Current Journal of Applied Science and Technology

Agriculture is the primary source of livelihood for rural areas in Bihar. Agriculture being mostly dependent on monsoon is highly affected by scanty rainfall, weather variations, flood, etc. The study was conducted in Bhagalpur district of Bihar to assess role of different technologies in enhancing income and mitigate challenges faced by farmers. Three villages of Sabour block in Bhagalpur district namely Farka, Ghospur and English were selected for study. A total of 150 farmers (50 from each village) were selected randomly and data was collected using semi-structured interview schedule. Production innovations like high yielding varieties, new techniques, and home-made remedies of costly designs were identified, along with a marketing channel to sell vegetables from diara region. Some new crops like strawberry and fruits plantation in large area seemed to have good scope; poultry business also appeared to be promising. Some constraints were also identified which when rectified can give new potentials to agricultural production in this area.

We are entering the era of big data. In this epoch, people are required to develop big data thinking gradually. It is a new kind of thinking that is different from people's previous natural thinking. It has the characteristics of data integration, statistic probability, focus on related relationships and intelligence. From the perspective of Chinese traditional philosophy, big data thinking is highly compatible with many elements of Chinese traditional philosophy, such as benevolence, harmony as well as difference and the unity of theory and practice based on empathy. This article discusses and believes that there is an interrelation between big data thinking and Chinese traditional philosophy. The latter has certain reference and guiding significance for the development of big data thinking in the era of big data.

Postharvest loss of fruit and vegetables especially mango, is a major challenge of agriculture. A research was therefore conducted to evaluate the quality of fresh mango fruits stored in two evaporative coolers, a non-cladded burnt-clay-brick (NBBEC) and an aluminum-cladded burnt-clay-brick evaporative coolers (ABBEC) to reduce postharvest loss. The physicochemical, microbiological and sensory attributes of mango stored in the coolers and in ambient were evaluated. Metabolic rates of mango were highest in ambient storage, intermediate in NBBEC with least values obtained in ABBEC. Beta carotene, ascorbic acid and acidity decreased while total soluble solids, pH and microbial load increased during storage. Mango stored in aluminum-cladded burnt-clay-brick evaporative cooler exhibited lower biochemical and physiological reaction rates hence tissue breakdown, colour changes, pH and titratable acidity were lower in ABBEC than in NBBEC and ambient storage conditions. ABBEC is therefore recommended for stop gap extension of shelf life of mango.

Most of the agricultural activities are limited for the depth of 15 – 20 cm and rest soil remain enact for long periods which inhibits the microbial activities below this depths and create an initial concentration of nutrients exponentially decreasing with depth. An attempt has been made to develop analytical models for time-dependent nitrification/ denitrification and depth-dependent absorption of urea fertilizer in high water table conditions with fertigation. Laplace transformation method was used to solve the unsteady-state advection-dispersion equation. The analytical solutions that can be derived by this method assist understanding of the movement of fertilizer in irrigated fields. The developed models were validated with the experimental results. They were closely predicting the fertilizer movement in one-dimension soil medium. The little deviation of result from observed values may be due to change of dispersion coefficient and velocity with moisture content. Here these parameters were assumed as constant throughout the time under consideration. Models developed for constant degradation rate is predicting very close to observe values which shows that the soil under study has no depth-dependent degradation. The developed models may be helpful for the planning of drain design, nutrient management and assessment of potential hazards to groundwater in agricultural fields by the knowledge of exact transport parameters and boundary conditions universally.

For better performance and durability of tractor and machinery during field operations, it is necessary to select a proper matching machine/implement. The purpose of the study was to analyse the effect on parameters affecting to power requirement of power take-off (P.T.O) for rotary tiller, development of mathematical modelling and validation of the model under field conditions. Three different regression models (multiple linear regression, weighted least squares and stepwise regression) were used to predict the P.T.O power requirement. All three developed models were observed significant at 1% level with R² value of 0.945, 0.984 and 0.940 for three models respectively. Correlation analysis was performed and all the parameters expressed positive correlation in relation to P.T.O power requirement. Speed of operation, moisture content, depth of cut, working width, peripheral velocity, number of blades and weight of rotary tiller were shown linear relation with P.T.O power requirement. L shaped blades consumed more power than the J and C shaped blades. Hard soil consumed more power followed by medium and light soil. The Mean Absolute Percentage Error (MAPE) ranged in reasonable limit for all three models. Based on higher R² value, weighted least square regression model was found to be the best fit model for prediction of P.T.O power requirement of rotary tiller.

The study aim at utilization of bulk availability of low cost ripe pumpkin into processed products possessing health benefits. A fruit bar was developed using pumpkin (Cucurbita moschata) at 40°Brix, 1.5% citric acid and 2% pectin by varying cooking method (with and without cooking of ingredients; with and without cooking of ingredients using concentrated pumpkin pulp (PP)). Pumpkin bar prepared using concentrated pulp and with cooking of ingredients had obtained maximum sensory score, as well as maximum content of β-carotene (9.89 mg/100 g) and ascorbic acid (8.75 mg/100 g). Pumpkin bar was evaluated for quality and stability during storage. The values for chemical and sensory parameters decreased significantly during storage but the bar was of good quality up to six months under ambient conditions. Aluminium Laminated Pouches (ALP) was observed to be better packaging material as compared to Low Density Polyethylene (LDPE) and Polypropylene (PP) boxes. Hence, it was concluded that ripe pumpkin can be utilized for the production of good quality and nutritionally enriched bar at remunerative cost.

