Estimation of broad-sense heritability for grain yield and some agronomic and quality traits of bread wheat (Triticum aestivum L.)

Twenty-five wheat genotypes (Triticum aestivum L.) were grown at three locations (Samsun, Amasya and Tokat) in the Middle Black Sea Region of Turkey in order to estimate the broad-sense heritability for grain yield and some agronomic and quality traits. Estimation of the heritability will help to identify selection parameters in our breeding programs for target environments. The heritability for grain yield, test weight, 1000-kernel weight, Zeleny sedimentation, protein content and plant height were 46.05%, 86.88%, 81.82%, 89.13%, 87.45% and 43.69%, respectively. It was found that Zeleny sedimentation was the least affected trait over environments and followed protein content, test weight and 1000-kernel weight. On the other hand, grain yield and plant height were the most affected traits across environmental conditions

Effects of deficit irrigation on water productivity and maize yields in arid regions of Iran

Deficit irrigation in the Gavkhuni River Basin (GRB),Iran, is an effective method for alleviation of drought impacts on crop yields. Whilst it saves considerable amounts of water, it has little effect on crop yields. The effects of deficit irrigation on grain yield and yield components of maize were studied using two factors [namely, the variety at two levels (704 maize variety with 9354 kg ha -1 yield, and 647 maize variety with 8822 kg ha -1 yield) and irrigation at four levels (control, 100, 80, and 60% of water level use)] for three consecutive years. Significant differences (P≤0.05) were noticeable in grain yield, as well as depth and column of kernel among the irrigation treatments. In addition, the effects of cultivars on grain yield, 1000 kernel weight, number of kernel per ear row, number of kernel per column, and depth of kernels were insignificant. Nevertheless, the effects of irrigation treatments on 1000 kernel weight and number of kernel per ear row were not significant. Based on the results and considering the quantitative characteristics of the crop, it was established that for the deficit irrigating of maize, the 80% irrigation level (i.e. 80% of crop evapotranspiration) is the most advantageous treatment when water is not limited. However, when higher water productivity and the possibility of using the water saved are taken into consideration during severe drought conditions, 60% irrigation level treatment is recommended

Estimates of genetic parameters for grain yield, various yield components and some quality traits in rice (Oryza sativa L.)

A study was conducted during two crop season (Kharif, 2011-12 and 2012-13) for estimating the genetic parameters by involving 10 parents and their 45 F1s in rice crop. The estimates of h2 (overall dominance effects) were positive and significant for days to 50 % flowering (9.11), days to maturity (0.24), plant height (2.95), panicle length1(39), productive tillers per plant (3.22), branches per panicle (5.61), flag leaf area (5.50), 1000-grain weight (0.27), biological yield (7.35) and amylose content (1.03) which indicated dominance of genetic components in F1s crosses. The theoretical value (0.25) of (H2/4H1) for all the traits except kernel length and amylose content indicated the asymmetrical distribution of positive and negative genes in the parents. The proportion of dominant and recessive alleles for panicle length, productive tillers, branches per panicle, 1000 grain weight, biological yield, kernel length and L/B ratio reflected more dominant alleles, whereas for days to 50 % flowering, days to maturity, plant height, grains per panicle, flag leaf area, grain yield, harvest index, kernel breadth, kernel length after cooking, elongation ratio, amylose content and hulling %, reflected more recessive alleles in the parents. The estimates of specific combining ability (SCA) effects revealed that the cross Vallabh Basmati 21 x Pusa 1121 could be an excellent candidate for improving grain yield (1.52**), harvest index (1.86**) and flag leaf area (6.20**) whereas Pusa 1121 x CSR 10 is excellent candidate for panicle length (0.89**) and amylose content (1.54**). The characters showing more than 60 % narrow sense heritability along with positive and significant correlation with each other and also with grain yield could be rewarding for further improvement of yield and quality in rice. Therefore, these parental lines can be used as donors in future by following bi-parental mating and the diallel selective mating system could be the best breeding method in an early segregating generation for improvement in these traits in rice crop

Variance components of combining ability for different morpho-physiological traits for heat tolerance in bread wheat

