Association pattern among yield and its related attributes for early peas (Pisum sativum L.)

Paper Details

Research Paper 01/03/2020
Views (734)
current_issue_feature_image
publication_file

Association pattern among yield and its related attributes for early peas (Pisum sativum L.)

Muhammad Najeebullah, Mudassar Iqbal, Kashif Nadeem, Muhammad Iqbal, Saeed Ahmad Shah Chishti, Ghazanfar hammad, Rana Husnain Shabbir, Ghulam Nabi, Muhammad Zubair, Zeeshan Qadeer, Umbreen Shahzad
Int. J. Biosci. 16(3), 83-87, March 2020.
Copyright Statement: Copyright 2020; The Author(s).
License: CC BY-NC 4.0

Abstract

A study was conducted in Vegetable Research Institute, Faisalabad, Pakistan during 2017-18 and 2018-19 to estimate the genetic variability and correlation among eight different genotypes of pea (Meteor, 9800-5, Pea-2009, 2001-20, Samrina zard, Olympia, 9200-10 and 2001-40). These accessions were sown in RCBD triplicate. Data was collected on morphological parameters i.e. days to 50% flowering, 100-seed weight, yield per plot, plant height, pods per plant, pod length, seed per pod and pod width. The analysis of genetic variability showed high values in genotypic coefficient of variation (GCV 22.42 & 17.81) for pods per plant in bi-annual study of yield related attributes. Maximum genetic advance (36.76% & 20.87%) was also found for pods per plant among all traits in early pea lines. Positive and highly significant correlation (0.8393 and 0.8846) was found with 100 seed weight and pod width during consecutive years (2017-2019). Maximum heritability was found for Pod length (97.95) and days to 50% flowering (96.64) during sequential years. It is concluded that these attributes could be used as selection criteria for the development of early bearing and high yielding varieties.

Bastianelli D, Grosjean F, Peyronnet C, Duparque M, Regnier JM. 1998. Feeding value of Pea (Pisum sativum L.) chemical composition of different categories of pea. Animal Sciences 67, 609-619.

Burton GW. 1952. Quantitative inheritance in grasses. Proceeding 6th International Grassland. Congress 1, 277-283.

Coyne CJ, McGee RJ, Redden RJ, Ambrose MJ, Furman BJ, Miles CA. 2011. Genetic adjustment to changing climates: Pea, In: Crop adaptation to climate change. Wiley Blackwell Chichester UK.238-250.

Fikreselassie M. 2012. Traits in field pea (Pisum sativum L.) genotypes. Pakistan Journal of Biological Sciences 15, 358-366.

Iqbal M, Bashir I, Iqbal M, Nadeem ALateef K, Chishti SAS, Niaz S. 2015.  Association pattern among yield and its related attributes in Peas (PisumSativum L.). Journal of Agriculture Research, 53(2), 173-177.

Nawab NN, Subhani GM, Mahmood K, Shakil Q, Saeed A. 2008. Genetic variability, correlation and path analysis studies in garden pea (Pisumsativum L.). Journal of Agriculture Research. 46, 333-340.

Phillips DA. 1980. Efficiency of symbiotic nitrogen fixation in legumes. Annual Review of Plant Physiology 31, 29-49.

Reid JB, Ross JJ. 2011. Mendel’s genes: Toward a full molecular characterization. Genetics 189, 3-10.

Singh JD, Singh IP. 2005. Studies on correlation and path analysis in field pea (PisumsativumL.).  National Journal of Plant improvement 1, 59-60.

Steel RGD, Torrie JH, Dicky DA. 1997. Principles and procedures of statistics – A biometrical approach, 3rd ed. McGraw Hill Book International Co, Singapore.

Tiwari G, Lavanya GR. 2012. Genetic variability, character association and component analysis in F4 generation of field pea (Pisum sativum var. arvense L.). Karnataka Journal of Agriculture Scienece 25, 173-175.

Related Articles

Sensory acceptability of gnocchi pasta added with different levels of malunggay (Moringa oleifera) leaves and blue ternate (Clitoria ternatea) flowers

Ralph Justyne B. Bague, James Troyo, Proceso C. Valleser Jr.*, Int. J. Biosci. 28(1), 103-114, January 2026.

Spatio-temporal analysis of vegetation cover and socio-environmental implications in Korhogo (Northern Côte d’Ivoire) from 1990-2020

Adechina Olayossimi*, Konan Kouassi Urbain, Ouattara Amidou, Yao-Kouamé Albert, Int. J. Biosci. 28(1), 94-102, January 2026.

Predicting the habitat suitability of Vitellaria paradoxa under climate change scenarios

Franck Placide Junior Pagny*, Anthelme Gnagbo, Dofoungo Kone, Blaise Kabré, Marie-Solange Tiébré, Int. J. Biosci. 28(1), 73-83, January 2026.

Performance response dynamics of rabbits (Oryctolagus cuniculus) to locally sourced, on-farm feed ingredients during the growing phase: Implications for the institutional rabbit multiplier project

Roel T. Calagui*, Janelle G. Cadiguin, Maricel F. Campańano, Jhaysel G. Rumbaoa, Louis Voltaire A. Pagalilauan, Mary Ann M. Santos, Int. J. Biosci. 28(1), 65-72, January 2026.

Chronopharmacology: Integration of circadian biology in modern pharmacotherapy

Sangram D. Chikane*, Vishal S. Adak, Shrikant R. Borate, Rajkumar V. Shete, Deepak V. Fajage, Int. J. Biosci. 28(1), 56-64, January 2026.

Evaluation of the impact of floristic diversity on the productivity of cocoa-based agroforestry systems in the new cocoa production area: The case of the Biankouma department (Western Côte d’Ivoire)

N'gouran Kobenan Pierre, Zanh Golou Gizele*, Kouadio Kayeli Anaïs Laurence, Kouakou Akoua Tamia Madeleine, N'gou Kessi Abel, Barima Yao Sadaiou Sabas, Int. J. Biosci. 28(1), 44-55, January 2026.

Utilization of locally sourced feed ingredients and their influence on the growth performance of broiler chickens (Gallus gallus domesticus): A study in support of the school’s chicken multiplier project

Roel T. Calagui*, Maricel F. Campańano, Joe Hmer Kyle T. Acorda, Louis Voltaire A. Pagalilauan, Mary Ann M. Santos, Jojo D. Cauilan, John Michael U. Tabil, Int. J. Biosci. 28(1), 35-43, January 2026.