Cultivated almond is an important nut crop commercially grown worldwide. The majority of research works carried out on almond fruit has been focused on chemical composition. However, fruit quality is defined by both chemical and physical characteristics, which are still not well documented. Here, we investigated gravimetrical traits of almond fruit in the five following cultivars: 'Ferraduel', 'Ferragnes', 'Fournat de Brezenaud', 'Marcona', and 'Tuono'. The present study was carried out across three different sites in northern Morocco namely Aknoul, Bni Hadifa and Tahar Souk and over two harvest seasons (2015 and 2016). Gravimetrical measurements consisted in: In-hull weight, nut weight, kernel weight, hull percentage, shelling percentage, true density, bulk density, and porosity. The outcomes of ANOVA demonstrated that cultivar, site, harvest season, and their interactions affected significantly almost gravimetrical traits. In fact, hull percentage, kernel bulk density, and both nut true and bulk densities were mainly under genotypic dependency, while harvest season (climatic factor) was the main variability source in kernel weight. Furthermore, site (edaphic factor) was the most important in determining in-hull weight, nut weight, and kernel true density, while shelling percentage, and kernel and nut porosities were controlled jointly by genetic and edaphic factors. Wide variabilities were found between cultivars, sites, and harvest seasons for almost parameters as demonstrated by LSD's test. Almond kernels from our cultivars were very small (cv. 'Tuono'), small (cvs. 'Ferraduel', 'Ferragnes', and 'Marcona'), and medium (cv. 'Fournat de Brezenaud'). Furthermore, corresponding nuts were hard (cvs. 'Fournat d Brezenaud' and 'Tuono') to very hard shelled (cvs. 'Ferraduel', 'Ferragnes', and 'Marcona'). Among sites, fruits harvested from Bni Hadifa performed better in terms of in-hull weight, nut weight, and kernel weight. Whereas, Tahar Souk had the greatest values of hull percentage and shelling percentage. Principal component analysis (PCA) allowed a good discrimination of cultivars, sites, and harvest seasons. The first component was of genetic order along which cultivars were separated, while the second and the third components exerted together an environmental control since they separated sites and harvest seasons, respectively. Significant correlations were highlighted among studied characteristics. The most important ones were modeled through simple regressions and therefore they can be used to predict each other.
