This report evaluates methods for reconstructing the coefficients of a model that describes the relationship between environmental conditions and the performance of potato genotypes, with performance measured by the weight of storage organs. For each genotype, this relationship is modeled as a linear combination of environmental factors weighted by genotype-specific environmental coefficients. The model incorporates the soil moisture field effect, wich varies both over the growing season and spatially within the field, with the latter captured through a linear combination of basis functions weighted by field effect coefficients. Initially, synthetic environmental data is generated, and fixed field effect and genotype-specific environmental coefficients are established. The model then calculates the expected performance based on these coefficients.

Subsequently, two approaches — a two-step method and a one-step method — are tested to reconstruct the original coefficients using the environmental and performance measurements. The robustness of both methods to noise is evaluated, and the minimum required number of environmental measurement locations within the field, as well as the optimal number of intermediate harvests during the growing season, are determined.
This is important because, once refined and expanded, the model and reconstruction methods can be applied to real multi-environment data to provide insights into how environmental factors influence the growth of different genotypes. Such analyses are important for advancing plant breeding efforts.