Aim/Objective: To evaluate the economic feasibility of brinjal–palak intercropping system.

Study Design: Randomized Block Design.

Place and Duration of Study: Research Farm of the Department of Vegetable Science, CCS Haryana Agricultural University, Hisar during 2016-17.

Methodology: Experiment comprised of 11 treatments with three replications of palak (20 x 5 cm) as intercrop with brinjal (60 x 60 cm) and paired row brinjal (30/60 x 60 cm).

Results and Discussion: Brinjal + palak (single row) gave the highest production efficiency (532.3 kg/days), net returns (Rs. 222652) and benefit to cost ratio (3.76) due to low cost of production, closely followed by paired row brinjal + palak (two rows). Paired row brinjal + palak (two rows) intercropping system also exhibited maximum gross returns (Rs. 304598), monetary advantage index (MAI) (Rs.139055), replacement value of intercropping (RVI) (2.47), relative value total (RVT) (3.79) and relative net return (RNR) (2.71). This may be attributed to additional advantage of intercrop yield and higher economic value of intercropping.

Conclusion: From farmer’s point of view, the treatment paired row brinjal + palak (two rows) was considered to be the most remunerative one among all the respective treatments due to its higher MAI, RVI and RNR.

Elaeis guineensis is one of the potential carbon sequestering perennial crop by biological means. It has helped in the mitigating global warming and climatic fluctuations. The main objective of our study is to evacuate the hidden potential treasure of oil palm in carbon sequestration and vegetable oil yield. In this study we selected Tenera hybrids oil palm plantations in Coimbatore district of Tamil Nadu with standard management practices. It had been selected in the year 2019 and assessed for carbon sequestration potential and Fresh fruit bunch yield by non-destructive carbon stock assessment methods and standard estate practices for harvest. In our study the carbon sequestration is higher in trunks found to be 15.3 t C/ha (tons carbon per hectare) in 5 years and 26.6 t C/ha in 10 years while roots sequestered carbon for about 4.0 t C/ha in 5 years and 6.93 t C/ha in 10 years plantations. The fronds sequesters about 1.39 t C/ha in 5 years and 2.1 t C/ha in 10 years oil palm plantations while the fresh fruit bunch yield in 5 years and 10 years plantations were found to be 7.60 t/ha/year (tons per hectare per year) and 12.31 t/ha/year respectively. The present study evidenced that the biomass production and fresh fruit bunch yield in oil palm proportionally increases with the age group.

This study holds that the higher biomass production which increases carbon sequestration and yields in oil palm helps in altering of the microclimate and to increase the economic benefits of farming communities.

Soybean (Glycine max L.) is a significant legume of food and plays a vital role in human livelihood. It is rich in proteins (40%), which contain major essential amino acids, and edible oil (20%). Salinity stress affects soybean yield 30-80%. Salinity stress significantly reduces net photosynthetic rates, increases energy losses for the mechanism of salt exclusion, substantially decreases nutrient intake and ultimately results in reduced plant growth. Present investigation was conducted to show how morphological and biochemical changes occur due to the stress of salinity on the soybean plant genotypes. Stress with salinity resulted in increased protein and proline content to withstand stress with salinity. Better root length, shoot length fresh weight and dry weight were observed of JS-355 variety. The JS-355 variety demonstrated the better response to all concentrations of salt stress used from 40 mM to 280 mM. As the salt concentration increases, so does the protein and proline concentration. The JS-355 variety showed the better results at all salt concentrations. The highest protein and proline content at high salt concentration was observed in varietyJS-355.

The present study was conducted in Latur district from Marathwada region of Maharashtra state during the years 2018-19. Three talukas viz., Latur, Ausa and Renapur of Latur District were selected randomly and four villages from each taluka were selected randomly. From each village ten members were randomly selected constituting the sample size 120. A number of profile characteristics were selected as independent variables to find out profile of farmers from the study area. All profile characteristics, age, education, family size, annual income, social participation, extension contacts, sources of information, knowledge level were found in medium category while majority of the respondents were having marginal land holding. It was observed from that variables like age and family size had found to be non-significant relationship with attitude of farmers towards sustainable agricultural practices. Variables like education, land holding, annual income, social participation and extension contact found to be positive and significant relationship with attitude of farmers towards sustainable agricultural practices. Variables like source of information and knowledge had positive and highly significant relationship with attitude of farmers towards sustainable agricultural practices.

