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- Author or Editor: C. Kuti x
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In earlier studies the inheritance of chilling tolerance in maize was investigated using the joint scaling test on six genotypes forming a systematic genetic series - P1, P2, F1, F2, B1, B2. The values of some genotypes (P1, P2, F1) were overestimated by the model, while those of the other genotypes (F2, B1, B2) were underestimated. It was thought that this could be due to the effect of the level of heterozygosity in the female parent. The level of heterozygosity of the female parent in the P1, P2, F1 genotypes is 0%, while in the F2, B1, B2 genotypes it is 100%. In addition to the m, [d] and [h] parameters, a new parameter, [fh] (female heterozygosity) was thus introduced. Analysis carried out with the new model confirmed a significant female heterozygosity effect.
The storage of wheat data in computers began in the mid-eighties in Martonvásár, and was accompanied by the development of the first simple programs to assist the data management of routine breeding tasks. The great expansion of breeding materials and the demand for new applications have led to an enormous increase in the number of data and have made data processing increasingly more complicated. Data storage facilities and computer programs reflecting an outdated technological level were unable to keep pace with developments. Data storage and applications had to be redesigned on new lines to create a completely new information system amalgamating know-how from breeding and informatics.The paper introduces an extremely important part of this system: pedigree records, which contain the designations of all the genotypes included in traditional field breeding programmes and in the gene bank, together with crossing data, phenotypes and genomic data.An up-to-date, consistent pedigree register is one of the key components in the breeding information system, without which the maintenance and alteration of the names of plant species (wheat, barley, oats, etc.) and linking them to experiments and experimental quality data would be an extremely complex, time-consuming task. It would be even more difficult to keep track of all the genotypes and the increasingly large numbers of related lines from year to year.In addition to describing the rationale behind the system, details will be given on the tools and conditions required for the establishment of the pedigree records, and the internal and external sources available. Finally, some practical examples will be given of how the Martonvásár wheat breeding information system has been applied.
The widespread use of digitally-controlled measuring and analytical devices and electronic data collectors, all equipped with microprocessors and linked to computers, has made it possible for on-line data collection to become a routine process. A rational combination of two up-to-date techniques, barcodes and digital balance terminals, linked to an average computer background (Kuti et al., 2003), has proved in practice to satisfy the criteria raised for the up-to-date processing of breeding data at low cost. This system is an example of how it is possible to reduce costs while processing data more rapidly and reliably and allowing human resources to be utilised more flexibly and efficiently. The modules (MvLabel, MvSticker, MvWeighing)of the program package developed in Martonvásár for the handling and analysis of the data from plant breeding and crop production experiments can also be used independently for the identification of experimental field units (spikes, rows, plots) and for the online handling of weight measurements and analytical data. They provide a simple solution for the design and printing of labels (self-adhesive or plastic) containing barcodes. They make it easier to retrieve the data recorded by digital balance terminals and store them on hard discs, while also helping to unify and synchronise the various parts of the system using barcode readers to identify the measurement data.
Genebanks are storage facilities designed to maintain the plant genetic resources of crop varieties (and their wild relatives) and to ensure that they are made available and distributed for use by plant breeders, researchers and farmers. The Martonvásár Cereal Genebank (MV-CGB) collection evolved from the working collections of local breeders and consists predominantly of local and regional materials. Established in 1992 by the Agricultural Research Institute of the Hungarian Academy of Sciences (Bedő, 2009), MVCGB with its over 10,000 accessions of the major species (Triticum, Aegilops, Agropyron, Elymus, Thinopyrum, Pseudoroegneria, Secale, Hordeum, Avena, Zea mays), became one of the approx. 80 cereal germplasm collections that exist globally. In Martonvásár breeding is underway on a number of cereal species, and large numbers of genotypes are tested each year in the field and under laboratory conditions. The increasing size of the research programmes assisted by a modern genebank background involve an enormous increase in the quantity of data that must be handled during research activities such as traditional breeding, pre-breeding and organic breeding. A computerized system is of primary importance to synchronize breeding and genebank activities, to monitor the quality and quantity of seed accessions in cold storage, to assist the registration of samples, and to facilitate characterization, regeneration and germplasm distribution.
