Non-sampled Areas Research Articles

A Scale to Measure the Perception of Graduates towards Student READY Programme

A scale was developed to measure the perception of graduates towards Student READY Programme (SRP). The Likert’s summated rating scale was followed in the construction of scale. Based on the review of literature and discussion with the expert’s, 49 statements were enlisted. The relevancy rating were sent to 160 scientists and extension specialists working in research institutes of Indian Council of Agricultural Research (ICAR) and State Agricultural University (SAU) for critical evaluation of statements on a 5 point continuum. Out of 160 judges 66 responded within a period of one month. Based on their judgment 40 statements were isolated in the first stage of screening by finding the relevancy weightage scores. Statements having relevancy weightage of more than 0.70, relevancy percentage of more than 70 per cent and mean relevancy score of more than 3.70 were considered for final selection. By this process, 32 statements were isolated in the first stage of screening, which were suitably modified and rewritten wherever applicable. Eight statements were added as per the comments of experts. Thus finally 40 statements were selected for item analysis. In item analysis the selected statements were administered to 80 agriculture graduates of non-sample area of Tamil Nadu and Karnataka. Finally a total of 28 statements were selected for the study based on ‘t’ values (> 1.75) resulted from the item analysis and were included in the final scale. The ‘r’ value of the scale was found to be 0.922, which was highly significant at one per cent level indicating the high reliability of the scale. Hence, the scale developed was found to be reliable and valid. The instrument developed to measure the perception of graduates towards Student READY Programme (SRP) can be used by the researchers.

Prediction in non-sampled areas under spatial small area models

Prediction in non-sampled areas under spatial small area models

Construction of a Scale Towards E-Crop Booking Services of Rythu Bharosa Kendras (RBKs)

In this modern era, farmers encounter difficulties in receiving timely advices and services from extension agents. Due to technological advancements in the recent past quality of services, speed in deliverables and precision actions are possible by creating proper interface between farmers, scientists, extension officers, service providers and by bringing innovation/sustainable interventions in agriculture and allied sectors. With this context as a new extension reform, state government of Andhra Pradesh, India has launched Rythu Bharosa Kendras for bringing the extension system nearer to the farming community and more transparency to ensure quality of services. Hence, this study represents the construction of a perception scale to understand the perception of farmers towards Rythu Bharosa Kendras. Keeping this in view, an attempt has been made to develop a scale for measuring the perception of farmers towards e-crop booking services of Rythu Bharosa Kendras. Likert’s method of summated rating technique was adopted to construct the scale. Based on the available literature and expert’s opinion, 50 statements were developed. After editing as per informal criteria, 40 statements were subjected to item analysis among the farmers of non-sample area. Out of which, 32 statements were retained in the developed perception scale based on the highest ‘t’ value. The ‘r’ (correlation coefficient) value was found to be 0.852 which represents significant at 1 per cent level and the reliability and validity of the constructed scale were found appropriate to measure the perception of farmers towards e-crop booking services of Rythu Bharosa Kendras.

Sample compensation method for injection electroluminescent display panels

Aiming at the problem of luminance uniformity for injection electroluminescent display panels, we present a new sample compensation method based on column-control according to successive scans theory. On the basis of our ideas, a small part of pixels of each column are selected as samples, and the column gating time calculated by sample average luminance value of corresponding column is written in hardware program. We adopt the 64 × 32 LEDs display panel as an example to expound the compensation method and obtain good result that the reduction in amplitude of luminance non-uniformity is 65.42% for the sample area, 58.67% for the non-sample area and 60.21% for the entire display panel.

Development of Scale to Measure Perceived Impact of Grape Beneficiary Farmers towards Restructured Weather Based Crop Insurance Scheme

. For the progress of our nation, our farmers need to be progressed. Driven by the motivation Restructured Weather Based Crop Insurance scheme (RWBCIS) has been introduced in India. As agriculture is effected by disasters and consequences are beyond our control, it is very essential to take precautionary measures to mitigate from unforeseen events. Crop insurance assists in stabilization of crop production and reduces the negative impact on lives of the farmers. Grapes are susceptible to changes in weather and cause losses to the farmers. An attempt is made to develop a scale to measure perceived impact of Grape beneficiary farmers towards Restructured Weather Based Crop Insurance Scheme. With the help of Likert’s Summated Rating technique perceived impact scale was constructed. The process started with selecting 39 statements after calculating Relevancy percentage, Relevancy weightage and Mean Relevancy score. Later for item analysis step, 30 farmers from non-sample area were selected and the test was administered having 39 statements on five point continum. After computing t value, 29 statements were retained. The Reliability and validity of the scale was computed for precision and accuracy. The scale developed was found reliable and valid. Hence, the scale was finalized and administered to 75 Grape beneficiary farmers of RWBCIS farmers in the sample area ie. Nashik district of Maharashtra state. The overall perceived impact of beneficiary farmers towards Restructured Weather Based Crop Insurance Scheme was low. Hence it can be inferred that the farmers perceived that there is low impact of the scheme on their lives. Therefore co-ordination between the concerned authorities and regular auditing of the insurance companies is required for the scheme to run efficiently.

