EggDetect Unit, the first non-invasive technology to detect egg fertility pre-incubation and the chicken's gender pre-hatching

Informacje na temat projektu

EDU

Identyfikator umowy o grant: 773801

DOI

10.3030/773801

Projekt został zamknięty

Data podpisania przez KE 12 Maja 2017

Data rozpoczęcia 1 Czerwca 2017

Data zakończenia 30 Września 2017

Finansowanie w ramach

• SOCIETAL CHALLENGES - Food security, sustainable agriculture and forestry, marine, maritime and inland water research, and the bioeconomy

Koszt całkowity

€ 71 429,00

Wkład UE

€ 50 000,00

Koordynowany przez

EGGDETECT LTD
Israel

Periodic Reporting for period 1 - EDU (EggDetect Unit, the first non-invasive technology to detect egg fertility pre-incubation and thechicken's gender pre-hatching)

Okres sprawozdawczy: 2017-06-01 do 2017-09-30

Podsumowanie kontekstu i ogólnych celów projektu

The EggDetect Unit seeks to optimise the incubation process for laying poultry. Currently there is no method for fertility testing when the egg is laid and gender differentiation happens only once the chicks are hatched. Male chicks are not useful either as layers or to raise as meat for consumers. The birth ratio of male to female birds is roughly 50:50. Millions of male birds are culled via maceration or suffocation annually. This is a poor use of resources and creates unnecessary costs on top of the ethical implications.

Prace wykonane od początku projektu do końca okresu sprawozdawczego oraz najważniejsze dotychczasowe rezultaty

Over the course of the feasibility study EggDetect has contacted stake holders and secured sites for pilot trial, contacted interested customers who have expressed intent once results are verified. We have investigated our mvp and created a road map to future value adding features. We have also completed the design for our pilot trial.

Innowacyjność oraz oczekiwany potencjalny wpływ (w tym dotychczasowe znaczenie społeczno-gospodarcze i szersze implikacje społeczne projektu)

EggDetect's EggDetect Unit (EDU) enables non-invasive fertility detection before the eggs are incubated and can predict gender of the egg while still in-ovo with 98% accuracy. Infertile eggs are no longer incubated reducing incubator contamination and eliminating food waste. The EDU removes the need for the mass culling of day old male chicks and instead returns them to the circular economy including the need for fertilised eggs in vaccine production. Further developments include deep learning from data accumulation will help managers with process flow and breeders to see the impact of genetic variation as breeders change.

EDU Schematic