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Autism spectrum disorders (ASDs) comprise a distinct entity of neurodevelopmental disorders with a strong genetic component. Despite the identification of several candidate genes and causative genomic copy number variations (CNVs), the majority of ASD cases still remain unresolved. We have applied microarray-based comparative genomic hybridization (array-CGH) using Agilent 400K custom array in the first Cyprus population screening for identification of ASD-associated CNVs. A cohort of 50 ASD patients (G1), their parents (G2), 50 ethnically matched normal controls (G3), and 80 normal individuals having children with various developmental and neurological conditions (G4) were tested. As a result, 14 patients were found to carry 20 potentially causative aberrations, two of which were de novo. Comparison of the four population groups revealed an increased rate of rare disease-associated variants in normal parents of children with autism. The above data provided additional evidence, supporting the complexity of ASD aetiology in comparison to other developmental disorders involving cognitive impairment. Furthermore, we have demonstrated the rationale of a more targeted approach combining accurate clinical description with high-resolution population-oriented genomic screening for defining the role of CNVs in autism and identifying meaningful associations on the molecular level.

Quantifying evapotranspiration and drainage losses is essential for improving irrigation efficiency. The FAO-56 is the most popular method for computing crop evapotranspiration. There is, however, a need for locally derived crop coefficients (Kc) with a high temporal resolution to reduce errors in the water balance. The aim of this paper is to introduce a dynamic Kc approach, based on Leaf Area Index (LAI) observations, for improving water balance computations. Soil moisture and meteorological data were collected in a terraced nectarine (Prunus persica var. nucipersica) orchard in Cyprus, from 22 March 2019 to 18 November 2021. The Kc was derived as a function of the canopy cover fraction (c), from biweekly in situ LAI measurements. The use of a dynamic Kc resulted in Kc estimates with a bias of 17 mm and a mean absolute error of 0.8 mm. Evapotranspiration (ET) ranged from 41% of the rainfall (P) and irrigation (I) in the wet year (2019) to 57% of P + I in the dry year (2021). Drainage losses from irrigation (DR_I) were 44% of the total irrigation. The irrigation efficiency in the nectarine field could be improved by reducing irrigation amounts and increasing the irrigation frequency. Future studies should focus on improving the dynamic Kc approach by linking LAI field observations with remote sensing observations and by adding ground cover observations.

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