ABSTRACT
Farmers are continually looking for new, reliable, objective, and non-invasive methods for evaluating the conditions of ewes. Live weight (LW) and body condition score (BCS) are used by farmers as a basis to determine the condition of the animal. Body composition is an important aspect of monitoring animal condition. The body composition is the amount of fat, muscle, and bone; knowing the amount of each is important because the information can be used for better strategic management interventions. Experiments were conducted to establish the relationship between body composition and body parameters at key life stages (weaning and pre-mating), using measurements automatically determined by an image processing application for 88 Coopworth ewes. Computerized tomography technology was used to determine the body composition. Multivariate linear regression (MLR), artificial neural network (ANN), and regression tree (RT) statistical analysis methods were used to develop a relationship between the body parameters and the body composition. A subset of data was used to validate the predicted model. The results showed a correlation between fat, muscle, and bone determined by CT and the fat, muscle, and bone weight estimated by the live weight and body parameters calculated using the image processing application, with r2 values of 0.90 for fat, 0.72 for muscle, and 0.50 for bone using ANN. From these results, farmers can utilize these measurements to enhance nutritional and management practices.
ABSTRACT
The arsenic concentration is an important issue in compost production. The main inputs of a compost factory, including kerbsides, green wastes, food industry wastes, and river weeds are investigated in this study. Also, this study investigated how treated timbers, ashes, and other contamination can impact arsenic concentration in compost production. The results showed that most treated timbers and all ashes of treated and untreated timbers contained significant amounts of arsenic. These results revealed that the presence of a small amount of treated timber ashes can significantly increase the arsenic concentration in composts. The results of the study show the arsenic concentration in compost increase during cold months, and it dropped during summer, which would be mostly because of high arsenic concentration in ashes of log burners. This study shows ashes of burning timbers can impact arsenic contamination mostly because of using Copper-Chrome-Arsenic wood preservatives (CCA). Also, the lab results show the arsenic level even in ashes of untreated timber is around 96 ppm. The ashes of H3, H4, and H5 treated timbers contain approximately 133,000, 155,000, and 179,000 ppm of arsenic, which one kg of them can increase arsenic concentration around 10 ppm in 13.3, 15.5 and 17.9 tons of dry compost products. The main problem is many people look at ashes and treated timber as organic materials; however, ashes of treated and untreated timbers contained high concentrations of arsenic. Therefore, it was necessary to warn people about the dangers of putting any ashes in organic waste bins.
Subject(s)
Arsenic/analysis , Composting , Arsenates , New Zealand , Wood/chemistryABSTRACT
This review paper concentrates on carbon dioxide emissions, discussing its agricultural sources and the possibilities for minimizing emissions from these sources in wheat production in Canterbury, New Zealand. This study was conducted over 35,300 ha of irrigated and dryland wheat fields in Canterbury. Total CO(2) emissions were 1032 kg CO(2)/ha in wheat production. Around 52% of the total CO(2) emissions were released from fertilizer use and around 20% were released from fuel used in wheat production. Nitrogen fertilizers were responsible for 48% (499 kg CO(2)/ha) of CO(2) emissions. The link between nitrogen consumption, CO(2) emissions and crop production showed that reducing the CO(2) emissions would decrease crop production and net financial benefits to farmers.
