or without covariate. Although the heritability estimates obtained from the monthly model were lower, the monthly model with nested covariates could be better than the cumulative model for genetic evaluation of laying hens in the 1st cycle of laying period when using either full or part records. The use of information from odd months of production could be of interest for the evaluation of full records.     

Evaluation of Five Most Commonly Grown Cotton Cultivars (Gossypium hirsutum L.) Under Mediterranean Conditions: Productivity and Fibre Quality

Studies were conducted in four regions of central Greece (Larisa, Karditsa, Livadia, Thiva), to evaluate the productivity and fibre properties (fibre strength and fibre length) of the five most commonly grown cotton cultivars in these regions. The experiments lasted for 6 years (1995–2000). All the characteristics tested were strongly influenced by the factors ‘year’, ‘cultivar’ and ‘region’. Significant cultivar × region, year × cultivar, region × year and cultivar × region × year interactions occurred for all the characteristics studied. The cultivar Alegria had the highest seed‐cotton and lint yield, while Aria had the lowest ones. Both cultivars gave the highest mean lint percentage but the lowest mean boll weight (MBW). Alegria had the lowest fibre strength, while Aria had the highest. The Acala‐type cultivars, Acala SJ2 and Zeta 2, had intermediate seed‐cotton and lint yield, while Vered 171 had high seed‐cotton and satisfactory lint yield. The three cultivars mentioned above had the highest MBW and very good fibre strength. Positive correlation was observed between fibre strength and length. In spite of the fact that mean fibre length was statistically the same in all cultivars, it was influenced by the factor ‘year’, as a result of different weather conditions. The year 1996 was the most unfavourable one for seed‐cotton yield and MBW, because it was characterized by lower than average air temperatures and rather dry conditions for all study sites. The factor ‘region’, a combination of different climatic conditions and cultural practices, influenced significantly all the parameters studied.