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The purpose of the research paper is to examine customers' online purchase intention towards apparel in the online environment, with a focus on the role of conviction and brand reputation of the e-retailer.

Hypotheses are based on an extensive literature review and tested using adapted existing scales for the constructs-social media usage for apparel, electronic word of mouth (EWOM), conviction, apparel e-retailer's brand reputation and online purchase intention towards apparel, and data are collected from 362 online customers of apparel brands in eight major cities across the country. Structural equation modelling (SEM) is applied to analyze data and test hypotheses because of multiple dependent variables.

The quantitative results indicate that impact of social media and EWOM on online purchase intention towards apparel is mediated by conviction. The results also explain the moderating effect of apparel e-retailer's brand reputation.

Findings provide suggestions for the apparel business in an online environment that address the issue of breach of trust and implications for apparel e-retailers, managers and researchers. The study contributes to the existing retail literature by proposing concept of conviction and role of apparel e-retailer's brand reputation in this context.

The purpose of this paper is to propose the concept of conviction in online environment. It examines the vital role of conviction and firm’s brand reputation while understanding the impact of social media usage and electronic word-of-mouth (EWOM) on purchase decisions of Generation Y.

Literature review resulted in six constructs – social media usage, EWOM, conviction, firm’s brand reputation and purchase intention and customer loyalty. The authors adopted the concept of conviction from another field of enquiry (organizational learning), conducted a qualitative study and an e-mail survey with post-graduate management students (Generation Y) of a university to examine the impact of social media and EWOM on customer purchase decision. Data were collected and analyzed with the help of structural equation modeling.

Results indicated that impact of social media usage and EWOM on purchase decision is mediated by conviction. Firm’s reputation as brand (perceived by the customer) moderates the relationship between EWOM and purchase intention in a manner that this relationship is significantly stronger if there is more positive brand reputation.

This study validates the concept of conviction in online environment. The purchase decision is defined as purchase intention and loyalty of the customer.

The Million Farmers School (MFS) program—also known as Kisan Pathshala was launched to impart training to the farmers by the government of the state of Uttar Pradesh (India) in December 2017. This study estimates the impact of training on agricultural knowledge of the farmers.

The study is based on household survey conducted in Uttar Pradesh (UP), India, during March–May 2019. The authors employed matching methods, the two-stage least square (2SLS)-residual and endogenous switching regression approaches to control for selection bias and endogeneity.

The results suggest that knowledge outcomes are significantly better among participants vis-à-vis non-participants. The results are robust to different model specifications. Further, the benefits are observed across different regions and social groups.

The MFS program can go a long way in enhancing agricultural know-how and the farmers' economic well-being, bringing a transformative change in the agricultural landscape of UP.

This study is based on a field survey data and analyzes various aspects of the program's impact, design and implementation, and offers implementation advice for greater efficacy in future.

While rapid increase in demand for foods but limited availability of croplands has forced to adopt input-intensive farming practices to increase yield, there are serious long-term ecological implications including degradation of biodiversity. It is increasingly recognised that ensuring agricultural sustainability under the changing climatic conditions requires a change in the production system along with necessary policies and institutional arrangements. In this context, this chapter examines if climate-smart agriculture (CSA) can facilitate adaptation and mitigation practices by improving resource utilisation efficiency in India. Such an attempt has special significance as the existing studies have very limited discussions on three main aspects, viz., resource productivity, adaptation practices and mitigation strategies in a comprehensive manner. Based on insights from the existing studies, this chapter points out that CSA can potentially make significant contribution to enhancing resource productivity, adaptation practices, mitigation strategies and food security, especially among the land-constrained farmers who are highly prone to environmental shocks. In this connection, staggered trench irrigation structure has facilitated rainwater harvesting, local irrigation and livelihood generation in West Bengal. However, it is necessary to revisit the existing approaches to promotion of CSA and dissemination of information on the design of local adaptation strategies. This chapter also proposes a change in the food system from climate-sensitive to CSA through integration of technologies, institutions and policies.

