Background: Chlorophyll is the most important pigment in plant which absorbs light and subsequently transfers its energy to drive the photochemical reactions of photosynthesis. The numerical image processing techniques have been widely used in the analysis of leaf characteristics.Methods: The methods based on RGB (Red, Green and Blue) image analysis may emerge as a new and low-cost method for estimation the chlorophyll content. In this work, we use eight RGB vegetation indices as alternative for chlorophyll content estimation. Result: The student t-test showed that all the RGB indices tested are suitable to estimate the chlorophyll content in barley genotypes. In addition, the results which based on the correlation analysis in combination with the values of root mean squared error (RMSE) demonstrate that the very suitable RGB indices are these with high values of correlation coefficient and lowest values of RMSE. Data collected from barley genotypes leaves indicated that digital image processing technology can be a useful and rapid non-destructive method for assessment of chlorophyll content. Among the RGB indexes tested in this study the 100-(2R-B) and RGRI (R/G) are the most promising index to estimate the chlorophyll content in barley genotypes.

The aim of this study was to know the relation between the grain yield and its components in order to identify the most important attributes in grain yield prediction which would serve as a criterion for the selection of genotypes growing under semi-arid conditions. Fifteen genotypes were studied composed of 11 advanced lines, 03 local landraces and 01 introduced genotype used as controls. Analysis of variance, simple linear correlation multiple linear regression, stepwise multiple linear regression, path analysis, principal component analysis and hierarchical clustering analysis were used to evaluate six traits including grain yield, plant height, days to heading, number of grains spike-1, number of spikes m-2 and thousand kernels weight. Analysis of variance showed that genotype effect was significant for the majority of traits studied (p=0.001), advanced line G10 was shown to be most performing (4.723 t ha-1). Simple linear regression revealed that the number of grains spike-1, number of spikes m-2 and thousand kernels weight contributed significantly in grain yield changes (R2=43, 17%). Path analysis showed that the number of grains spike-1, number of spikes m-2 and thousand kernels weight had a direct and significant effect on grain yield. Principal component analysis showed that thousand kernels weight and negative days to heading were most important factors traits in grain yield. According to these results number of grains spike-1 and thousand kernels weight were crucial for the majority of static analysis.

Licensed under a Creative Commons Attribution 4.0 International License Multi-environment trials were conducted in two locations (Algiers and Setif ) during two crop seasons in order to assess the responses of 17 genotype of barley (Hordeum vulgare L.) by evaluation of genotype-by-environment interactions (GEI) on grain yield and determine the stable genotypes. Results showed significant (p <0.001) effects of environment and genotypes and their interaction on grain yield. The genotypes had different behavior conducting to yield variation in the tested locations. So, selection could consider a specific adaptation of the genotypes and their yield stability. The Additive main effects and multiplicative interaction analysis is a useful tool allowing to explore important information on the obtained results; it revealed that 'Plaisant/ charan01' is the most stable genotype followed by 'Barberousse' and 'Barberousse/Chorokhod' , while 'Begonia' and 'Plaisant' were unstable with specific adaptation to Setif location during 2018/19. the cultivar 'Express' presented a high productivity.

Background: Barley (Hordeum vulgare L.) is one of the more important cultivated crops in the Mediterranean region, where drought and high temperatures during the grain filling stage are the main abiotic stresses limiting its production. The aim of this study is to evaluate the effects of the spike type on the grain yield, thousand kernels weight and some grain filling parameters.Methods: The present study was conducted on the experimental site of station ITGC in Setif, Algeria, eight Barley genotypes were tested during two cropping seasons (2017/2018 and 2018/2019) in a randomized block design with 3 replications.Result: The results proved significant effect of genotypes and spike types on the grain filling parameters, but no significant effect of spike type on the thousand kernels weight during the both cropping seasons. In addition, the spike type registered significant effect just during the second cropping season. Among the genotypes with 6 rows spike type the local genotype Fouarra have high grain yield (97.79 Q/ha) with a deviation of 37.57% from the total mean of the genotypes with 6 row spike type. Many studies proved that in 6-row barleys, the magnitude of contribution of grain number in grain yield was higher than contribution of grain weight. The grain growth of genotypes studied follows a sigmoid curve, during the first season (2017-2018) the duration of grain filling ranged between 24 days for Saida 183 and 28 days for Rihane 03, for the group of genotypes with 6 rows. In addition, the duration of grain filling for the 2 row genotypes varied from 24 days for G4 to 28 days for genotype G2. During the second season (2018-2019) and for the genotypes with 6 rows, the duration of the grain filling varied from 21 days for the Saida 183 and 26 days for the genotype Fouarra, for the genotypes with 2 rows the duration of grain filling ranged from 21 days for the genotype G2 to 26 days for the genotype G3. The correlation analysis between the grain filling parameters, GY and TKW demonstrate a significant and positive correlation between TKW and MGW and GFR (r = 0.82* and r = 0.84*, respectively). Overall, the genotype variation in grain filling velocity and duration was responsible for the difference in grain yield and the improvement in grain yield was achieved by the increasing in velocity or duration of grain filling.

Image analysis systems have been increasingly utilized for the assessment of plant growth and health for decades. We used in this study the software Mesurim Pro to evaluate the variation of the leaf reflectance at Red, Green and Blue and the variation of the senescence parameters. The analysis of variance revealed that the reflectance at different wavelengths (Red, Blue and Green) was highly significant genotypes effects (P < 0.001); for this parameter the good genotypes are those we have the lowest values such as G19. In addition, the preferable genotypes were those which have low values for the mean senescence and senescence velocity; based on this raison the best genotype was the introduce genotype G12. The genotypes effect was significant for the grain yield and thousand-kernel weight, for the chlorophyll content and the analysis of variance showed a significant effect of genotypes, the highest values registered by the introduced genotype G5 this one was in the same homogenize group of G2, G4, G8 and G18. The ranking of genotypes based on all parameters suggested that the genotypes G11, G12, G5, G15 and G18, respectively (introduce genotypes) were the ideal genotypes under these conditions.