Marine Algae and the Global Food Industry

Marine Algae ◽  
2014 ◽  
pp. 308-327 ◽  
Author(s):  
Jeff T. Hafting ◽  
M. Lynn Cornish ◽  
Amy Deveau ◽  
Alan T. Critchley

2019 ◽  
Vol 11 (18) ◽  
pp. 5072 ◽  
Author(s):  
Vivek Pandey ◽  
Natalia Vidal ◽  
Rajat Panwar ◽  
Lubna Nafees

The global food industry has a critical role to play in achieving multiple Sustainable Development Goals (SDGs). Accordingly, global firms in this industry pursue a wide array of sustainability issues. However, it remains unclear as to how leading firms differ from laggard firms in the industry in terms of their overall approach to sustainability and SDGs. To bridge this gap, we conducted in-depth interviews with sixteen experts comprising representatives of global firms, non-government organizations (NGOs), and researchers and academics. First, we identified five sustainability performance criteria—engagement with multi-stakeholder groups (MSGs), measurement of sustainability outcomes, resource commitment by top management, integration of sustainability programs with traditional management systems, and a robust process for the identification of specific sustainability issues or SDGs. Then, we found that leaders and laggards are markedly different in their approaches to pursue these performance criteria.


2020 ◽  
Vol 187 ◽  
pp. 04001
Author(s):  
Ravipat Lapcharoensuk ◽  
Kitticheat Danupattanin ◽  
Chaowarin Kanjanapornprapa ◽  
Tawin Inkawee

This research aimed to study the combination of NIR spectroscopy and machine learning for monitoring chilli sauce adulterated with papaya smoothie. The chilli sauce was produced by the famous community enterprise of chilli sauce processing in Thailand. The ingredients of the chilli sauce consisted of 45% chilli, 25% sugar, 20% garlic, 5% vinegar, and 5% salt. The chilli sauce sample was mixed with ripened papaya (Khaek Dam variety) smoothie with 9 levels from 10 to 90 %w/w. The NIR spectra of pure chilli sauce, papaya smoothie and 9 adulterated chilli sauce samples were recorded using FT-NIR spectrometer in the wavenumber range of 12500 and 4000 cm-1. Three machine learning algorithms were applied to develop a model for monitoring adulterated chilli sauce, including partial least squares regression (PLS), support vector machine (SVM), and backpropagation neural network (BPNN). All model presented performance of prediction in the validation set with R2al = 0.99 while RMSEP of PLS, SVM and BPNN were 1.71, 2.18 and 3.27% w/w respectively. This finding indicated that NIR spectroscopy coupled with machine learning approaches were shown to be an alternative technique to monitor papaya smoothie adulterated in chilli sauce in the global food industry.


2011 ◽  
pp. 398-402 ◽  
Author(s):  
Isuru Wijesekara ◽  
Mahinda Senevirathne ◽  
Yong-Xin Li ◽  
Se-Kwon Kim

2010 ◽  
Vol 19 (3) ◽  
pp. 251-268 ◽  
Author(s):  
RAMNI JAMNADASS ◽  
IAN K DAWSON ◽  
PAUL ANEGBEH ◽  
EBENEZAR ASAAH ◽  
ALAIN ATANGANA ◽  
...  

2020 ◽  
Author(s):  
Nurdeng Deuraseh ◽  
Negara Brunei Darussalam

The halal food industry has received a substantial increase in attention from local authorities in recent years, resulting in the creation of an organisation to oversee the sector, design and develop halal food standards to cater the growing demand of consumers, and ensure that halal food is produced in accordance with instructions in the Quran (‘Kulu Mimma fi al-Ard Halalan Thayyiban’). Based on this demand, Negara Brunei Darussalam, through the Religious Council, has developed a Halal food standard PBD24: 2007. This paper is an attempt to discuss, highlight and analyze the general guidelines, rules and policies of halal food production based on Halal food standard PBD24: 2007, and its contribution to global food quality and safety. It was found that Negara Brunei Darussalam owns a comprehensive standard and law to fulfil the need of local and international halal food industry. Keywords: Halal Food Standard, Negara Brunei Darussalam, Quality and Safety Food.


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