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No full textThe increasing global demand for broiler meat
has highlighted the significance of religious
slaughtering methods, such as Halal and Kosher,
due to their impact on meat quality and consumer
preferences. This study examines the effects of
these methods on the quality of broiler meat,
focusing
on
physicochemical
nutritional
properties,
composition,
and
sensory
attributes. A total of 25 birds were slaughtered
using each method, and the resulting meat
samples were analysed for moisture, ash, fat,
protein content, pH, colour, texture, and sensory
qualities. The results showed no significant
differences between Halal and Kosher methods in
moisture, ash, fat, and protein content. However,
Halal meat exhibited higher pH and lightness
values, which could influence its appearance and
shelf life. Sensory evaluation revealed no
significant differences in consumer preference,
although Halal meat scored slightly higher in
aroma, taste, and overall acceptability. While
these findings align with some previous studies,
the small sample size limits the generalizability
and credibility of the results. Future research with
larger sample sizes is necessary to validate these
findings and provide a more comprehensive
understanding of the differences between Halal
and Kosher slaughtering methods. Ultimately, the
choice between these methods may be driven more
by religious and cultural beliefs than by
significant differences in meat quality. This study
affirms that both Halal and Kosher methods are
effective in producing high-quality broiler meat,
reflecting the diversity of dietary practices and the
importance of respecting consumer preferences in
the global market
Impact of IT governance mechanisms on IT-enabled dynamic capabilities to achieve firm performance: role of moderators
Get PDFPurpose
Although information technology (IT) governance and IT capability have been extensively examined, the impact of IT governance mechanisms on IT-enabled dynamic capability (ITDC) with moderators has received less attention. This study investigates how the impact of IT governance mechanisms on firm performance is achieved through an ITDC through the moderating role of IT governance decentralization and a turbulent environment.
Design/methodology/approach
This study extends from the traditional view of IT capabilities and integrates dynamic capability theory to propose that IT governance is vital for the ITDC. Path analysis, hierarchical regression analysis and moderation analysis were performed using partial least squares (Smart PLS 3.0) as the data analysis methods. This study empirically tests the proposed mediated moderation model by using data collected from 254 firms in China to test the hypotheses.
Findings
Significant and impactful relationships are found in the model that includes turbulent environment moderating effects. Contrary to expectations, IT governance decentralization is also significant but not very strong.
Research limitations/implications
This study’s findings have implications for investigating IT governance, IT-enabled capabilities and moderators. Accordingly, this study has implications for board and executive management to capitalize on dynamic IT capability, to keep pace with the challenges and turbulent conditions associated with business needs and for the productivity paradox in the context of Chinese firms.
Originality/value
This country-specific research study theoretically contributes to the IT governance, dynamic capabilities and turbulent environment in the information systems literature and proposes many practical guides to the board and executive management of companies in the Chinese context
Development of ice cream added with jackfruit (artocarpus heterophyllus) and sugarcane syrup
Get PDFThe jackfruit (Artocarpus heterophyllus Lam.) is one of the important
tropical fruits cultivated in the worldwide. The objective of this study was to
optimize the amount of jackfruit pulp added to the ice cream while taking
account of consumer demand and nutritional value. Well-ripened jackfruits
were blended with 5% water and heated to 70°C to create jackfruit pulp. The
ice cream composites were made by combining fresh milk and jackfruit pulp
in the following ratios: 10:90 (T2), 15:85 (T3), 20:80 (T4), and control
sample. The physical and chemical characteristics (pH, moisture content,
titratable acidity, Ash, protein, and fat), sensory attributes and yeast and mold
were ascertained. There was a significant difference in the Moisture content,
pH and titratable acidity value of the ice cream between the treatments. The
moisture content ranged from 64.19±1.22 % to 54.28±0.13%, pH ranged
from 6.75±0.01 to 6.47±0.01 and titratable acidity from 0.23 to 0.13.
Additionally, the highest overrun percentage was observed in 15% jackfruit
pulp incorporated ice cream. Yeast and mould count were absent in all the
treatments. Based on the sensory evaluation, ice cream with 15% jackfruit
pulp incorporated ice cream was recorded the highest score for taste, flavor,
mouth feel, appearance and overall acceptability. In conclusion, 15%
jackfruit pulp and 85% fresh milk work better as ingredients for ice cream
preparation
issn
No full textThis study explores the impact of the
“Entrepreneurial School Garden Program” on
students’ environmental attitudes, using a mixed
methods research approach. This program
integrates practical gardening activities with the
school’s co-curriculum to enhance knowledge and
skills in food and nutrition, agriculture, and
entrepreneurship.