Soy beverage is becoming more and more popular because it is touted as a healthy food containing useful phytochemicals and is free from lactose and cholesterol. The purpose of this paper is to optimize the spray drying process parameters for obtaining soy beverage powder with good reconstitution and handling properties.

Pre-concentrated soy beverage was dried in a laboratory model spray dryer, and the effects of inlet air temperature (180-220°C), feed rate (20-40 ml/min) and feed solid content (15-25 per cent) on some physical parameters and reconstitution properties (wettability and dispersibility) of spray-dried soy beverage powders were investigated. Second order polynomial response surface model was selected for the analysis of data and optimization of the process.

Spray drying of soy beverage at different processing conditions resulted in powders with particle size (volume mean diameter) in the range of 86 to 156 µm. Dispersibility and wetting time of the spray-dried soy beverage powders was found to be in the range of 56 to 78 per cent and 30 to 90 s respectively, under various drying conditions. Inlet air temperature was found to be the main factor affecting most of the quality parameters, followed by solid content of the feed. Temperature significantly affected the wettability, dispersibility, colour parameters, particle size and flowability of the powder at p ≤ 0.01. Lower temperature and higher feed solid content produced bigger-sized powder particles with better handling properties in terms of flowability and cohesiveness. A moderate inlet air temperature (196°C), higher feed solid content (24 per cent) and lower feed rate (27 ml/min) were found suitable for drying of soy beverage.

The study implied the possibility of producing powder from soy beverage using the spray-drying method and optimized drying conditions for obtaining soy beverage powder with good reconstitution properties.

The finding of this study demonstrated for the first time how the inlet air temperature, feed solid content and feed rate during spray-drying influenced different quality parameters of soy beverage powder. Further, an optimized drying condition has been identified.

This study examined the effects of adopting dairy feed technology bundles on the milk production of smallholder dairy farmers.

The study was based on Multinomial Endogenous Switching Regression (MESR) to estimate the effects of the adoption of three feed technology bundles on milk production using data collected from 518 dairy farm households in West Java, Indonesia.

The findings indicated that adopting technology bundles had positive and robust effects on milk production, with gradual positive effects between non-adoption and the adoption of different bundles of technologies.

This study focused on the association between the adoption of feed technology bundles and milk production. However, further analysis of the causal links between the adoption of feed technologies and milk production as well as the inclusion of other outcomes in the analysis, such as production costs and risk mitigation, are required.

Most of the literature on agricultural technology adoption focuses on the adoption of individual technologies, crop farming and conservation practices. Therefore, this study examined the effects of the adoption of dairy feed technology bundles.

This paper aims to study the color change kinetics of lac dye in response to pH and food spoilage metabolites (ammonia, lactic acid and tyramine) for its potential application in intelligent food packaging.

UV-Vis spectroscopy was used to study the color change of dye solution. Ratio of absorbance of dye solution at 528 nm (peak of ionized form) to absorbance at 488 nm (peak of unionized form) was used to study the color change. Color change kinetics was studied in terms of change in absorbance ratio (A528/A488) with time using zero- and first-order reaction kinetics. An indicator was prepared by incorporating lac dye in agarose membrane to validate the result of study for monitoring quality of raw milk.

Dye was orange-red in acidic medium (pH: 2 to 5) and exhibited absorbance peak at 488 nm. It turned purple in alkaline medium (pH: 7 to10) and exhibited absorbance peak at 528 nm. The change in absorbance ratio with pH followed zero-order model. Acid dissociation constant (pKa) of dye was found to be 6.3. Color change of dye in response to ammonia and tyramine followed zero-order reaction kinetics, whereas for lactic acid, the first-order model was found best. In the validation part, the color of the indicator label changed from purple to orange-red when the milk gets spoiled.

The study opens a new application area for lac dye. The results suggest that lac dye has potential to be used as an indicator in intelligent food packaging for detection of spoilage in seafood, meat, poultry and milk.