Development and Validation of a Farmer’s Focused Digital Literacy Scale

The research aimed to develop a tool for assessing the digital literacy of farmers towards ICT-led agriculture in India. The study identified three dimensions namely digital knowledge, attitude, and digital competency, for a farmer-focused digital literacy scale. Digital competency consisted of seven sub-dimensions viz device setup, digital communication and collaboration, digital content creation and sharing, digital safety, problem-solving, digital marketing, and digital payment. The digital literacy scale was developed with Likert scale construction methodology. An overall mean relevancy score of 5.693 was obtained. A pilot study was conducted with 60 farmers in a non-sampled area. The t value was calculated, and the cutoff value for item selection was set at > 1.75. For assessing internal consistency reliability using the Spearman-Brown formula, a reliability coefficient of 0.850 was found. The calculation of Cronbach’s alpha gave a value of 0.743, indicating that the scale shows a high level of consistency in its measurement. The standard farmers-focused digital literacy scale comprised of 30 items, and its content validity was determined with expert opinions.

Scale to Measure the Attitude of Fish Farmers Towards the APART Project in Assam

A scale was constructed and standardized to measure the attitude of fish farmers towards scientific technologies demonstrated by “Assam Agribusiness and Rural Transformation Project (APART)” from May 2021 to September 2022 in APART-fishery operated districts of Assam using the ‘Scale Product Method’. Sixty-five (65) experts responded unbiased to the 50 attitude statements related to recommended technologies of fish farming by the project. On the basis of scale values and Q values, only 28 statements were incorporated in the final attitude scale. When administered in a non-sample area, the reliability coefficient of the whole test was 0.90 using Rulon’s formula. Moreover, when the constructed attitude scale was administered among 180 APART beneficiaries during July, 2022 to September, 2022, majority i.e. 87.22 per cent of the respondents had most favourable attitude towards technologies demonstrated by APART project which is depicts the impact of the development programme. This attitude scale can be applied practically for measuring the attitude of fish farmers under similar programmes which will aid policy-makers in right decision-making.

Small Area Estimation of Poverty and Wealth Using Geospatial Data: What have We Learned So Far?

This article offers a non-technical review of selected applications that combine survey and geospatial data to generate small area estimates of wealth or poverty. Publicly available data from satellites and phones predict poverty and wealth accurately across space, when evaluated against census data, and their use in model-based estimates improves the accuracy and efficiency of direct survey estimates. Models based on interpretable features appear to predict more accurately than estimates derived from convolutional neural networks. Estimates for sampled areas are significantly more accurate than those for non-sampled areas due to informative sampling. In general, estimates benefit from using geospatial data at the most disaggregated level possible. Tree-based machine learning methods appear to generate more accurate estimates than linear mixed models in common settings. Small area estimates using geospatial data can improve the design of social assistance programmes, particularly when the existing targeting system is poorly designed. AMS subject classification: 62P20

Modeling and mapping the spatial variability of soil micronutrients in the Tigris basin

BackgroundCrop production is negatively impacted by excess and lack of soil micronutrients. Due to anthropogenic and natural factors, soil micronutrients vary greatly in space, necessitating time- and money-consuming large-scale sampling. Therefore, modeling their spatial distributions and forecasting in non-sampled areas are essential for high crop production. MethodsIn this study, regional variations in soil micronutrient content of the Upper Tigris Basin were modeled to produce local change maps for the development of site-specific nutrient management systems. The concentrations of extractable zinc (Zn), copper (Cu), manganese (Mn), and iron (Fe) in soil samples taken at 388 different sites between 0 and 20 cm deep were determined. Using variogram and kriging analyses, the spatial distribution of the micro element concentrations was modeled and mapped in a GIS environment. ResultsThe micronutrients demonstrated significant variability with a high coefficient of variation (CV > 35%). It was found that the spatial dependence of the samples ranged from low for Fe and Cu to high for Zn and Mn. The spatial distribution of soil micronutrients was influenced by soil texture in addition to distance. Overall, the results demonstrated that the management of site-specific micronutrients may be aided by the integration of geostatistics and GIS, which is particularly beneficial in terms of effective management of the lands and the optimal use of inputs. ConclusionOverall, the findings showed that the integration of geostatistics and GIS may be helpful in the management of site-specific micronutrients, which is especially advantageous in terms of efficient management of the lands and the best use of inputs.