India is the land of Agriculture. The role of the agricultural sector still important to Indian economy. However, despite the tremendous significance of agriculture in our country, there is disillusionment among students toward in higher agricultural education. Most of the school going students choose their career in medical and engineering and counts agriculture as boring and unattractive subject. Enhancing their perception and attitude toward agriculture as the fastest growing industry where they can start their own entrepreneurial and helping other to acquire knowledge and skill related to agriculture development will reduce dependence on government jobs and help youths to start their own agriculture start-up that will be beneficial to national economy. Thus the present study was carried out to assess students’ perception on enrolment factors in retention in higher agricultural education. A Study was conducted in six colleges of Bihar Agriculture University, Sabour, Bhagalpur. Eighty students from these six colleges were chosen through stratified random sampling. The collected data were classified, tabulated and analyzed. The findings inferred that there are major Enrolment Factors (out of twenty) contributes in students retention is agricultural education, promote agriculture within the country (Rank I). The finding of the study will help extension policy makers and Governments to frame suitable polices for educating students and youths and enhance their knowledge towards agriculture and retention in higher agricultural education.

The study focused on the analysis of two neighboring zones in the Los Humeros geothermal field (LHGF), each one with different characteristic behaviors. A characterization methodology which can be used in geothermal reservoir engineering was designed and applied to study the zones. The static temperature profiles determined in wells located at the studied zone of the field ranged between 300°C and 360°C. From these temperatures, isotherms in the studied area were calculated and these trend to be deeper toward eastern zone of the field. Similarly the thicknesses tend to reduce in this direction. By analyzing the profiles of fluid circulation losses were determined during drilling of wells in this zone, the existence of low permeability in the rock formation was inferred. From the results of transient pressure tests, low permeability was confirmed. A marked difference in the productive characteristics between the wells, in the close neighborhood was also observed.  Behavior of wells also shows tendency to increase in their steam fractions, with the exploitation time. The characterization methodology applied to the studied zones, allows identify that there is a reservoir section with low permeability, but with high temperatures the depth increases.

Disruptive innovation is the main form of innovation for latecomers to catch up with technology. Knowledge spillover can achieve low-cost disruptive innovation, which has an important impact on the development of disruptive innovation. Disruptive innovation of latecomers can promote the flow of knowledge in the production network. Disruptive innovation and knowledge spillover are two independent and interrelated systems, but the relationship between them is not fully explained. In this paper, the index system of interactive coupling evaluation is constructed, the index weight is calculated by entropy weight method, and the coupling evaluation model of disruptive innovation and knowledge spillover is established to reveal the relationship between them. It is found that disruptive innovation and knowledge spillover are in the stage of moderate coupling and highly coordinated coupling and the contribution rate of the two systems in the total system will affect the coupling and coordination between them.

Demands for fish protein including dried fish protein to develop functional food are gradually growing in the world. Surimi, the concentrated myofibrillar protein extracted from fish flesh by washing minced meat, separated from bones, skin, and guts with added cryoprotectants such as sugar or alcohol (most commonly used cryoprotectant in the surimi industry is 1:1 mixture of sucrose and sorbitol at a concentration of 8%), finally stored in frozen condition in block form, is used as a raw material for preparation of number of value-added products. The dried form of surimi can be prepared from frozen surimi blocks by adopting different drying technologies and it offers many advantages such as ease of handling, lower distribution costs and more convenient storage. The present work is aimed to study the effect of drying temperature on the quality of dry surimi powder, prepared from Pangasius meat. A significantly higher (p<0.05) value of ash (1.83±0.47%) was recorded in surimi powder dried at 60°C than at 50°C and 70°C. The moisture content significantly (p<0.05) reduced at 60° (9.05±0.22%) and 70°C (9.55±0.51%) as compared to 50°C. The quality parameters such as TVB-N, PV, pH and TPC were all found to be well within the recommended level of acceptability except for the surimi powder dried at 50°C, wherein the TVBN (36.24±1.26 mg/100 g) crossed the limit of acceptability. Drying temperature was found to affect the colour of the surimi powder with the optimum acceptable colour score achieved at 60°C (6.38±0.52). At higher temperature of 70°C darkening was observed with consequent decrease in the colour scores (5.75±0.46). Therefore, the optimal temperature for drying of Pangasius surimi into its powdered form was achieved during its exposure at temperature of 60°C.

Data Mining [DM] has exceptional and prodigious potential for examining and analyzing the vague data of the medical domain. Where these data are used in clinical prognosis and diagnosis. Nevertheless, the unprocessed medical data are widely scattered, diverse in nature, and voluminous. These data should be accumulated in a sorted out structure. DM innovation and creativity give a customer a situated way to deal with new fashioned and hidden patterns in the data.

The advantages of using DM in medical approach are unbounded and it has abundant applications, the most important: it leads to better medical treatment with a lower cost. Consequently, DM algorithms have the main usage in cancer detection and treatment through providing a learning  rich environment which can help to improve the quality of clinical decisions. Multi researches are published about the using of DM in different destinations in the medical field. This paper provides an elaborated study about utilization of DM in cancer prediction and classifying, in addition to the  main features and challenges in these researches are introduced in this paper for helping  apprentice and youthful scientists and showing for them the key principle issues that are still exist around there.