Job offersmore »
- Import Assistant and Operations Assistant - Netherlands
- Farms Director UK - South East
- Agronomist to work abroad
- Export salesperson GERMANY - Barcelona, Spain
- Account Manager Zachtfruit Scandinavië en Duitsland - Netherlands
- International Editor
- Experienced tomato grower - Angola
- Sales Area Managers - Czech Republic, Eastern Europe, Portugal
- Chief Operations Officer - Deerfield (MA) USA
- LED strategic account manager - Netherlands
Top 5 - yesterday
- No news has been published yesterday.
Top 5 - last week
Top 5 - last month
Exchange ratesmore »
"High-tech genetics drives agriculture forward"The requirements of the food security agenda can only be achieved if we can access the right varieties, cultivars or breeds of plants and animals with the genetic capability to meet the demands of producers and consumers. Key to breeding and growing the next generation of crops, is our understanding of what variation is present in crop material and how it is controlled. These areas of science are developing at an ever-increasing pace, with a need for all involved to keep up to speed with advances.
With more than 3,000 attendees, over a hundred workshops and thousands of posters, the Plant and Animal Genomes (PAG) conference, held each January in San Diego (US), is one of the largest scientific gatherings for the agriculture sector. Just returned from PAG XXVI, scientists from the Genetics, Genomics and Breeding Department at NIAB EMR reflect on the highlights of the meeting, and how recent breakthroughs can be applied to horticultural research.
Ed Buckler from Cornell University (US) plenary talk has been unanimously hailed as a high point in the conference. As noted by Dr Matt Clark, recently appointed at NIAB EMR to lead our technology development programme, “Ed Buckler outlined the four ages of agricultural breeding, each faster and better: (1) Best-to-best breeding- intuitive selection of animals and plants with the best traits for breeding. (2) Genetics- design of optimised breeding crosses, and with DNA technology marker assisted selection. (3) Genomic selection- training computer models using dense genotyping and phenotyping data to predict breeding values based only on sparse, quick and cheap genotyping. (4) Genome editing– builds upon genomic selection by selecting for predicted optimised genomes, but adding gene editing technologies to changes sets of single alleles rather select large genomic blocks (with their intrinsic risk of linkage drag).”
The recent ruling on genome editing by the court of justice of the European Union is particularly relevant to the fourth technology in Buckler’s talk. Matt also commented, “Bruce Whitlaw (Roslin, UK) described how genomic selection has already revolutionised animal breeding (where it was adopted early, especially in dairy cattle), and how genome editing can be used with genomic selection to increase genetic breeding values even faster, and rapidly create breeds of disease resistant animals.”
Less nitrogen, lowering agriculture inputs
Ed Buckler also spoke of his vision for using renewable power at source to create nitrogen fertilisers (~50% of agricultural energy input) and thereby store the energy from fluctuating wind and solar power close to their point of use. Gloria Coruzzi (NYU, USA) in another plenary talk also demonstrated how crops differ in nitrogen efficiencies, then described her lab’s detailed models of how plants change their chemistry and the genes used in response to the addition of nitrogen in only minutes.
Dr Richard Harrison, Head of the NIAB EMR’s Genetics, Genomics and Breeding Department, also mentioned Liang Dong’s plenary talk as, “very relevant to the work we are carrying at NIAB EMR, highlighting the opportunity for the use of inexpensive and high-throughput sensors and phenotyping technologies. At NIAB EMR we are making tremendous strides in these areas which are combined with our expertise in data processing and image analysis. The use of machine learning approaches for the interpretation is pervasive and will revolutionise the area of applied plant science. Whether it is through the prediction of host range of a pathogen, the automated classification of healthy and diseased tissues, the identification of pest species in mixed samples of autonomously acquired images, machine learning approaches, coupled with advanced phenotyping approaches, are already adding support to many applied areas of horticultural science. For several years now NIAB EMR has led a range of BBSRC and Innovate UK projects that have at their heart machine learning approaches.”
Focussing on horticultural crops, NIAB EMR’s apple breeder Amanda Karkstrom commented, “Plant breeding for disease resistance has traditionally utilised single or multiple resistance genes when developing new varieties with improved resistance. In their talks Marie Wolters from Wageningen University & Research and Johannes Fahrentrapp from Zurich University of Applied Sciences presented work where they instead have identified and silenced susceptibility genes in Solanaceous crops as an alternative method to improve resistance to diseases such as potato late blight (Phytophthora infestans), tomato powdery mildew (Oidium neolycopersici) and Botrytis cinerea. Susceptibility genes are host genes coding for proteins that are necessary for a pathogen to successfully infect its host-disrupted or low-functional variants of such genes therefore leads to improved resistance. Genes conferring susceptibility to powdery mildew in apple and wild strawberry have been identified and there are potentially genes with similar functions in other horticultural host pathogen systems. Allelic variation within these genes could therefore be exploited to breed new varieties with durable resistance.”
When used independently, each of these advances will create incremental improvements to varieties being bred in five years’ time. When combined, these technologies have the power to drive to whole of food security forward – and cut fruit breeding from a lifetime’s work, to produce a variety, down to a handful of years.
Source: NIAB EMR
Publication date: 1/31/2018
Other news in this sector: