The maize database, first of its kind in India, is a central repository for cultivars i.e. hybrids and open pollinated varieties (OPVs) notified for cultivation in India since the inception of All India Coordinated Maize Improvement Project (AICMIP) in 1957. The database includes the information on cultivars developed from public as well as private breeding programmes. Besides, information on registered germplasm is also given. The database carries image gallery showcasing photographs of cobs/standing crop of the public-bred cultivars released after 1993.The database also presents information about adaptability of cultivars, average yield and disease, and insect-pest resistance along with the parental materials used in breeding programmes. Information on 31 descriptors as per Distinctivity, Uniformity and Stability (DUS) tests in respect of parental lines and their hybrids that were filed for protection under "Protection of Plant Varieties and Farmers Rights Act, 2001" (PPVFRAct, 2001) has been supplemented. In addition, the database provides contact information on developers of the notified cultivars thereby facilitating interactions among the members of maize community. The information contained within maize database can be accessed at on-line expert system called maize AGRIdaksh (www.iimr.res.in/maizeexpertsystem/www.agridaksh.iasri.res.in/maize). Information on notified cultivars (1961
Crop yields of major cereal including maize are not increasing at the targeted growth rates to feed the rising demands stemming from increase in the human population. To increase maize grain yield, there should be continuous improvement of cultures which are actively utilized by the plant breeders. Variability in germplasm is always the key to improvement and to assess the extent of variation is never ending process in a plant breeding program. Out of several methods available for assessing the variability, multivariate analysis is one of the most important and widely used methods. In the present study, 27 hybrids (including three checks) were evaluated for yield and yield contributing traits at three different locations during rabi 2013-14. Analysis of variance revealed significant variations among hybrids for all the traits. Based on Principal Component Analysis, 76.81% of the total variance in the data was accounted for by first four principal components (PC). Cluster analysis based on PC grouped the 27 hybrids into two major groups named as A and B. The group A further contained three sub-groups named as A 1 , A 2 , and A 3 with two hybrids falling in each group. Similarly group B contained four subgroups classified as B 1 to B 4 with 2, 7, 5 and 7 hybrids falling in each subgroup respectively. The hybrids falling in two major groups contained more diversity than those falling in subgroups within a group. Selection of hybrids from the different groups would facilitate exploiting significant heterosis. Therefore, multivariate analysis including Principal component analysis followed by cluster analysis could be a reliable approach for assessing the extent of variability on in the germplasm and making its use in a suitable direction.
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