To estimate the level of heat tolerance for different genotypes of bread wheat with respect to morphological characters under studied grains/ spike, grain weight/spike, grain filling duration (duration between the anthesis stage and the physiological maturity), 1000-kernel weight and grain yield/plant for yield. Physiological traits like relative injury (RI %), chlorophyll content, canopy temperature depression (CTD), were used in present investigation to contribute toward capability of plants to tolerate heat stress of the yield contributing traits during heat stress.The findings of present investigation had clearly explained that influences of environments on morpho physiological characters i.e. grain yield per plant (14886.15) and its attributing traits i.e. spike length (459.7), tillers per plant (622.34), spikelets per spike (278.1), 1000 kernel weight (13262.39), grain weight per spike (177.89) and number of grains per spike (2898.44) in wheat were highly significant and positive. Among the parent and their crosses had handsome amount of variations across the environment. The results of interaction for environments with parents, lines, testers and their crosses with respect to morpho physiological characters in wheat was found significant for some characters while variation was absent for other characters studied. Physiological traits like relative injury per cent, chlorophyll content and CTD were vital parameters to quantify the degree of heat stress to develop tolerant genotypes which is urgent and present need under changing climate scenario

Feature and Region Selection for Visual Learning

Visual learning problems such as object classification and action recognition are typically approached using extensions of the popular bag-of-words (BoW) model. Despite its great success, it is unclear what visual features the BoW model is learning: Which regions in the image or video are used to discriminate among classes? Which are the most discriminative visual words? Answering these questions is fundamental for understanding existing BoW models and inspiring better models for visual recognition. To answer these questions, this paper presents a method for feature selection and region selection in the visual BoW model. This allows for an intermediate visualization of the features and regions that are important for visual learning. The main idea is to assign latent weights to the features or regions, and jointly optimize these latent variables with the parameters of a classifier (e.g., support vector machine). There are four main benefits of our approach: (1) Our approach accommodates non-linear additive kernels such as the popular $\chi^2$ and intersection kernel; (2) our approach is able to handle both regions in images and spatio-temporal regions in videos in a unified way; (3) the feature selection problem is convex, and both problems can be solved using a scalable reduced gradient method; (4) we point out strong connections with multiple kernel learning and multiple instance learning approaches. Experimental results in the PASCAL VOC 2007, MSR Action Dataset II and YouTube illustrate the benefits of our approach

Grain Characteristics, Chemical Composition, and Functional Properties of Rye (Secale cereale L.) As Influenced by Genotype and Harvest Year

Grain characteristic, chemical composition, and functional properties of rye were measured in 19 different cultivars grown in one location in up to 3 years. The cultivars included 8 adapted hybrids, 7 adapted population cultivars, and 4 nonadapted population cultivars. The results showed a significant influence of both harvest year and genotype on grain characteristics, chemical composition, and functional properties of the grain. Multivariate data analysis confirmed that the variations in the data were explained by yearly and genotype differences. Calculations of variance components showed that the variations in plant height, harvest yield, and protein content were mainly due to genotype differences and to a lesser extent to differences among harvest years. The kernel weight, hardness index, and content of dietary fiber components, however, were more strongly influenced by the harvest year than by the genotype. Differences in starch properties measured by falling number (FN), amylograph peak viscosity, and temperature at peak viscosity were more strongly influenced by harvest year. The water absorption was strongly influenced by genotype effects, compared to yearly differences. FN and amylograph peak temperature were positively correlated (r = 0.94). No correlation was found between the water absorption and the relative proportion of water-extractable arabinoxylan (AX) compared to the total AX content. However, the degree of ferulic acid cross-linking showed a negative correlation (r = -0.70) with the water absorption

Stochastic Low-Rank Kernel Learning for Regression

We present a novel approach to learn a kernel-based regression function. It is based on the useof conical combinations of data-based parameterized kernels and on a new stochastic convex optimization procedure of which we establish convergence guarantees. The overall learning procedure has the nice properties that a) the learned conical combination is automatically designed to perform the regression task at hand and b) the updates implicated by the optimization procedure are quite inexpensive. In order to shed light on the appositeness of our learning strategy, we present empirical results from experiments conducted on various benchmark datasets.Comment: International Conference on Machine Learning (ICML'11), Bellevue (Washington) : United States (2011