Modeling leaf area index using time-series remote sensing and topographic data in pure Anatolian black pine stands

We aimed to map and analyze LAI by using Landsat 8 and Sentinel-2 time series and the corresponding ground measurements collected in pure Anatolian black pine [Pinus nigra J.F. Arnold ssp. pallasiana (Lamb.) Holmboe] stands within seven-month (from June to December) period. A total of 30 sample plots were selected and seven-month changes of LAI values were determined through hemispherical photography for each sample plot. Remote sensing (reflectance values and vegetation indices obtained from Landsat-8 and Sentinel-2) and topographic (elevation, aspect, and slope) data were used to model the LAI for each month using multiple linear regression (MLR) method. Additionally, the data for all months were combined and modeled. In this case, autoregressive modeling techniques were used to solve the temporal autocorrelation problem. Our study indicated that the models developed from Sentinel-2 give more successful results than Landsat 8 on monthly LAI models. The most successful models were obtained in June by using the reflectance values (R adj 2  = 0.39, RMSE = 0.3138 m2 m-2), reflectance values-topographic data (R adj 2  = 0.59, RMSE = 0.3174 m2 m-2), vegetation indices-topographic data (R adj 2  = 0.82, RMSE = 0.2126 m2 m-2), and reflectance values-vegetation indices-topographic data (R adj 2  = 0.93, RMSE = 0.1060 m2 m-2). Among the autoregressive modeling techniques, the highest success was obtained with the Landsat 8 OLI using the moving average (2) procedure (R2 = 0.56). This study is significant that it is the first to analyze the monthly effect on LAI modeling and mapping in pure Anatolian black pine stands using both reflectance values, vegetation indices, and topographic data.

Determination of risk factors in cattle and small ruminant livestock enterprises from the perspective of animal life insurance: a case study in Turkey

ABSTRACT The objective of this study was to determine the risk factors in the production processes of cattle and small ruminant breeding enterprises, along with developing a scale that could be used during the insured breeding process in different regions of Turkey. In this study, we obtained information from 252 enterprises from different provinces (Afyonkarahisar, Aksaray, Ankara, Burdur, Karaman, and Konya) of Turkey. Reliability and validity analyses were conducted using the “Risk Assessment Form in Cattle and Small Ruminant Animal Production”. The Cronbach alpha (α) coefficient was used to analyze reliability, while the exploratory factor analysis was applied to analyze the validity. About 68.7% (173) of the enterprises included cattle breeding, while the remaining 31.3% (79) involved small ruminant breeding. To determine the risk factors, twenty-four questions were directed toward the livestock enterprises, and the following six factors were determined: Economic-Political Risks, Yield/Product Losses, Enterprise Technical Risks, Credit/Financing, Workforce, Enterprise Follow-up, and Registration. In the politico-economic risk scoring, the score of enterprises already having Animal life insurance (ALI) was observed to be higher than those who did not have it, with the difference being statistically significant (p<0.05). We interpreted that producers with higher politico-economic risk factor scores preferred insurance. Although the producers could determine the risk factors well, not all producers were necessarily aware of risk measures. Thus, it was necessary to improve the farmers’ perception of risks and support their efforts to manage and reduce these risks. Also, the importance of insurance practices within and out of the farm is predicted to increase gradually to develop more conscious, sustainable, and profitable breeding in agriculture and animal product markets, which are becoming more liberalized day by day.

The effect of stocking density on growth performance and average cost in partridge rearing (Alectoris graeca)

In this study, stocking density and economic evaluation of partridge rearing was investigated. Experimental design was constructed as 576.9 cm(2)/chick (group I), 384.6 cm(2)/chick (group II), 288.5 cm(2)/chick (group III), and 230.8 cm(2)/chick (group IV). Live weights of the first, second, third, and fourth groups at 12 wk of age were determined as 376.46, 367.95, 371.07, and 358.80 g, respectively. Additive feed consumption and feed conversion ratio of the groups were determined as 1,781.74 g and 4.93, 1,805.13 g and 5.13, 1,830.51 g and 5.15, and 1,720.09 g and 5.02, respectively. Total mortality rates of the groups at the end of the feeding time were determined as 3.5, 3.75, 6.75, and 13.00%, respectively (P < 0.05). As a result, it was concluded that rearing in 288.5 cm(2)/chick was suitable according to live weights of partridges, feed conversion ratio, and mortality rates. Also, it was concluded that decreasing costs and increasing profitability in partridge rearing could be achieved.

Effect of Hen Weight on Egg Production and Some Egg Quality Characteristics in the Partridge (Alectoris graeca)

A study was conducted to determine the effect of live weight of partridges on egg production and egg quality characteristics. A total of 144 Rock Partridges were divided into control, heavy, middle, and light BW groups at 32 wk of age. Live weights averaged 512.78 g for the control group, 576.18 g for the heavy group, 523.49 g for the middle group, and 473.83 g for the light group. Egg production rates of these groups were 41.44, 45.78, 32.38, and 24.67%, respectively, over an 8-wk period (P < 0.05). Live weight significantly affected egg weight, specific gravity, albumen index, shell weight, shell thickness, Haugh unit, and albumen weight (P < 0.05). Live weight did not affect the shape index, membrane weight, or yolk weight. As a result, the live weights of partridges used for breeding should not be under the average live weights of hens of the stock. On the other hand, other important factors that affect the egg quality of partridges should be investigated.