The growing popularity of Unmanned Aerial Vehicles (UAVs) in recent years, along with decreased cost and greater accessibility of both UAVs and thermal imaging sensors, has led to the widespread use of this technology, especially for precision agriculture and plant phenotyping. There are several thermal camera systems in the market that are available at a low cost. However, their efficacy and accuracy in various applications has not been tested. In this study, three commercially available UAV thermal cameras, including ICI 8640 P-series (Infrared Cameras Inc., USA), FLIR Vue Pro R 640 (FLIR Systems, USA), and thermoMap (senseFly, Switzerland) have been tested and evaluated for their potential for forest monitoring, vegetation stress detection, and plant phenotyping. Mounted on multi-rotor or fixed wing systems, these cameras were simultaneously flown over different experimental sites located in St. Louis, Missouri (forest environment), Columbia, Missouri (plant stress detection and phenotyping), and Maricopa, Arizona (high throughput phenotyping). Thermal imagery was calibrated using procedures that utilize a blackbody, handheld thermal spot imager, ground thermal targets, emissivityand atmospheric correction. A suite of statistical analyses, including analysis of variance (ANOVA), correlation analysis between camera temperature and plant biophysical and biochemical traits, and heritability were utilized in order to examine the sensitivity and utility of the cameras against selected plant phenotypic traits and in the detection of plant water stress. In addition, in reference to quantitative assessment of image quality from different thermal cameras, a non-reference image quality evaluator, which primarily measures image focus that is based on the spatial relationship of pixels in different scales, was developed. Our results show that (1) UAV-based thermal imaging is a viable tool in precision agriculture and (2) the three examined cameras are comparable in terms of their efficacy for plant phenotyping. Overall, accuracy, when compared against field measured ground temperature and estimating power of plant biophysical and biochemical traits, the ICI 8640 P-series performed better than the other two cameras, followed by FLIR Vue Pro R 640 and thermoMap cameras. Our results demonstrated that all three UAV thermal cameras provide useful temperature data for precision agriculture and plant phenotying, with ICI 8640 P-series presenting the best results among the three systems. Cost wise, FLIR Vue Pro R 640 is more affordable than the other two cameras, providing a less expensive option for a wide range of applications.

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Ginger is the potential high value sub-sector in Nepal for small scale farmers' livelihoods. In this context, this research was conducted in 2016 to analyze value chain of ginger sub-sector in Salyan district of Nepal. Dadagaun and Tharmare VDCs of Salyan were purposively selected for the study. Primary data were collected using semi-structured questionnaire for household survey as well as focus group discussion (FGD), key informant interview (KII) and rapid market appraisal (RMA) survey were used. Household level cross-sectional data from 140 households (70 from Dadagaun and 70 from Tharmare VDC) were sampled using simple random sampling technique. Descriptive statistics, and value chain analysis were used to analyse data. Average land under ginger cultivation was 1.62 ropani which was higher in Dadagaun (2.17 ropani) than Tharmare (1.07 ropani) and found statistically significance different at 1 percent level. The average marginal cost of fresh ginger was NRs. 12.15/kg. Local traders were the major market actor influencing the price of ginger and bargaining power as the major factor whereas farmers were seemed weaker in the value chain due to low bargaining power with lack of market information. Huge marketing margin (NRs. 94/kg) and low producers share (14.55%) showed that there was no strong linkage between the producers and traders. This study revealed that ginger value chain analysis in the study area found very unstructured and poor strengthening of business enabling environment, unorganized functional market chain and poor inputs and service provision.

Objective: To assess the corporate social responsibility practices in Nepalese commercial banking sector. Methods and Materials: Primary and secondary sources of data were used in the study. The primary data were collected through direct questionnaire method from 60 employees of sampled commercial banks. The secondary source was through journals, textbooks and annual reports of Nepal Rastra Bank. SPSS and Microsoft excel were used to analyze the collected data. The value of Cronbach’s Alpha (α) of overall questionnaire is 0.92, which suggests the reliability of primary data. Descriptive and explorative research designs were used to analyze the primary and secondary data. Results and Conclusion: Responses from all the respondents of commercial banks regarding CSR and Non-Financial Performance clearly imply that CSR has an influence on the Non-Financial Performance. In terms of ‘R2’, CSR impacts both Brand Image and Brand Awareness (i.e. 0.987). This clearly indicates that more than 98.7% variance of both non-financial performances has been explained by CSR. In terms of ‘R2’, CSR impacts less in financial performance (i.e. 0.149). This clearly indicates that only than 14.9% variance of financial performance has been explained by CSR.