- Crop specialist Horticulture (Roses)
- North American Salesperson - Leamington (Ontario) Canada
- Commercial Manager | Fresh Produce | Kenya
- Technical Sales Agronomist - Switzerland
- International Retail Account Manager Fruit
- (Senior) Sourcing Manager Fruit
- Territory Account Manager - Texas, Colorado, and the Toronto/Niagara area of Canada
- National Development Manager, Bravo(TM) Apples - Australia
- Greenhouse Head Grower and Manager - Canada
- Greenhouse operations manager - Canada
Top 5 -yesterday
- Booming South African blueberry industry eyes Asian markets
- Opportunities in the US market come from the great marketing done by the citrus community
- Almost everybody is happy with the new Tomato Suspension Agreement
- Zirkle Fruit to lay off 300 workers in Prosser, WA
- Polish blueberry season recovering, work force needed for manual harvesting
Top 5 -last week
Top 5 -last month
- Enormous, but strange avocado
- Will Asia Fruit Logistica take place in September? Trade show organization offers participants option in December
- Avocado market expected to tighten in coming weeks
- "India can have its place in the avocado growing industry"
- Potato prices double due to shortage in Europe
Machine learning: The future of fresh-food replenishment
Unlike other products in retail stores, fresh produce usually has a limited shelf life. Stores are always looking for ways to keep rotten produce off the shelves, as the last thing they want is to leave shoppers with a bad image of their company. Using machine learning, a system can automatically regulate stock according to ever changing demand in the store, reducing the amount of food that normally goes to waste when stores overstock a product.
Most retailers use the sales figures from prior years to determine present demand for products. The problem with this method of stocking goods is that it doesn't account for changing preferences or look for possible growth. With machine learning the system can calculate likely demand and make the safest investments and even calculates risks by probing for areas of possible future growth.
The system lessens the chances of products going out of stock. When products run out, shoppers get disgruntled and have to go elsewhere to find it. This can hurt customer loyalty, as shoppers may lose faith in your store if they cannot consistently find what they need.
Incorporating machine learning into your business doesn't even have to be a huge investment. Following the trend of cloud services, machine learning programs are also available using this model. This outsources the computers and the computer work to other companies and offers a bargain and less of a hassle to retailers. It allows them to focus on what they do best, selling.
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Other news in this sector:
- 2019-08-23 Stabilization of Spanish imports of Moroccan fruit and vegetable products
- 2019-08-23 'Availability of cherries was severely restricted'
- 2019-08-23 Phoenix-based grocer focuses on shopper education
- 2019-08-23 Pakistan: Trade gaining momentum at Ghulam Khan border
- 2019-08-23 Botswana looks to Zimbabwe for horti goods
- 2019-08-22 Spanish horticultural exports up by 4.8% in first semester of 2019
- 2019-08-22 Agricultural production in Azerbaijan on the increase
- 2019-08-22 Up quality management and traceability to increase fruit exports from Vietnam
- 2019-08-22 Online grocery shopping still rare in US
- 2019-08-22 Tomato export volumes from Azerbaijan disclosed
- 2019-08-22 South Korean farm goods’ exports growing throughout July
- 2019-08-21 Extreme drought in Central Chile
- 2019-08-21 Costa Rican fruit and vegetable exports to Portugal increase
- 2019-08-21 2000 kilos of peeled onions a week - served to the catering trade
- 2019-08-21 “We found these micro cucumbers in the mountains of South America”
- 2019-08-21 Russia tries to charm Georgia through economics
- 2019-08-21 "Why more companies should follow Mann’s lead on GMO labelling"
- 2019-08-21 Indonesia: Consumer-oriented agricultural imports are growing
- 2019-08-20 US: Horrible weather torments Pennsylvania farmers
- 2019-08-20 Monsoon costs Indian farmers ₹11.66 billion