4.7 Article

Antioxidant activity of polyphenols from Ontario grown onion varieties using pressurized low polarity water technology

Journal

JOURNAL OF FUNCTIONAL FOODS
Volume 31, Issue -, Pages 52-62

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.jff.2017.01.037

Keywords

Ontario onions; Flavonoids; Antioxidants; Phenolic compounds; Polyphenols

Funding

  1. Ontario Ministry of Research and Innovation [0520512]
  2. Natural Sciences and Engineering Research Council of Canada [400929]
  3. Ontario Ministry of Agriculture, Food and Rural Affairs [500135]

Ask authors/readers for more resources

Natural by-products, especially flavonoids, are in great demand in the nutra-pharmaceutical and biomedical industries. In this study, Ontario-grown onion varieties, namely Stanley, Safrane, Fortress, Lasalle and Ruby Ring, were screened for their antioxidant properties. Pressurized low polarity water technology, an environmentally friendly technique, was employed to extract the flavonoids from the onion varieties, followed by quantification and analysis using High Performance Liquid Chromatography. The antioxidant activities in the extracted samples were determined using various antioxidant assays, such as 2,2-diphenyl-l-picrylhydrazyl, 2,2'-azino-bis (3-ethylbenzothiazoline-6-sulphonic acid), ferric reducing ability of plasma, lipid peroxidation, total antioxidant capacity and oxygen radical absorbance capacity assays. The total phenolic content extracted from the Ruby Ring variety was the highest when compared to all the other yellow onion varieties tested. Our results indicate that Ruby Ring may be chosen as a preferred variety over other onion varieties to develop functional and health food products. (C) 2017 Elsevier Ltd. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Review Agriculture, Dairy & Animal Science

Transforming the Adaptation Physiology of Farm Animals through Sensors

Suresh Neethirajan

ANIMALS (2020)

Review Chemistry, Analytical

Measuring Farm Animal Emotions-Sensor-Based Approaches

Suresh Neethirajan, Inonge Reimert, Bas Kemp

Summary: Understanding animal emotions is crucial for improving animal welfare, but currently there are no scientific assessments available for measuring emotional responses. Using sensors to collect biometric data for measuring animal emotions is a growing topic in agricultural technology, involving various sensors and processing algorithms in the analysis systems.

SENSORS (2021)

Review Agriculture, Dairy & Animal Science

Social Network Analysis in Farm Animals: Sensor-Based Approaches

Suresh Neethirajan, Bas Kemp

Summary: Social behaviour has a significant impact on livestock management and animal welfare. The use of sensing technologies in social network analysis of farm animals allows for a better understanding of animal interactions and behavioural dynamics. This can ultimately lead to improvements in welfare and farm management processes.

ANIMALS (2021)

Review Agriculture, Dairy & Animal Science

Digital Twins in Livestock Farming

Suresh Neethirajan, Bas Kemp

Summary: A digital twin is a digital replica of a real-world entity that helps farmers monitor animal behavior, improve business decisions, and enhance precision farming in the livestock sector. With the integration of artificial intelligence and machine learning, digital twins have the potential to play a significant role in modern animal farming.

ANIMALS (2021)

Review Agriculture, Dairy & Animal Science

Digital Phenotyping in Livestock Farming

Suresh Neethirajan, Bas Kemp

Summary: The application of wearable sensors in animal farming has great potential for providing reliable information to growers and welfare-conscious consumers. These sensors can collect specific data on animal health, welfare, and profitability, with the goal of creating shared data standards and stores in the future. Further research is needed to tailor these technologies efficiently and accurately for different species and to improve the overall well-being and production of farm animals.

ANIMALS (2021)

Review Veterinary Sciences

The Use of Artificial Intelligence in Assessing Affective States in Livestock

Suresh Neethirajan

Summary: To promote the welfare of farm animals, it is essential to recognize, register, and monitor their affective states. Artificial intelligence and machine learning offer a promising approach to automate emotion recognition in production animals, leading to improved animal welfare and productivity.

FRONTIERS IN VETERINARY SCIENCE (2021)

Article Agriculture, Dairy & Animal Science

Automated Tracking Systems for the Assessment of Farmed Poultry

Suresh Neethirajan

Summary: With the advancement of artificial intelligence, the poultry industry is increasingly adopting sensor technologies for automated tracking and tracing of poultry birds. These systems have advantages such as overcoming human subjectivity, enhancing care for birds, and enabling timely interventions. However, there are still challenges in algorithm development and implementation. This review explores recent advancements and the potential future directions of AI-assisted automated tracking systems in poultry farming.

