Causal mechanism for determination of grain yield and milling quality of lowland rice

Kozak, Marcin; Singh, Pankaj Kumar; Verma, Med Ram; Hore, D. K.

doi:10.1016/j.fcr.2007.03.010

Cited by 25 publications

(17 citation statements)

References 9 publications

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“…Numerous yield-related traits determine the variation in crop yield at both the genetic level (i.e., the driver of variation is a genetic factor) and the environmental level (i.e., the driver of variation is an environmental factor). An assessment of these yield-related traits is essential for identifying the yield-limiting factors, creating more efficient breeding strategies (Mohammadi et al 2003;Foulkes et al 2007;Tian et al 2011;Zheng et al 2011) and allowing for the recommendation of cultivar and crop management systems (Kozak et al 2007a(Kozak et al , 2007bKozak & Verma 2009;Sadras & Slafer 2012;Slafer et al 2014). These studies were mostly conducted on small grain cereal crops at the genetic (Garcia del Moral et al 1991Moral et al , 2005Mohammadi et al 2003;Lamb et al 2011) and environmental levels (Blue et al 1990;Maman et al 2004;Kozak et al 2007aKozak et al , 2007bEstrada-Campuzano et al 2012;Golba et al 2013).…”

Section: Ontogenetic-based Sequential Path Analysis Of Grain Yield Anmentioning

confidence: 96%

“…An assessment of these yield-related traits is essential for identifying the yield-limiting factors, creating more efficient breeding strategies (Mohammadi et al 2003;Foulkes et al 2007;Tian et al 2011;Zheng et al 2011) and allowing for the recommendation of cultivar and crop management systems (Kozak et al 2007a(Kozak et al , 2007bKozak & Verma 2009;Sadras & Slafer 2012;Slafer et al 2014). These studies were mostly conducted on small grain cereal crops at the genetic (Garcia del Moral et al 1991Moral et al , 2005Mohammadi et al 2003;Lamb et al 2011) and environmental levels (Blue et al 1990;Maman et al 2004;Kozak et al 2007aKozak et al , 2007bEstrada-Campuzano et al 2012;Golba et al 2013). To provide detailed and reliable insights into the complex causal relationships, an ontogenetic-based sequential path analysis that considers the sequential development of yield-related traits was used and proved to be efficient (García del Moral 1991Simane et al 1993;Samonte et al 1998;Board et al 1999;Kozak et al 2007b).…”

Section: Ontogenetic-based Sequential Path Analysis Of Grain Yield Anmentioning

confidence: 96%

“…These studies were mostly conducted on small grain cereal crops at the genetic (Garcia del Moral et al 1991Moral et al , 2005Mohammadi et al 2003;Lamb et al 2011) and environmental levels (Blue et al 1990;Maman et al 2004;Kozak et al 2007aKozak et al , 2007bEstrada-Campuzano et al 2012;Golba et al 2013). To provide detailed and reliable insights into the complex causal relationships, an ontogenetic-based sequential path analysis that considers the sequential development of yield-related traits was used and proved to be efficient (García del Moral 1991Simane et al 1993;Samonte et al 1998;Board et al 1999;Kozak et al 2007b). Dhungana et al (2007) and Lamb et al (2011) used an alternative approach, called structural equation modeling, to assess these complex relationships.…”

Section: Ontogenetic-based Sequential Path Analysis Of Grain Yield Anmentioning

confidence: 98%

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Ontogenetic-based sequential path analysis of grain yield and its related traits in several winter wheat cultivars

Mądry

Studnicki

Rozbicki

et al. 2015

Acta Agriculturae Scandinavica, Section B — Soil & Plant Sc

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Studies that provide representative insights for determining yield through its related traits during the ontogeny of modern cultivars subjected to sources of environmental variation are limited for different crops, including wheat. Most of the empirical evidence on the relationships between the yield of small grain cereal crops and its contributing traits has been obtained under dry or semidry conditions. The aims of this paper were to (1) illustrate how an path analysis can be used to clarify and interpret the relationships between grain yield (GY), yield components, and other yield-related traits of 25 winter wheat cultivars subjected to sources of environmental variation and (2) determine how the yield-related traits contribute to the yield variation. The data used in this analysis were generated from multi-environment trials across wheat-growing areas in Poland. Using Ward's clustering procedure was capable of identifying the most critical predictor traits of the yield components and their contributions to cultivar-focused GY variation. Our findings document, confirm, and improve the basic biological understanding of how to grow modern wheat cultivars for high GY through effectively stimulating the improvement of yield-related traits through the optimization of developmental stagebased agronomic strategies. Our results confirmed empirically that modern European wheat cultivars grown in a temperate climate require favorable conditions, the use of appropriate N fertilizer and growth regulators, and the application of fungicide to protect against leaf diseases and to provide conditions that effectively increase the time to anthesis, the Leaf Area Index per spike at anthesis, and the grain filling duration, and reduce plant height and flag leaf disease severity, thus leading to a high GY. A high yield level is obtained by the performance of preferred yield-related traits that can maintain the three yield components at relatively high levels.

