IIRB 2022: HIGHLIGHTS

IIRB 2022: HIGHLIGHTS

The major highlight is, as always, the ability to meet with ones peers. Even if the cost of travel to Mons skyrocketed as a result of the issues in the airline industry, just having the chance to meet the people who share your passion is worth its weight in gold alone.

Of the more innovative features of IIRB2022, the introduction of pre-Congress access to Posters was a great introduction. A few emails with questions were even fired off in the week prior the Congress.

As usual, the more immediate highlight where posted to Twitter. This was mainly on the NBR account (nordicbeet), but also on my own account (meran_bioph).

MY HIGHLIGHTS

STORAGE

Presentation 5.7 Eva Maria Molin (AIT): “Microbial factors underlying storability of sugar beet”. Basically, there is something in this. It was found that the fungal and bacterial communities in the soil and on the beet varied between varieties, and this correlated with their storability. Fungus ASV-225 (a yeast used in wine production) was associated with poor storage, and bacteria ASV-649 (a growth promoting bacteria) was associated with good storage.

CANOPY COVER MEASUREMENT WITH DRONE IMAGES

This came up twice: once in a poster, and once in a presentation.

Poster 1.4 J. Arnhold, F. Ispizua, D. Grunwald, H.-J. Koch: “Leaf area index or ground cover: which parameter correlates better with sugar yield affected by row distance?” Their work shows that canopy cover, assessed with a RGB camera on a drone, and using the VARI index, returns a high correlation with final yield. They did have a lot of variability in their treatments, thanks to crop rows spacings at up to 90 cm, but still, looks promising. From a conversation with the authors, they had tried the GLI index as an alternative to VARI, but found VARI to be better.

Presentation 2.3 Lucy Tillier (Univ. of Nottingham): “The impact of canopy architecture on radiation use efficiency and yield potential of sugar beet”. Lucy had also measured canopy cover using RGB images, but did the thresholding in ImageJ, and R!. No standard index was used, just the raw colour channels. I don’t have the full details, but Lucy said that it was really easy to do in R. Yay!

SATELLITE IMAGES FOR YIELD ESTIMATION

Presentation 2.2 Gernot Bodner (BOKU Wien)“Management options to improve drought resilience in sugar beet”. Gernot described a platform he was developing that uses satellite images to compare field conditions, and links it to management practices: seeding time, cover crops, pre-crops and maybe tillage. The lesson is mainly that this is an idea people are chasing so it is probably achievable. His work on which part of the root system draws up water was also very interesting.

OTHER REMOTE IMAGING UPDATES

Presentation 3.1 François Joudelat (ITB): “LITERAL – a light but extensive phenotyping tool for beets”. On-person and fixed cameras for rapid or continual phenotyping, respectively. Mainly interesting to continue to note that Francois is a real leader in this field. The on-person camera also seems pretty neat, cheap, effective (30/sec per plot).

Presentation 3.2 Abel Barreto, Facundo Ispizua (IfZ): “Assessments of relevant leaf diseases in sugar beet variety trials by multispectral UAV imaging and artificial intelligence methods”. Main update was that their models for cercospora seem to be transferable to other leaf diseases, which suggests that they are really measuring necrotic cells.

Presentation 4.8 David Eyland (Sesvanderhave): “Mitigating drought impact through variety improvement”. Success with the thermal drone – cooler varieties under drought conditions = higher yields.

SOIL STRUCTURE AND GROWTH

Presentation 2.1 Heinz-Josef Koch (IfZ): “Effects of different cover crops on soil structure and succeeding young sugar beet under contrasting N fertilisation”. Aggregate stability (+ve correlation) and penetration resistance (-ve correlation) strongly linked to crop yield within a field. This is something that I’m not too surprised about, but I’m not sure we’ve had a study on this. It bodes well for cover crops, regen ag, less tillage. It is also something that we should be able to easily integrate into precision projects.

WEATHER DATA BASED WARNING SYSTEM/ MODELS

Presentation 5.3 Simon Bowen (BBRO): “Development of a Cercospora risk warning system for the UK”. Seems that lots of us are working on these type of systems. The two nice things from this presentation: first, the 6×6 km grid traffic-light warning system looks neat; second, the purpose of the warning system needs to be well communicated – the warning is to go scout, NOT go spray.

RESEARCH NETWORKS

Presentation 3.3 Sebastian Streit (IfZ): “FarmerSpace – a trial field for digital crop protection in sugar beet production”. There is a whole network of high-tech, digital ag, research farms around Germany. The robots in sugar beet farm at Göttingen – FarmerSpace – is but one.

LOW-LIGHT

The issues in the travel industry of Europe, and COVID meant that basically all the people that I wanted to talk to in depth were missing from the congress…

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