Seed Production in Birdsfoot Trefoil (Lotus Corniculatus L.) PDF Download
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Author: Qingfeng Li
Publisher:
ISBN:
Category : Lotus corniculatus
Languages : en
Pages : 350
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Book Description
Author: Qingfeng Li
Publisher:
ISBN:
Category : Lotus corniculatus
Languages : en
Pages : 350
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Book Description
Author: John Earl Esworthy Winch
Publisher:
ISBN:
Category : Lotus corniculatus
Languages : en
Pages : 278
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Book Description
Author: Alejandro Jose Peralta Ansorena
Publisher:
ISBN:
Category :
Languages : en
Pages : 138
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Book Description
Author: Supansani Supanjani
Publisher:
ISBN:
Category : Lotus corniculatus
Languages : en
Pages : 234
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Book Description
Author:
Publisher:
ISBN:
Category : Forage plants
Languages : en
Pages : 28
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Book Description
Author: United States. Agricultural Research Service. Crops Research Division
Publisher:
ISBN:
Category : Big trefoil
Languages : en
Pages : 16
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Book Description
Author: Richard Marwood Shibles
Publisher:
ISBN:
Category : Lotus
Languages : en
Pages : 180
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Book Description
Author: Lance Edison Woods
Publisher:
ISBN:
Category : Lotus
Languages : en
Pages : 260
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Book Description
Author: Mark Andrew Hughes
Publisher:
ISBN:
Category : Lotus
Languages : en
Pages : 84
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Author: Juan Carlos Bresciani
Publisher:
ISBN:
Category : Lotus
Languages : en
Pages : 96
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Book Description
In the last 30 years, birdsfoot trefoil (Lotus corniculatus L.) has been recognized as a great potential source of forage. Since the 1930's, many studies have been reported in relation to birdsfoot trefoil characteristics, including some directly related with the association between seed yield and its components. The purpose of this study was to evaluate six seed yield components on 26 genotypes of birdsfoot trefoil. This information was used to estimate the seed yield based on measurement of the components, to study associations among the characteristics, to determine variability in seed yield, and to estimate the usefulness of each characteristic in improving seed yield potential. Seed yield components measured in this experiment were number of clusters per plant, number of flowers per cluster, number of pods per cluster, number of seeds per pod, seed weight, number of barren stalks per plant, and seed yield. The experiment consisted of a randomized block design with three replications. Each replication contained two plants of each genotype. Based on the previously measured components, theoretical yields were calculated in order to evaluate the sampling techniques employed and the selection of characteristics. The degree of association among the characteristics was measured by means of simple correlation coefficients. Variability of seed yield due to variations in its components was analyzed by regression analysis. With the simple regression coefficients obtained in this analysis, two predictive methods of estimating seed yield were calculated and compared against the actual seed yield. The usefulness of each seed yield component for future breeding programs involving seed yield improvement was considered. From the data presented in this study it is concluded that seed yield of individual clones can be estimated by the use of its components. Theoretical yields calculated from these estimates were not significantly different from the actual seed yield. Associations between characteristics and seed yield were significant for number of clusters per plant and number of pods per cluster at the 1 percent level of probability and for number of seeds per pod at the 5 percent level of probability. Clusters per plant and pods per cluster showed the greatest influence on seed yield, accounting for 60.49 percent of the variation in seed yield when these two characteristics were considered together. Both characteristics were equally useful in predicting seed yield. Predicted yield based on clusters per plant and pods per cluster did not show significant differences with harvested seed yield.
