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Agricultural mechanization and custom machine services have developed rapidly in China, which can influence rice production efficiency in the future. We calculate technical efficiency, allocative efficiency, and scale efficiency using data collected in 2015 from a face-to-face interview survey of 450 households that cultivated 3096 plots located in the five major rice-producing provinces of China. We use a one-step stochastic frontier model to calculate technical efficiency and regress the efficiency scores on socio-demographic and physical land characteristics to find the influencing variables. Variables influencing technical efficiency are compared at three different phases of rice cultivation. We also calculate technical efficiency by using the Heckman Selection Model, which addresses technological heterogeneity and self-selection bias. Results indicate that: (1) the average value of technical efficiency using a one-step stochastic frontier model was found to be 0.74. When self-selection bias is accounted for using the Heckman Selection Model, the average value of the technical efficiency increases to 0.80; (2) mechanization at the chemical application phase has a positive effect on technical efficiency, but mechanization does not affect efficiency at the plowing and harvesting phases; (3) machines are overused relative to both land and labor, and high machine input use on the small size of landholding has resulted in allocative inefficiency; (4) rice farmers are overwhelmingly operating at a sub-optimal scale. Future policies should focus on encouraging farmland transfer in rural areas to achieve scale efficiency and allocative efficiency while promoting mechanization at the chemical application phase of rice cultivation to improve technical efficiency. 相似文献
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Jeewan THAPA Susan K. MIKOTA Kamal Prasad GAIRHE Sarad PAUDEL Dinesh Kumar SINGH Ishwari Prasad DHAKAL Chie NAKAJIMA Yasuhiko SUZUKI 《The Journal of veterinary medical science / the Japanese Society of Veterinary Science》2021,83(8):1278
We conducted a tuberculosis (TB) serosurveillance program of captive elephants in Nepal and compared hematology and biochemistry parameters between seropositive and seronegative elephants. A total of 153 elephants (male=20, female=133) from four national parks were tested for TB using the ElephantTB STAT-PAK® Assay (ChemBio Diagnostic Systems, Inc., Medford, NY, USA). The mean reported age for 138 elephants was 38.5 years (range 2–71 years). Seroprevalence for TB was 21.56% (33/153). The majority of seropositive elephants were female (n=30) and from Chitwan National Park (n=29). The occurrence of TB seropositive cases in other more remote national parks suggests TB may be widespread among the captive elephant population of Nepal. Hematology and biochemistry analyses were performed on 13 and 22 seropositive elephants, respectively and, nine elephants from a seronegative TB herd for comparison. Hematology parameters (hemoglobin, packed cell volume, platelet, white blood cells, and erythrocyte sedimentation rate) were comparable between the two groups. Total protein, globulin, and lactate dehydrogenase were significantly higher in seronegative elephants, and bilirubin was significantly higher in seropositive elephants whereas blood urea nitrogen, creatinine, glutamic oxaloacetic transaminase/aspartate aminotransferase (GOT/AST), glutamic pyruvic transaminase/alanine aminotransferase (GPT/ALT), gamma glutamyl transferase (GT), and albumin were not significantly different. The range of biochemical parameters that were significantly different between seropositive and seronegative elephants had narrow ranges. Thus, the potential of these parameters as a direct biomarker for TB diagnosis is limited based on the findings in this study. We recommend including blood parameters in future TB surveillance studies. 相似文献
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