3D numerical modeling of THI distribution in livestock structures: a cattle barn case study

In dairy cattle farming, heat stress largely impairs production, health, and animal welfare. The goal of this study is to develop a workflow and a numerical analysis procedure to provide a real-time 3D distribution of the THI in a generic cattle barn based on temperature and humidity monitored in sample points, besides characterizing the relationship between indoor THI and outside weather conditions. This research was carried out with reference to the study case of a cattle barn. A model has been developed to define the indoor three-dimensional spatial distribution of the Temperature-Humidity Index of a cattle barn, based on environmental measurements at different heights of the building. As a core of the model, the Discrete Sibson Interpolation method was used to render a point cloud that represents the THI values in the non-sampled areas. The area between 1-2 meters was emphasized as the region of greatest interest to quantify the heat waves perceived by dairy cows. The model represents an effective tool to distinguish different areas of the animal occupied zone characterized by different values of THI.

A Scale to Measure the Attitude of Cotton Growers towards Weather Based Agro-Advisory Services in Telangana and Andhra Pradesh States

In this modern era, climate change is the most severe challenge experienced in the field of agriculture. To become climate smart, farmers should be equipped well with weather forecast information in prior to do farm operations. Hence, this study represents the construction of an attitude scale to understand the attitude of farmers towards weather based agro-advisory services. Keeping this in view, an attempt has been made to develop a scale for measuring the attitude of farmers towards weather based agro-advisory services in cotton cultivation. Likert’s method of summated rating technique was adopted to construct the scale. Based on the available literature and expert’s opinion, 40 statements were developed. After editing as per informal criteria, 33 statements were subjected to item analysis among the farmers of non-sample area. Out of which, 30 statements were retained in the developed attitude scale based on the highest ‘t’ value. The ‘r’ (correlation coefficient) value was found to be 0.852 which represents significant at 1 per cent level and the reliability and validity of the constructed scale were found appropriate to measure the attitude of cotton farmers towards weather based agro-advisory services.

MaxEnt brings comparable results when the input data are being completed; Model parameterization of four species distribution models.

Species distribution models (SDMs) are practical tools to assess the habitat suitability of species with numerous applications in environmental management and conservation planning. The manipulation of the input data to deal with their spatial bias is one of the advantageous methods to enhance the performance of SDMs. However, the development of a model parameterization approach covering different SDMs to achieve well-performing models has rarely been implemented. We integrated input data manipulation and model tuning for four commonly-used SDMs: generalized linear model (GLM), gradient boosted model (GBM), random forest (RF), and maximum entropy (MaxEnt), and compared their predictive performance to model geographically imbalanced-biased data of a rare species complex of mountain vipers. Models were tuned up based on a range of model-specific parameters considering two background selection methods: random and background weighting schemes. The performance of the fine-tuned models was assessed based on recently identified localities of the species. The results indicated that although the fine-tuned version of all models shows great performance in predicting training data (AUC > 0.9 and TSS > 0.5), they produce different results in classifying out-of-bag data. The GBM and RF with higher sensitivity of training data showed more different performances. The GLM, despite having high predictive performance for test data, showed lower specificity. It was only the MaxEnt model that showed high predictive performance and comparable results for identifying test data in both random and background weighting procedures. Our results highlight that while GBM and RF are prone to overfitting training data and GLM over-predict nonsampled areas MaxEnt is capable of producing results that are both predictable (extrapolative) and complex (interpolative). We discuss the assumptions of each model and conclude that MaxEnt could be considered as a practical method to cope with imbalanced-biased data in species distribution modeling approaches.