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Section: Ontogenetic-based Sequential Path Analysis Of Grain Yield Anmentioning

confidence: 96%

Section: Ontogenetic-based Sequential Path Analysis Of Grain Yield Anmentioning

confidence: 96%

Section: Ontogenetic-based Sequential Path Analysis Of Grain Yield Anmentioning

confidence: 98%

See 1 more Smart Citation

Ontogenetic-based sequential path analysis of grain yield and its related traits in several winter wheat cultivars

Mądry

Studnicki

Rozbicki

et al. 2015

Acta Agriculturae Scandinavica, Section B — Soil & Plant Sc

View full text Add to dashboard Cite

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“…Cause-effect analysis provides an effective means of partitioning the correlation coefficients into direct and indirect effects of the component characters on yield on the basis of which crop improvement programmes can be logically devised (Kozak et al,2007). Any successful hybridization program for varietals improvement depends mainly on the selection of parents having high variability so that desired character (s) combinations may be selected to improve grain quality and higher grain yield.…”

Section: Introductionmentioning

confidence: 99%

Interrelationship and cause effect analysis among panicle yield attributing traits in lowland Traditional Rice

Chakravorty¹,

Ghosh²

2014

JCEA

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Yield component analysis provides a framework for identifying potentially useful traits for yield improvement. A field experiment was conducted for two consecutive years to evaluate the forty four low land traditional rice cultivars for twenty three panicle yield and its attributing traits during kharif season at the Zonal Adaptive Research Station, Krishnagar, Nadia, West Bengal, India. Significant varietal differences were observed for all the characters. Among the panicle yield attributing traits, number of primary branches per panicle, number of grains on primary branches panicle -1 , number of spikelets on primary branches panicle -1 , grain length, grain breadth, grain thickness, kernel breadth, kernel thickness, 100 grain weight, 100 kernel weight correlated significantly and positively with panicle yield both at the genotypic and phenotypic levels. Results of path analysis showed that the direct positive effect on panicle yield was greatest for number of spikelets on secondary branches panicle -1 (0.998) which is followed by number of grains on secondary branches panicle -1 (0.948), grain length (0.755), and number of spikelets on primary branches panicle -1 (0.625), grain thickness (0.392) and fertility % of spikelets on primary branches panicle -1 (0.378). Few characters like number of primary branches panicle , by number of grains on primary branches panicle -1 and grain breadth showed negative direct effect on panicle yield even though the genotypic correlation coefficients on panicle yield were positive. The study revealed that the direct selection of the above said traits might be rewarding for panicle yield improvement since they revealed a true relationship with the panicle yield.

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“…The increase in genetic potential of rice through improving the above traits, however, has attained the plateau; further improvement is possible only through simultaneous improvement of yield components along with physiological properties. Even though much has been done and published on hill rice with the focus on the genetic divergence (e.g., Ghosh et al 1981;Singh et al 2006) and association of traits (e.g., Seetharaman et al 1973;Kozak et al 2007), studies on genetics of the physiological efficiency are lacking.…”

Section: Introductionmentioning

confidence: 98%

Genetic analysis of panicle and physiological traits in hill rice grown in mid altitudes of northeastern India

et al. 2009

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This paper aims to discover the genetic parameters underlying the physiological efficiency and panicle characters of hill rice plants. In order to improve these characters, it is crucial to learn the nature and magnitude of gene action involved in inheritance of panicle and physiological traits. With this purpose, we combined a line 9 tester analysis of crosses involving local cultivars and indigenous and exotic germplasm grown at the northeastern hill region of India. From the study it follows that number of tillers per hill, number of ear bearing tillers per hill, panicle length, panicle weight, number of grains per panicle, number of filled grains per panicle, pollen fertility, spikelet fertility, leaf area index, total chlorophyll content and harvest index were mainly under the control of nonadditive gene action, while total dry matter accumulation and grain yield per plant were under the control of additive gene action. The genotypes DR 92, Ngoba, IET 16451 and UPR 1425-1-1-4 were identified as superior parents with high performance and significant general combining ability effects. For heterosis breeding six cross combinations, viz.,

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Causal mechanism for determination of grain yield and milling quality of lowland rice

Cited by 25 publications

References 9 publications

Ontogenetic-based sequential path analysis of grain yield and its related traits in several winter wheat cultivars

Ontogenetic-based sequential path analysis of grain yield and its related traits in several winter wheat cultivars

Interrelationship and cause effect analysis among panicle yield attributing traits in lowland Traditional Rice

Genetic analysis of panicle and physiological traits in hill rice grown in mid altitudes of northeastern India

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