ANIMALS (2022)

Review Veterinary Sciences

Is Seeing Still Believing? Leveraging Deepfake Technology for Livestock Farming

Suresh Neethirajan

Summary: Despite the negative implications associated with Deepfake technologies, the underlying machine learning algorithms have enormous potential that can be applied to various fields such as digital media, medicine, biology, affective science, and agriculture.

FRONTIERS IN VETERINARY SCIENCE (2021)

Article Agriculture, Dairy & Animal Science

ASAS-NANP symposium: mathematical modeling in animal nutrition: limitations and potential next steps for modeling and modelers in the animal sciences

Marc Jacobs, Aline Remus, Charlotte Gaillard, Hector M. Menendez, Luis O. Tedeschi, Suresh Neethirajan, Jennifer L. Ellis

Summary: The hype of artificial intelligence has shown the limitations of modeling as a human process, emphasizing the importance of data and human involvement in the sustainable role of models in the animal sciences ecosystem.

JOURNAL OF ANIMAL SCIENCE (2022)

Article Agriculture, Dairy & Animal Science

Affective State Recognition in Livestock-Artificial Intelligence Approaches

Suresh Neethirajan

Summary: Emotions and affective states recognition in farm animals is an underexplored research domain, but the use of biometric sensors and artificial intelligence methods offer the potential to improve animal welfare standards. Currently, there are no scientifically validated methods for assessing farm animal emotions, and traditional monitoring methods have limitations. Biometric sensor data and AI technology can unobtrusively monitor farm animals, but their potential for quantifying affective states and applications are yet to be realized.

ANIMALS (2022)

Correction Agriculture, Dairy & Animal Science

Affective State Recognition in Livestock-Artificial Intelligence Approaches (vol 12, 759, 2022)

Suresh Neethirajan

ANIMALS (2022)

Article Agriculture, Dairy & Animal Science

DISubNet: Depthwise Separable Inception Subnetwork for Pig Treatment Classification Using Thermal Data

Savina Jassica Colaco, Jung Hwan Kim, Alwin Poulose, Suresh Neethirajan, Dong Seog Han

Summary: Thermal imaging is increasingly used in animal husbandry to detect disease and distress. This paper proposes a lightweight model, DISubNet, for classifying pig treatments based on thermal images, leading to improved animal welfare and sustainable pig production.

ANIMALS (2023)

Review Agronomy

SOLARIA-SensOr-driven resiLient and adaptive monitoRIng of farm Animals

Suresh Neethirajan

Summary: Sensor-enabled big data and artificial intelligence platforms have the potential to address global socio-economic trends related to the livestock production sector. However, current digital approaches do not meet the challenges due to a lack of efficient and real-time non-invasive precision measurement technologies that can detect and monitor animal diseases and identify resilience in animals.

AGRICULTURE-BASEL (2023)

Review Agricultural Engineering

The Significance and Ethics of Digital Livestock Farming

Suresh Neethirajan

Summary: The emergence of precision and digital livestock farming provides an opportunity for sustainable animal farming practices that improve animal welfare and health. However, this transformation raises ethical concerns around the potential digital divide, the loss of personal connection between farmers and animals, and the objectification of animals as data points. Addressing these concerns requires the development of standards and codes of conduct, as well as the integration of virtual and augmented reality technologies for enhanced human-animal interactions and personalized care.

AGRIENGINEERING (2023)

Article Anesthesiology

Regional Anaesthesia in Harris Platelet Syndrome for Transurethral Resection of Prostate-A Clinical Conundrum or Certitude?

Soma Ganesh Raja Neethirajan, Aishwarya Ramesh, Aruna Parameswari

Summary: The routine use of the autoanalyzer has helped uncover the increasing incidence of thrombocytopenia, with disorders associated with macrothrombocytes requiring preoperative evaluation to assess bleeding tendencies and transfusion needs. Harris platelet syndrome, a disorder characterized by macrothrombocytes and thrombocytopenia, has a low risk of intraoperative bleeding and has been mistakenly treated with steroids or splenectomy in some cases. Successful management of a patient with Harris platelet syndrome undergoing transurethral resection of the prostate without complications has been reported, highlighting the importance of proper diagnosis and treatment.

TURKISH JOURNAL OF ANAESTHESIOLOGY AND REANIMATION (2021)

No Data Available