A scale to measure perception of farmers on pesticides use behaviour

A scale was developed to measure the perception of farmers about pesticides use behaviour by following the Likert’s summated rating scale was. Based on the review of literature and discussion with the experts, 81 statements were prepared on dimensions. Relevancy rating was sent to 250 scientists and extension specialists working in research institutes of Indian Council of Agriculture Research (ICAR), State Agricultural University and development Departments for critical evaluation of statements on five point continuum. Eighty five judges sent in time were analyzed and aggregate of 74 statements were selected by finding the relevancy weightage scores (RWS) equal or more than 0.75 and mean relevancy score of 3.00 were selected for the item analysis. In item analysis the selected statements were administered to 40 farmers in non-sample area in Dharwad district of Karnataka state. Finally a total of 25 statements were selected for the study based on ‘r’ values (> 1.75) they were included in the final scale. The ‘r’ value of the scale was found to be 0.91, which was significant at one per cent level indicating the high reliability. The scale developed was found to be reliable and valid, hence it is recommended to use the scale to study pesticide use behaviour.

A Scale to Measure Attitude of Farmers Towards Vermiculture Technology

An attitude scale was constructed to measure the attitude of farmers towards vermiculture technology. Likert’s summated rating was followed for the development of the attitude scale. A total of 40 statements were screened after obtaining a relevancy score from expert’s judgment and given to vermiculture farmers of the non-sample area of Hamirpur district, Uttar Pradesh. Based upon ‘t’ value obtained for each statement, fi nally, 16 statements were chosen to have 8 positive and 8 negative statements. The reliability and validity of the scale indicate its precision and consistency of the results. The developed Scale is well suitable to measure the attitude of farmers towards vermiculture technology beyond the study area in the future.

Soil pedogeochemical attributes prediction by interpolators in ice-free areas of Antarctica

The main objective of this paper is to predict soil attributes in unsampled areas using geostatistical models, By improving the prediction parameters of selected data, using environmental covariates characteristic of Antarctic ice free areas. In this study, 58 soil samples from a grid were collected at 0-10 cm depth in Keller Peninsula, King George Island, Antarctica. The soil chemical analysis was performed, and the values of potassium, calcium and magnesium were determined for each soil sampled. Simple kriging (SK) and Random Forest interpolator were used in this work to predict the values of the studied soil attributes in non-sampled areas. We used a Terrestrial Laser Scanner (TLS) to generate a cloud of points, to obtain digital elevation models (DEMs) of 1, 5, 10, 20 and 30 meters cell size. The use of covariates did not improve the parameters of soil bases prediction in the studied area. The final maps did not show great differences based on RMSEs, mainly related to the great spatial variability of soil attributes in this region, despite soil thematic maps evidencing visual difference.

Development of Scale to measure the Behavioural Intention of Farmers to Adopt Nutrition Sensitive Agriculture

A scale was developed to measure the "Behavioural intention of farmers to adopt Nutrition Sensitive Agriculture (NSA)". Based on the review of literature and discussion with the expert's, 74 statements were enlisted. The Likert's summated rating technique was followed in the construction of scale. The list of 74 statements was sent to a panel of 120 experts with the request, to critically evaluate each statement for itsrelevancy to measure thebehavioural intention of farmers to adopt Nutrition Sensitive Agriculture. Out of 120 expertsselected for the scale construction, 40 experts responded in time and at the earliest. Based on their judgment an aggregate of 40 statements was selected. Statements having Relevancy Weightage 0.80 and Mean Relevancy Score 2.4 were considered for the item analysis. In item analysis, the selected 40 statements were administered on 40 farmers in the non-sample area. Finally, a total of 24 statements were selected for the study, based on the‘t’ values (> 1.75) resulted from the item analysis and were included in the final scale. The ‘R’ value of the scale was found to be 0.732 and the value of Cronbach’s alpha found to be 0.776 which was significant at 1% level indicating the high reliability. Hence, the scale developed wasfound to reliable and valid. Thus, the instrument developed to measure the behavioural intention of farmers to adopt Nutrition Sensitive Agriculture.

Development of a regional climate change perception index based on traditional knowledge base of small-marginal farmers

Due to global climatic change, the pronounced impact of temperature and precipitation variability on agriculture has lately alarmed the top-up organizations to enable effective adaptation and mitigation strategies for small-marginal farmers. In contrast, despite being the main stakeholders of this sector, these farmers have always been neglected in the decisionmaking process while planning for adaptation strategies to combat climate change impacts in agriculture. Practicing farmers have a wide array of knowledge, both current and traditional, related to climate change impacts. This underutilized form of the knowledge base in the form of observable environmental changes that they deal with while producing food on their farms is a valuable resource for agricultural development. Their involvement in the decision-making process would be crucial to better understand the adaptation strategies at a local scale. With this in mind, we proposed a regional index for measuring the level of perception of farmers on climate change. The proposed index is based on 21 closed-ended statements, which have been exhaustively selected from a set of 62 statements through judges' rating methodology. The final set of statements has been checked for validity and reliability measures. These statements then have been put to pilot testing in a non-sampled area comprising of small farmers (n= 40). Finally, the set of 21 statements was applied in the study area (three selected districts in West Bengal) to estimate the perception score. The results indicate very high reliability among the statements of the proposed climate change perception index of the farmers.

