Abstract: κ-casein is one of milk proteins which are very important for milk processing. Genotypes of κ-casein affect milk yield, fat, and protein content. The main factors which affect local Latvian dairy breed milk yield and composition are analyzed in research. Data were collected from 88 Latvian brown and 82 Latvian blue cows in 2015. AA genotype was 0.557 in Latvian brown and 0.232 in Latvian blue breed. BB genotype was 0.034 in Latvian brown and 0.207 in Latvian blue breed. Highest milk yield was observed in Latvian brown (5131.2 ± 172.01 kg), significantly high fat content and fat yield also was in Latvian brown (p < 0.05). Significant differences between κ-casein genotypes were not found in Latvian brown, but highest milk yield (5057 ± 130.23 kg), protein content (3.42 ± 0.03%), and protein yield (171.9 ± 4.34 kg) were with AB genotype. Significantly high fat content was observed in Latvian blue breed with BB genotype (4.29 ± 0.17%) compared with AA genotypes (3.42 ± 0.19). Similar tendency was found in protein content – 3.27 ± 0.16% with BB genotype and 2.59 ± 0.16% with AA genotype (p < 0.05). Milk yield increases by increasing parity. We did not obtain major tendency of changes of milk fat and protein content according parity.
Abstract: The paper presents the results of the molecular
genetics analysis in sports research, with special emphasis to use
genetic information in diagnosing of motoric predispositions in Roma
boys from East Slovakia. The ability and move are the basic
characteristics of all living organisms. The phenotypes are influenced
by a combination of genetic and environmental factors. Genetic tests
differ in principle from the traditional motoric tests, because
the DNA of an individual does not change during life. The aim of
the presented study was to examine motion abilities and to determine
the frequency of ACTN3 (R577X) gene in Roma children. Genotype
data were obtained from 138 Roma and 155 Slovak boys from 7 to 15
years old. Children were investigated on physical performance level
in association with their genotype. Biological material for genetic
analyses comprised samples of buccal swabs. Genotypes were
determined using Real Time High resolution melting PCR method
(Rotor-Gene 6000 Corbett and Light Cycler 480 Roche). The
software allows creating reports of any analysis, where information
of the specific analysis, normalized and differential graphs and many
information of the samples are shown. Roma children of analyzed
group legged to non-Romany children at the same age in all the
compared tests. The % distribution of R and X alleles in Roma
children was different from controls. The frequency of XX genotype
was 9.26%, RX 46.33% and RR was 44.41%. The frequency of XX
genotype was 9.26% which is comparable to a frequency of an Indian
population. Data were analyzed with the ANOVA test.
Abstract: Phelipanche ramosa is the most damaging obligate
flowering parasitic weed on wide species of cultivated plants. The
semi-arid regions of the world are considered the main centers of this
parasitic plant that causes heavy infestation. This is due to its
production of high numbers of seeds (up to 200,000) that remain
viable for extended periods (up to 20 years). In this study, 13
treatments for the control of Phelipanche were carried out, which
included agronomic, chemical, and biological treatments and the use
of resistant plant methods. In 2014, a trial was performed at the
Department of Agriculture, Food and Environment, University of
Foggia (southern Italy), on processing tomato (cv ‘Docet’) grown in
pots filled with soil taken from a field that was heavily infested by P.
ramosa). The tomato seedlings were transplanted on May 8, 2014,
into a sandy-clay soil (USDA). A randomized block design with 3
replicates (pots) was adopted. During the growing cycle of the
tomato, at 70, 75, 81 and 88 days after transplantation, the number of
P. ramosa shoots emerged in each pot was determined. The tomato
fruit were harvested on August 8, 2014, and the quantitative and
qualitative parameters were determined. All of the data were
subjected to analysis of variance (ANOVA) using the JMP software
(SAS Institute Inc. Cary, NC, USA), and for comparisons of means
(Tukey's tests). The data show that each treatment studied did not
provide complete control against P. ramosa. However, the virulence
of the attacks was mitigated by some of the treatments tried: radicon
biostimulant, compost activated with Fusarium, mineral fertilizer
nitrogen, sulfur, enzone, and the resistant tomato genotype. It is
assumed that these effects can be improved by combining some of
these treatments with each other, especially for a gradual and
continuing reduction of the “seed bank” of the parasite in the soil.