Quantitative
data
were
collected through a survey on a sample of 214
students in the Jaffna district, where 22 schools
had completed the program. Qualitative data were
gathered through interviews with 5 groups of
teachers, observations, and document analysis.
The results revealed significant improvement in
environmental attitudes (M=4.0494, SD=
0.7538). Students perceived improvements in
their environmental awareness (M=3.9745),
positive
I.
INTRODUCTION
In recent years, there has been a growing interest
among the curriculum designers and educational
researchers on the effectiveness of extracurricular
activities for developing social and emotional
competencies in school students. Thus, attention
is focused on the role of school-based gardening
programs as a means of enhancing students'
educational
experiences
and
personal
development. These programs are increasingly
recognized by educators for their potential to
foster a range of positive outcomes, including
improved
attitudes
toward
environmental
sustainability (M=3.9185), and adaptability to
environmental
changes
(M=4.195).
The
frequency of engagement in gardening activities
influenced students’ attitudes, while female
students exhibited greater improvements than
male students. Qualitative data analysis revealed
improvements in a sense of responsibility and
achievement, enhanced social skills and
teamwork,
and
increased
environmental
awareness and stewardship. The frequency and
duration of engagement have an influence on
motivation. Students are perceived to be more
responsible and capable of dealing with
environment-related problems through their
improved problem-solving skills, goal-setting
abilities, and self-awareness. They developed
better communication skills, empathy, and
teamwork to adapt themselves to the environment.
The engagement in gardening resulted in an
improved consciousness of sustainability and
commitment to environmental stewardship
Effects of cyberbullying on learners’ writing skills at the University of Kotli Azad Jammu and Kashmir
Get PDFPurpose: This study explores the impact of cyberbullying - defined as the use of
electronic communication to harass or intimidate - on university students’ writing
skills, particularly those using social media. It examines how cyberbullying affects
both the social and psychological aspects of students' academic writing, highlighting
an underexplored consequence of online harassment in higher education.
Design/Methodology/Approach: The target population for the study comprised
undergraduate students from the University of Kotli Azad Jammu and Kashmir. A
random sampling technique was used to select a sample of 350 undergraduates. Data
were collected through a structured questionnaire to analyze the relationship between
cyberbullying and writing proficiency.
Findings: The study reveals that cyberbullying significantly impacts students’
confidence, self-expression, and clarity in writing. Participants exposed to
cyberbullying reported reduced focus and coherence in academic writing,
demonstrating that online harassment negatively influences critical academic skills.
Practical Implications: The findings highlight the need for educational institutions
to implement digital literacy and anti-cyberbullying programs. Policymakers can also
leverage these insights to strengthen regulations aimed at minimizing cyberbullying
and safeguarding students’ academic performance.
Originality/Value: This study provides novel insights into how cyberbullying affects
students' writing skills, bridging a gap in existing research that often overlooks the
academic consequences of cyberbullying. It offers valuable implications for educators,
students, and policymakers to foster safer online environments
issn
No full textPurpose: Liquidity management encompasses both investment and financing
policies, with maintaining an optimal balance being crucial for profitability. This
study examines whether high liquidity turnover companies in Sri Lanka adopt
conservative or aggressive strategies to financing and investing in current assets, and
how these strategies effect profitability.
Design/methodology/approach: The study analyzes data from 56 companies across
the materials, capital goods, and retail sectors over a 10-year period (2013–2022),
using panel regression analysis in E-Views.
Findings: The fixed effect model reveals that companies with high liquidity adopting
a
conservative financing policy experience a significant negative effect on
profitability, likely due to increased opportunity costs and growth restrictions.
Meanwhile, investment policy shows an equal distribution between fixed and current
assets but has no significant effect on profitability, suggesting that matching assets
does not drive profit growth. However, sales levels show a significant and positive
effect on profitability, indicating that higher revenue generation directly boosts
profits.
Practical implications: Companies typically achieve profitability through increased
sales, yet conservative financing policies may restrict these gains. This study suggests
that a less conservative financing approach may enhance profitability.