The purpose of this paper is to study the application of entropy based optimized fuzzy logic control for a real-time non-linear system. Optimization of the fuzzy membership function (MF) is one of the most explored areas for performance improvement of the fuzzy logic controllers (FLC). Conversely, majority of previous works are motivated on choosing an optimized shape for the MF, while on the other hand the support of fuzzy set is not accounted.

The proposed investigation provides the optimal support for predefined MFs by using genetic algorithms-based optimization of fuzzy entropy-based objective function.

The experimental results obtained indicate an improvement in the performance of the controller which includes improvement in error indices, transient and steady-state parameters. The applicability of proposed algorithm has been verified through real-time control of the twin rotor multiple-input, multiple-output system (TRMS).

The proposed algorithm has been used for the optimization of triangular sets, and can also be used for the optimization of other fussy sets, such as Gaussian, s-function, etc.

The proposed optimization can be combined with other algorithms which optimize the mathematical function (shape), and a potent optimization tool for designing of the FLC can be formulated.

This paper presents the application of a new optimized FLC which is tested for control of pitch and yaw angles in a TRMS. The performance of the proposed optimized FLC shows significant improvement when compared with standard references.

The purpose of this paper was to study the color change kinetics of lac dye in response to aldehydes, carbon dioxide and other food spoilage metabolites for its potential application in intelligent food packaging.

UV–Vis spectroscopy was used to study the color change of dye solution. Ratio of absorbance of dye solution at 528 nm (peak of ionized form) to absorbance at 488 nm (peak of unionized form) was used to study the color change. Color change kinetics was studied in terms of change in absorbance ratio (A₅₂₈/A₄₈₈) with time using zero and first-order reaction kinetics. Lac dye-based indicator was prepared to validate the result of study for monitoring quality of strawberries.

Lac dye was orange-red in acidic medium and purple in alkaline medium. Color change of dye in response to benzaldehyde followed zero-order reaction kinetics, whereas for carbon dioxide first-order model was found best. No color change of dye solution was observed for alcohols, ketones and sulfur compounds. In the validation part, the color of the indicator label changed from purple to orange when the strawberries spoiled.

The study expands application area for lac dye as sensing reagent in intelligent food packaging for spoilage or ripeness detection of fruits and vegetables.

Purpose of this study is to classify the states of Markov Chain for the implementation of Markov Password for effective security. Password confirmation is more often required in all authentication process, as the usage of computing facilities and electronic devices have developed hugely to access networks. Over the years with the increase in numerous Web developments and internet applications, each platform needs ID and password validation for individual users.

In the technological development of cloud computing, in recent times, it is facing security issues. Data theft, data security, denial of service, patch management, encryption management, key management, storage security and authentication are some of the issues and challenges in cloud computing. Validation in user login authentications is generally processed and executed by password. To authenticate universally, alphanumeric passwords are used. One of the promising proposed methodologies in this type of password authentication is Markov password. Markov passwords – a rule-based password formation are created or generated by using Markov chain. Representation of Markov password formation can be done by state space diagram or transition probability matrix. State space classification of Markov chain is one of the basic and significant properties. The objective of this paper is to classify the states of Markov chain to support the practice of this type of password in the direction of effective authentication for secure communication in cloud computing. Conversion of some sample obvious password into Markov password and comparative analysis on their strength is also presented in this paper. Analysis on strength of obvious password of length eight has shown range of 7%–9% although the converted Markov password has shown more than 82%. As an effective methodology, this password authentication can be implemented in cloud portal and password login validation process.

The objective of this paper is to classify the states of Markov chain to support the practice of this type of password in the direction of effective authentication for secure communication in cloud computing. Conversion of some sample obvious password into Markov password and comparative analysis on their strength is also presented in this paper.

Validation in user login authentications is generally processed and executed by password. To authenticate universally, alphanumeric passwords are used. One of the promising proposed methodologies in this type of password authentication is Markov password.