Abstract: The small plot experiment was set in 2013 at the RISFLátókép Experimental Farm of the Centre for Agricultural and Applied Economic Sciences of the University of Debrecen, on lime-coated chernozem soil in four replications. The final heights of the maize hybrids were studied at three plant densities (50, 70, and 90 thousand ha-1) and two row spacing (45 and 76cm). During the experiment, we have investigated the development of the final plant heights of five maize hybrids of different vegetation time and genotype: Sarolta, DKC 4025, P 9175, Reseda/P 37M81, and SY Affinity. In the development of the plant heights, the tiller number and the hybrid were the decisive factors. The increasing stock density resulted in significant difference in the plant height values, while the row spacing did not. With the increase of plant density and the length of vegetation time, the heights of the individual plants increased.
Abstract: Analysis and visualization of microarraydata is veryassistantfor biologists and clinicians in the field of diagnosis and treatment of patients. It allows Clinicians to better understand the structure of microarray and facilitates understanding gene expression in cells. However, microarray dataset is a complex data set and has thousands of features and a very small number of observations. This very high dimensional data set often contains some noise, non-useful information and a small number of relevant features for disease or genotype. This paper proposes a non-linear dimensionality reduction algorithm Local Principal Component (LPC) which aims to maps high dimensional data to a lower dimensional space. The reduced data represents the most important variables underlying the original data. Experimental results and comparisons are presented to show the quality of the proposed algorithm. Moreover, experiments also show how this algorithm reduces high dimensional data whilst preserving the neighbourhoods of the points in the low dimensional space as in the high dimensional space.
Abstract: Quantitative trait loci (QTL) experiments have yielded
important biological and biochemical information necessary for
understanding the relationship between genetic markers and
quantitative traits. For many years, most QTL algorithms only
allowed one observation per genotype. Recently, there has been an
increasing demand for QTL algorithms that can accommodate more
than one observation per genotypic distribution. The Bayesian
hierarchical model is very flexible and can easily incorporate this
information into the model. Herein a methodology is presented that
uses a Bayesian hierarchical model to capture the complexity of the
data. Furthermore, the Markov chain Monte Carlo model composition
(MC3) algorithm is used to search and identify important markers. An
extensive simulation study illustrates that the method captures the
true QTL, even under nonnormal noise and up to 6 QTL.
Abstract: Competitive relationships among Bradyrhizobium
japonicum USDA serogroup 123, 122 and 138 were screened versus
the standard commercial soybean variety Williams and two
introductions P1 377578 "671" in a field trial. Displacement of strain
123 by an effective strain should improved N2 fixation. Root nodules
were collected and strain occupancy percentage was determined
using strain specific fluorescent antibodies technique. As anticipated
the strain USDA 123 dominated 92% of nodules due to the high
affinity between the host and the symbiont. This dominance was
consistent and not changed materially either by inoculation practice
or by introducing new strainan. The interrelationship between the
genotype Williams and serogroup 122 & 138 was found very weak
although the cell density of the strain in the rhizosphere area was
equal. On the other hand, the nodule occupancy of genotypes 671 and
166 with rhizobia serogroup 123 was almost diminished to zero. .
The data further exhibited that the genotypes P1 671 and P1 166 have
high affinity to colonize with strains 122 and 138 whereas Williams
was highly promiscuous to strain 123.
Abstract: Evolutionary Programming (EP) represents a
methodology of Evolutionary Algorithms (EA) in which mutation is
considered as a main reproduction operator. This paper presents a
novel EP approach for Artificial Neural Networks (ANN) learning.
The proposed strategy consists of two components: the self-adaptive,
which contains phenotype information and the dynamic, which is
described by genotype. Self-adaptation is achieved by the addition of
a value, called the network weight, which depends on a total number
of hidden layers and an average number of neurons in hidden layers.
The dynamic component changes its value depending on the fitness
of a chromosome, exposed to mutation. Thus, the mutation step size
is controlled by two components, encapsulated in the algorithm,
which adjust it according to the characteristics of a predefined ANN
architecture and the fitness of a particular chromosome. The
comparative analysis of the proposed approach and the classical EP
(Gaussian mutation) showed, that that the significant acceleration of
the evolution process is achieved by using both phenotype and
genotype information in the mutation strategy.