Originality value: This study offers localized insights into the profitability impacts
of liquidity management in Sri Lanka’s high liquidity sectors. It highlights the value
of balancing short-term financing with current assets through effective forecasting to
optimize risk and return in similar emerging economies
Deep learning for ripeness and freshness detection of local fruits in the export industry
Get PDFIn the export industry, ensuring consistent fruit quality is crucial for meeting
international standards, satisfying customer expectations, and minimizing food waste.
This study focuses on the classification of two key fruit quality attributes ripeness (raw
or ripe) and freshness (fresh or rotten). The research examines local varieties of papayas,
mangoes, and bananas, which are significant for export markets. By employing
advanced image classification techniques, the study aims to develop a reliable system
that can support quality control in the export process. A Convolutional Neural Network
(CNN) was used as the primary model for image classification. Additionally, other
machine learning algorithms such as Decision Tree, Random Forest, and K-Nearest
Neighbors (KNN) were evaluated for performance comparison. The dataset comprises
over 10,000 images, sourced from both local markets and online databases, with a
particular focus on local papayas. Two training strategies were implemented one using
a larger, online-only dataset and another combining online data with additional samples
from local markets. The CNN model achieved over 95% accuracy in predicting fruit
freshness using both methods. However, for ripeness prediction, the second approach
integrating local market data produced slightly better results than the online-only
dataset. This underlines the importance of including diverse data to build robust models.
The comparison of different algorithms revealed that CNN consistently outperformed
others, especially in freshness detection. These findings provide actionable insights for
improving quality assurance and operational efficiency in the export industry, helping
reduce food waste and increase customer satisfaction through the adoption of advanced
machine learning techniques
AI-driven agriculture: a comprehensive review of machine and deep learning applications
Get PDFPurpose: This study assesses and consolidates Artificial Intelligence (AI) and robotic
based farm automation advancements, focusing on machine learning (ML) and deep
learning (DL). The paper compares AI algorithms and architectures for plant disease
detection, weed and crop identification, fruit counting, land cover classification, and
crop and plant recognition.
Design/methodology/approach: This article analyses the current ML and DL
algorithm advances in agricultural robotics over the last decade using a systematic
literature review. Region-based Convolutional Neural Networks (RCNN), ResNet-18,
and Fully Convolutional Networks (FCN) are compared to traditional ML algorithms
like Multi-Layer Perceptron (MLP), K-nearest Neighbour (KNN), Random Forest
(RF), and Support Vector Machine (SVM) to determine their precision and
effectiveness.
Findings: RCNNs identify plant diseases at 79.78% vs 57.18% for MLP and KNN.
ResNet-18 has a high Area Under the Curve (AUC) of 91.74% for crop-weed
separation. This discriminates better than RF and SVM. FCN outperforms SVM and
RF in land cover classification at 84.9%. The data show that DL techniques improve
agricultural automation very well.
Practical implications: This investigation shows that DL algorithms can considerably
improve agricultural automation. Agriculture professionals may enhance disease
identification, crop classification, and land coverage analysis by using advanced DL
models.
Originality value: This paper analyses the current ML and DL breakthroughs in
agricultural automation to expand knowledge. It offers fresh viewpoints on AI model
efficacy and highlights key research areas
Unlocking market secrets: dynamics of the day-of-the-week effect during crisis in an emerging market
No full textBy examining the impact of the day of the week during the COVID-19 pandemic and the subsequent economic recession, it is possible to provide insights into market behaviour during volatile times that can be furnished to investors and policymakers for informed decisions. This study investigates the day-of-the-week effect on the Colombo Stock Exchange (CSE), with particular emphasis on the variations in this effect during the COVID-19 pandemic and the subsequent economic crisis. The study applies the Exponential Generalised Autoregressive Conditional Heteroskedasticity (EGARCH) model, allowing for the evaluation of asymmetric responses to positive and negative shocks. The data span from January 2006 to December 2022 and are segmented into different periods: the entire sample, war and post-war periods, the COVID-19 pandemic and the economic crisis period, each reflecting distinct market conditions. The study uncovers a significant day-of-the-week effect on the CSE. Mondays and Tuesdays typically show a negative effect, while Thursdays and Fridays display a positive impact. However, this pattern shifts notably during the COVID-19 pandemic, with all weekdays exhibiting significant positive impact, and varies further across different waves of the pandemic. The economic crisis period also shows unique weekday effects, particularly before and after an important political event