In recent years an information system has been elaborated and constantly improved in Martonvásár, making it possible to handle the 3–4 million identification, observation, measurement, pedigree and other data generated for a total of almost 100,000 experimental plots each year. The extremely rapid development of biotechnology has made breeders interested in integrating molecular breeding methods into the conventional phenotype-pedigree system. The aim is to improve the competitiveness of breeding programmes through the intensive use of this new technology, with particular emphasis on determining how marker-assisted selection can be utilised. The present paper outlines not only a new data structure introduced to accommodate the new data elements of data categories such as gene sources, primer bank, primer combinations, markers, genes and alleles, but also data management tools and a standalone software interface to combine both molecular and phenotypic data. The integration of the molecular genomic data (GENETECH) with the information from the existing databases: pedigree (PEDIGREE), gene bank (GENEBANK) and germplasm exchange (GERMPEXCHG), ensures that biotechnological data generated at no little cost can be harnessed in ways that are important for breeders in decision-making. This is achieved through: (i) identification and centralization in uniform sources of the molecular data, and their matching with specific phenotypes, with special regard to those of importance for marker-assisted selection, (ii) integration and compliance with existing information system data, (iii) facilitation of decision-making based on the above (e.g. grouping of selection/crossing partners).
The effect of irrigation water on the yield and on individual yield components was examined for 19 durum wheat varieties by continually recording weather data and carrying out measurements on the moisture content, temperature, electrical conductivity and tension of the soil. Dry (rain-fed) and irrigated treatments were included in the experiment, which was carried out in the framework of the EU FP7-244374 DROPS project.During the rainless spring of 2011 the soil moisture content of the non-irrigated area dropped to 21–22 vol% and the effect of drought stress was still felt at harvest. The quantity of irrigation water applied during the growing season ensured normal conditions for generative development and a significant difference could be detected between the yield components in the two treatments. The thousand-kernel weight of the varieties was identical in the dry and irrigated plots, but in response to irrigation there was an increase in the number of grains per ear and the grain weight, and an improvement in fertilisation, resulting in higher yields.
The research institute in Martonvásár is one of the largest agricultural research institutes in Hungary and in Central Europe. For many years now, the accumulated data on the extensive wheat breeding stocks has been handled and analysed using programs developed in the institute. The information system that has been elaborated and constantly improved can be used for keeping records of breeding stock, for planning field and laboratory experiments, for site-plant performance evaluation, for automated data collection, for the rapid evaluation of the results and for effective management of the pedigree, seed exchange and the institute’s cereal gene bank.The demand for the storage of molecular data and their use in breeding has increased parallel with the development of new, PCR-based markers. For this reason, informatics tools (data structure and software) suited to the design of marker-assisted selection experiments and the interpretation of the results have been developed as part of the existing Martonvásár wheat breeding information system. The aim was to link molecular data to the phenotypic information already available in the database and to make the results available to wheat breeders and geneticists.The interpretation of molecular data related to specific genotypes is of assistance in clarifying the genetic background of economically important phenotypic traits, in identifying markers linked to the useful genes or agronomic traits to be found in the genomics database, and in the selection of satisfactory parental partners for breeding. Marker assisted selection coupled with traditional breeding activities enables the breeder to make plant selections based on the presence of target genes. Conventional wheat breeding with the integrated molecular component allows breeders to more accurately and efficiently select defined sets of genes in segregating generations.The molecular data are stored in a relational database, the central element of which is the [DNASource] entity. This is used to collect and store information on gene sources arising during breeding. It is therefore linked both to the phenotypic data stored in the traditional breeding system (measurements, observations, laboratory data) and to the component parts of the new, molecular data structure ([PrimerBank], [Marker], [Allele] and [Gene]).