Test to Measure the Attitude of Horse Stakeholders Towards Horse Keeping

A scale was constructed and standardized to measure the attitude of horse keepers towards horse management using Thurstone’s “equal-appearing interval” method from March 2021 to September 2021. Several attitude statements concerning the psychological object i.e., horse management were collected. 36 experts responded unbiasedly to the 22 attitude statements. On the basis of scale values and Q-values, only 8 statements were incorporated in the final attitude scale. When administered in a non-sample area, the reliability coefficient of the whole test was 0.88 in Spearman-Brown formula. The content validity was computed using index of reliability formula and it was 0.93. When the constructed attitude scale was administered among 60 horse stakeholders (horse keepers, veterinarians and NGOs) from October 2021 to April 2022, majority (66%) of the respondents had unfavourable attitude towards horse keeping which is evident from the declining horse population in India. The developed attitude scale can be applied practically for identifying the attitude of horse keepers which will aid policy-makers in right decision-making.

A scale to measure the perception of veterinarians towards antimicrobial use and resistance

Veterinarians are the primary sourceof knowledge for farmers on how to use antibiotics responsibly in farm animals and how to decrease the risk of antibiotic resistance.Antimicrobial use and resistance is a multidimensional construct that lacks a specific measurement scale. This paper looks into the development of a scale to assess veterinarian perception about antimicrobial use and resistance. Following a thorough literature review, focus group interviews were conducted with selected key informant veterinarians to identify statements.An initial list of 80 statements reflecting positive and negative perception towards antimicrobial use and resistance was prepared. After editing, a final list of 70 statements were arrivedat. Descriptives of antimicrobial use and resistance, consensus regarding antimicrobial use and resistance indicators were arrived at through relevancy rating by a panel of 40 judges in the field of veterinary science based on which 35 statements were selected for item analysis. These 35 statements were subjected to item analysis among 60 veterinarians selected from a non-sample area. Out of the 60 veterinarians to whom the items were administered for item analysis, 15 veterinarians each with the lowest and highest scores were used as the two criterion groups to evaluate individual items. Individual items were selected based on‘t’ value whereinitems that had a t-value of more than 1.75 were selected and incorporated into the final schedule. Based on the calculated‘t’ values, 14 items were finally selected and includedin the final scale. Reliabilityof the scale was tested using Cronbach’s alpha coefficient of reliability test for which a Cronbachalpha of 0.852 was obtained indicating the internal consistancy of the scale.

Raiva bovina no Rio Grande do Sul: taxas de positividade, distribuição geográfica e ocorrência sazonal

Rabies is a zoonotic disease characterized by acute viral encephalitis. It is almost 100% fatal for infected animals. While cases of human rabies have still been registered in Brazil, in the state of Rio Grande do Sul rabies is considered a controlled disease in urban areas. However, the transmission of bovine rabies – which has been largely associated with the Desmodus rotundus bat – is endemic. Additionally, there are estimates that only 10% of rabies cases are reported. Therefore, this study aimed to describe the positivity rates, geographical distribution, and seasonal occurrence of bovine rabies in RS, as well as the sampling practices in rabies surveillance. Using samples submitted for laboratory diagnosis from 2016 to 2019, we conducted a retrospective study of the sample results, positivity rates, and seasonal occurrence of rabies in cattle. Throughout these four years, less than a third of state municipalities sent samples for diagnosis, suggesting that the occurrence of rabies might still be underestimated in non-sampled areas. A higher number of rabies cases were reported in 2019, a year in which the most diagnosed samples and the highest positivity percentages were recorded. However, the case numbers registered between 2016 and 2019 were not significantly different. We found that the summer and autumn months presented statistically different positivity rates. Besides this, we did not find any positive D. rotundus samples, despite the positivity rates for bovine rabies. Active surveillance, especially of bat populations and under-sampled regions, must be strengthened to correctly estimate the impact of rabies.