QualiTree

QualiTree is a tree-in-orchard model: it takes into account planting distances and their consequences on light interception. It can be used for the orchard scale by considering an "average" tree, pending consideration of the variability of the initial states of the trees, of the vegetation cover between rows, and even of other modalities (mixtures of species in the orchard).

Its initial design focuses on the elaboration of multi-criteria fruit quality and the variability of this quality within the tree. For this reason, QualiTree is an architected model, with an architecture at a level of detail necessary and sufficient for this purpose, which is not that of the FSPM models.

It incorporates a detailed fruit model designed and studied upstream, the tree part not being at the same level of detail in terms of the structures and processes represented. The major modelling choices, in terms of structures and processes, assumptions, analogies, are described in Lescourret et al. (2011: initial version) and Rahmati et al. (2018: version where water processes are made explicit).

It is generic even though it has been mainly used for peach. An adaptation to apple has been made (Pallas et al., 2016).

It is currently an annual-scale model, which works from initial states of the tree organs. Making it perennial is part of our plans, knowing that many states, including the number of fruit and the number of fruit-bearing shoots, are very strongly regulated by the practices of fruit growers done each year (winter pruning, thinning).

It first represented (Lescourret et al., 2011) carbon processes in the tree in addition to fruit quality processes. The light interception sub-model that partly drives these carbon processes is described in Miras-Avalos et al. (2011). Subsequently, the water processes were represented explicitly (Rahmati et al., 2018).

The application publications of QualiTree are mostly about water stress response - we are in the Mediterranean area in Avignon and this is a major issue for the Mediterranean, or for other even more arid areas. This is why we are collaborating with colleagues in southern Spain or Iran (Miras-Avalos et al., 2013a, b; Rahmati et al., 2018).

An evolution of the model is underway on the following points:

• The addition of a soil with carbon, water and nitrogen processes. The Stics soil sub-model has been chosen. We have also designed a sub-model of the effect of nitrogen uptake on tree functions. All this will allow QualiTree to explicitly represent the effect of water and nitrogen inputs on the functioning of the soil-tree-atmosphere system, and also to simulate indicators of ecosystem services related to C, N and water processes. This part has been conceptualised and coded, and we are in the testing and calibration phase by confrontation with data.
• Representation of the influence of pests on the model's functions and the consequences on the yield and quality of fruit and ecosystem services. A first work has been carried out, which couples QualiTree to a model of brown rot epidemiology (Bevacqua et al., 2019). We are continuing to develop this part since 2021 within the Odace project.

• Application to agrivoltaics (coexistence of a crop and photovoltaic panels on the same plot). The reduction of incident radiation in this context required the revisiting of certain assumptions and the addition of certain processes. In particular, the link between the light environment at the time of shoot growth and the growth in leaf size and mass (SLA) was explained. Moreover, by reducing carbon acquisition, agrivoltaic systems accentuate competition for carbon resources, resulting in a more significant physiological decline, which has also been formalised (Perrine Jullion's PhD thesis, other projects in progress).

QualiTree articles

Bevacqua, D., Genard, M., Lescourret, F., Martinetti, D., Vercambre, G., Valsesia, P., & Miras-Avalos, J. M. (2019). Coupling epidemiological and tree growth models to control fungal diseases spread in fruit orchards. Scientific Reports, 9. https://doi.org/8519 10.1038/s41598-019-44898-6

Lescourret, F., Moitrier, N., Valsesia, P., & Genard, M. (2011). QualiTree, a virtual fruit tree to study the management of fruit quality. I. Model development. Trees-Structure and Function, 25(3), 519–530. https://doi.org/10.1007/s00468-010-0531-9

Miras-Avalos, J. M., Alcobendas, R., Alarcon, J. J., Pedrero, F., Valsesia, P., Lescourret, F., & Nicolas, E. (2013a). Combined effects of water stress and fruit thinning on fruit and vegetative growth of a very early-maturing peach cultivar: Assessment by means of a fruit tree model, QualiTree. Irrigation Science, 31(5), 1039–1051. https://doi.org/10.1007/s00271-012-0385-6

Miras-Avalos, J. M., Alcobendas, R., Alarcon, J. J., Valsesia, P., Genard, M., & Nicolas, E. (2013b). Assessment of the water stress effects on peach fruit quality and size using a fruit tree model, QualiTree. Agricultural Water Management, 128, 1–12. https://doi.org/10.1016/j.agwat.2013.06.008

Miras-Avalos, J. M., Egea, G., Nicolas, E., Genard, M., Vercambre, G., Moitrier, N., Valsesia, P., Gonzalez-Real, M. M., Bussi, C., & Lescourret, F. (2011). QualiTree, a virtual fruit tree to study the management of fruit quality. II. Parameterisation for peach, analysis of growth-related processes and agronomic scenarios. Trees-Structure and Function, 25(5), 785–799. https://doi.org/10.1007/s00468-011-0555-9

Pallas, B., Da Silva, D., Valsesia, P., Yang, W. W., Guillaume, O., Lauri, P. E., Vercambre, G., Genard, M., & Costes, E. (2016). Simulation of carbon allocation and organ growth variability in apple tree by connecting architectural and source-sink models. Annals of Botany, 118(2), 317–330. https://doi.org/10.1093/aob/mcw085

Rahmati, M., Miras-Avalos, J. M., Valsesia, P., Lescourret, F., Genard, M., Davarynejad, G. H., Bannayan, M., Azizi, M., & Vercambre, G. (2018). Disentangling the Effects of Water Stress on Carbon Acquisition, Vegetative Growth, and Fruit Quality of Peach Trees by Means of the QualiTree Model. Frontiers in Plant Science, 9. https://doi.org/3 10.3389/fpls.2018.00003

Project leader: Gilles Vercambre