Unveiling the Insights: A Comprehensive Overview of InnoVar Project’s VCU Trials

Innovar > News > Unveiling the Insights: A Comprehensive Overview of InnoVar Project’s VCU Trials

We have now finished all the VCU trials of Innovar project. This makes a total of 42 trials for Core bread wheat and 12 Core durum trials, 18 drought and 12 organic trials in the frame of the project. Altogether, a total of 84 Innovar field trials have been completed. During the first two trial seasons, we observed that in some of the environments, the disease pressure was very low and in these, there were no significant differences between the three management treatments performed in the Core trials. Thus, additional trials on Nitrogen management were included during the third season, to determine the interaction between the level of nitrogen and disease not foreseen at the start of the project. Each trial comprised three set of varieties: the first set was common to all trials, the second was common for each ACZ and the last one was site-specific and each variety was tested under 3 fungicide/PGR management regimes: full, optimised and minimal.

From all these trials, many data were collected. These included phenotypic, phenomic, climate and soil data. Phenotypic data covered thirty different phenotypic traits related to crop development and growth, disease and stress incidences, and yield related traits. Additional measurements related to yield components such as biomass and senescence were also recorded by several partners.  Preliminary analysis of data indicated important GxE interactions and highlighted the best or worse adapted varieties to the different agroclimatic zones (ACZ) as well as the main climatic variables responsible for the variety’s behaviour in the ACZ. Phenomic comprised a total of 169 drone flights. Data were collected by the drones through Micasense sensors cameras at 10 different key growing stages. Different vegetation indexes related to photosyntetic activity, biomass development, nitrogen uptake has been obtained. Climate data have been collected through meteo-stations installed in the VCU trial sites. Soil sampling in the different trial sites have also been completed (base line, spatial sampling).  All collected data have been incorporated to the Innovar database which is a valuable outcome of this project, for its use in the frame of the project and in the future by other researchers.

Data already recorded have allowed to perform preliminary analysis regarding genomic predictions. This showed that across ACZs, Pannonian ACZ showed the highest predictive ability for most agronomic traits. Within ACZ and the particular environments, the predictive ability increased in most cases for yield. According to the models a preliminary classification of the varieties according to a High-Performance Low Risk Scale have also been developed. This classification is at the core of the development of the InnoVar App, linked to the InnoVar website and database, that will enable growers to make the most appropriate variety choices based on their farm location, climate and disease risk.

The Innovar trial protocol has incorporated additional treatments compared to conventional VCU trialling to gauge sustainability of the varieties in trial.  In addition, the trial design allows for statistical comparison between low- and high-risk scenarios, for example, with and without fungicide. Its potential to estimate variety’s sustainability traits is being determined with data generated from the core VCU trials. The comparison of the varietal performance across multiple ACZ and growing seasons will also give an indication of their resilience to a range of biotic and abiotic stresses. Preliminary revision of VCU protocols will include DUS/VCU crossover characteristics such as growth habit, ear emergence or plant height. Methods to incorporate traits for sustainability, resilience and DUS/VCU crossovers are being studied, as appropriate into revised VCU protocols.

Overall, the VCU trials and the information we are obtaining from them, will contribute to create a powerful resource for ongoing research for a more efficient use of resources, a better understanding of the crop x environment interactions and the prediction of  the variety’s responses to climate change.

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