Standardization of CPUE for Chilean Jack Mackerel (Trachurus murphyi) from Chinese Trawl Fleets in the High Seas of the Southeast Pacific Ocean

The generalized linear model （GLM） and generalized additive model （GAM） were applied to the standardization of catch per unit effort （CPUE） for Chilean jack mackerel from Chinese factory trawl fishing fleets in the Southeast Pacific Ocean from 2001 to 2010 by removing the operational, environmental, spatial and temporal impacts. A total of 9 factors were selected to build the GLM and GAM, i.e., Year, Month, Vessel, La Nifia and E1 Nifio events （ELE）, Latitude, Longitude, Sea surface temperature （SST）, SST anomaly （SSTA）, Nino3.4 index and an interaction term between Longitude and Latitude. The first 5 factors were significant components in the GLM, which in combination explained 27.34% of the total variance in nominal CPUE. In the stepwise GAM, all factors explained 30.78% of the total variance, with Month, Year and Vessel as the main factors influencing CPUE. The higher CPUE occurred during the period April to July at a SST range of 12-15℃ and a SSTA range of 0.2-1.0℃. The CPUE was significantly higher in normal years compared with that in La Nifia and E1 Nifio years. The abundance of Chilean jack mackerel declined during 2001 and 2010, with an increase in 2007. This work provided the relative abundance index of Chilean jack mackerel for stock as- sessment by standardizing catch and effort data of Chinese trawl fisheries and examined the influence of temporal, spatial, environ- mental and fisheries operational factors on Chilean jack mackerel CPUE.

The Effect of Pulverization Equipment Types and Tractor Velocities on Some Technical Indicators for Machinery Unit

This experiment was conducted in silty clay loam soil and cultivated with previous season wheat. Tillage for experiment field was applied using moldboard plow with 0.22-0.24 m depth, the rate of tractor velocity was 2.45 km hf^-1, as a tillage velocity. Two rates of tractor velocities （first factor） were applied： 3.24 km hr^-1, for the first velocity, and 4.71 km hr^-1 for the second, Three types of tillers （second factor） were used： disk harrow, rotavator tiller, and spring spike tooth harrow. The first velocity rate was： 2.51 km hr-l（with disk harrow as a machinery unit）, 2.92 km hr^-1 （with rotivator）, and 3.06 km hrl（with spring spike tooth harrow）, while the second velocity rate was： 3.19 km hr-1 （with disk harrow as a machinery unit）, 4.05 km hrl（with rotivator）, and 4.26 km hrl（with spring spike tooth harrow）. Split plot design in RCBD with three replicates was used at the constant of soil moisture 11%-13%. Results were analyzed statistically and means were tested with LSD. The results showed the significant differences between both two experiment factors and their interaction for all study parameters which included： slippage percentage, practical productivity, numbers of masses 〉 5 cm m^-2, and the implement width. At the constant of pulverization equipment types, the higher percentage of slippage was 16.45%, the higher rate of practical productivity was 0.677 h hr1, and the higher rate of implement width was 2.05 m, while the rate of masses 〉 5 cm m-2 decreased to 13.8 mass m2. At the constant of velocity, disk harrow achieved higher slippage percentage 17.69%, spring spike tooth harrow tiller achieved higher practical productivity 0.858 h hr^-1 and higher rate of implement width 2.73 m, and the rotivator achieved the lower rate of masses 〉 5 cm m2 and 4.1 mass m2. The comparison among the three pulverization equipment typess was the purpose of this study to give the best studied indexes under two different velocities.

Prediction of Repair and Maintenance Costs of Two-wheel Drive Tractors in Iran

Predicting of repair and maintenance （R＆M） costs of tractors in any mechanized farm is necessary for owners and managers to obtain information on overall costs and to control financial balance and production economy. In this context a study was conducted to predict accumulated R＆M costs （Y） of two-wheel drive （2WD） tractors based on accumulated usage hours （X） in Misagh-e-Sabz Agribusiness Company in Iran. Recorded data of the company were used to determine regression models for predicting accumulated R＆M costs （as percentage of initial purchase price） based on accumulated usage hours. The statistical results of the study indicated that in order to predict accumulated R＆M costs of 2WD tractors with accumulated usage hours of 2260 h or less the power regression model Y=0.013 （X/100）1.677 with R2=0.976, and to predict accumulated R＆M costs of 2WD tractors with accumulated usage hours of 2260 h or more the polynomial regression model Y=0.004 （X/100）2-0.181 （X/1 00）＋4.373 with R2=0.998 can be strongly suggested.