Workpackage number 6: Crop and fruit quality models Start date or start event: 0
Activity Type: RTD/Innovation
Participant ID

UPCT 

INRA 

WU

Person-month per participant

16 

48 

20 


Objectives

  1. Improvement and adaptation of an existing tree/orchard model in order to describe the effects of irrigation water quality, fertigation and RDI strategy on fruit quality and safety. The current model allows predicting the main fruit quality traits at the tree/orchard scale under the influence of climate and cultural practices. The new version of this model will provide a predictive tool that will allow the simulation of the effects of a given irrigation strategy on fruit yield, quality and safety. These outputs are needed for the evaluation and validation of irrigation strategies.
  2. Development of quality models (state description models and quality change models) for the selected product, each with its own specific (major) quality attribute. The models will be calibrated and validated against data obtained in WP3 and WP4.

Description of work

The main task of WP6 is to include the effects of water stress induced by a given irrigation strategy into available crop models and to develop a model that permit the simulation of the post-harvest behaviour of the product. The data obtained from WP3 and WP4 will be used to develop and validate new models, or to improve existing ones.

It is long time recognised that the growing and management conditions during the pre-harvest period may have a marked effect on the quality of horticultural and agricultural products and on the way this quality changes during subsequent post harvest storage. Some studies have evidenced a dependence of post harvest quality parameters on pre-harvest conditions, but only a few information about how this relation works is presently available. To be able to optimise the production taking both the traditional production criteria into consideration (yield, resistance, absence of defects) as well as consumer-oriented attributes of quality (firmness, colour, taste), this relation should be cleared up and modelled.

(Task 6.1) Inclusion of the effects induced by cultural practices (RDI, water quality and fertilisation) into existing tree models (months: 1-24)

The tree model to be developed in this task will be based on two existing models developed by INRA, STICS-3 and ALEXIS. STICS-3 is a generic 1D crop model which has extensively been used and tested, particularly for cereal or forage crops. It will be extended to deal with orchards. ALEXIS is a ‘mean plant’ based crop model dedicated to peach tree, with emphasis on fruit quality. These crop models will be used as tools to analyse the integrated effects of different irrigation strategies. Both will include an effective root sink term.

The ALEXIS simulation model of plant growth and fruit edible quality integrates the influence of climate and crop management. Emphasis will be put in considering (i) within-tree variation and the state variables accounting for the effect of technical operations (e.g., stem water potential depending upon irrigation) and (ii) a profile of fruit quality traits (dry and fresh mass, part of dry mass in the flesh, concentration of four sugars in the flesh, flesh firmness, relationship between soluble solids content and acidity, skin color). Computerization using object-oriented technologies and future improvements will be carried out for making easier the use of the software by different users and its connection to data and various procedures (other models, parameter estimation modulus, etc.).

(Task 6.2) Development of fruit quality models for selected quality attributes (months: 10-36).

The choice of quality models will largely depend on the product at hand. Each specific product will have its own most important quality attribute like firmness, colour, taste (sugars and acids) and flavour. All these attributes can be modelled as a function of storage time for one product or another. The major challenge in this task is to predict the quality at harvest, as a function of the imposed growing conditions. This means that the efforts have to be concentrated on the estimation of fruit status at harvest in terms of pre-harvest conditions. The models known as “state description models” are frequently used to estimate the optimal harvest time (maturity indicators). Including the variability within trees and within orchards will constitute a major part of the quality modelling effort. As such, the interaction with the tree model evaluation and development will require an intensive work. Special attention will be devoted to pinpoint plausible causes and/or carrier (e.g. enzymes and precursor concentration) for the occurring variation.

The project aims at extending/completing the model by (i) up-scaling from tree to orchard, the latter being considered as a set of trees possibly submitted to heterogeneous conditions, (ii) extending the range of fruit traits to diseases susceptibility, by modelling the occurrence of diseases that might be induced by RDI management or the use of inappropriate/unsuitable irrigation water, (iii) relating irrigation practices using indicators of water status variables of the current model,(iv) relating the fertigation and irrigation practices to the status of the quality at harvest.

A plant indicator such as stem diameter variations (see WP2) could be relevant for an accurate management of water for fruit quality. In this case, the work should be based on knowledge gained from WP2 (possibly under the form of a sub model), plus expert knowledge on the water quantities to be applied as function of the indicator value. However, soil indicators such as tensiometers are more widespread in orchards. Here, knowledge gained from WP5 will lead to the integration of a soil compartment, using empirical relationships and/or a simple scheme of the soil/plant system. If possible, plant and soil indicators will be modelled.

The expected products (submodel of tree transpiration, Month 12; submodel of tree photosynthesis, Month 12; submodel of microcrack occurrence on the fruit skin, Month 12; a global model of whole plant reacting to irrigation; Month 24; quality state description models, Month 24 and quality change models, Month 24) will be part of an orchard management tool that will be able to test innovative irrigation decision rules on the basis of multicriteria analysis (fruit quality traits, susceptibility to fungi attacks and water use efficiency) and to limit the range of future experiments and decision rules. WP6 will be developed by INRA, UPCT and WU teams, using the data recorded in the different orchards and pilot farms, and compiled in the WP1 database, whenever the data of WP2, WP3 and WP4 will begin to be available. INRA and UPCT will develop mainly the crop models, while WU will develop the fruit quality model, integrating the quality and safety parameters at harvest and post-harvest stages.


Deliverables:

D10: A simple submodel of tree transpiration adapted to the case study (month 12)

D11: A simple submodel of tree photosynthesis reduction under drought conditions adapted to the case study (month 12)

D12: A submodel of microcrack occurrence on the fruit skin (month 12)

D28: A global model of whole plant reacting to irrigation (month 24).

D29: Quality state description models for the four products under study (month 24)

D30: Quality change models for the four products under study (month 24)


Milestonesand expected result:

Milestones: M6.1 Month 12 The submodels related to the whole tree gas exchanges (transpiration and photosynthesis) should be available for their further integration into the global crop model.

M6.2.Month 24. The availability of the global crop model is needed for its integration into the farm simulator (WP7: Valuation of the impact of change in irrigation strategies on farm functioning trough the farm simulator). The global crop model developed in this WP will constitute the main component of the irrigation farm simulator (WP7).

Results: The expected products (submodel of tree transpiration, Month 12; submodel of tree photosynthesis, Month 12; submodel of microcrack occurrence on the fruit skin, Month 12; a global model of whole plant reacting to irrigation; Month 24; quality state description models, Month 24 and quality change models, Month 24) will be part of an orchard management tool that will be able to test innovative irrigation decision rules on the basis of multicriteria analysis (fruit quality traits, susceptibility to fungi attacks and water use efficiency) and to limit the range of future experiments and decision rules.