Agricultural Research Journal
Open Access
SCOPUS
  • Year: 2025
  • Volume: 62
  • Issue: 4

Participatory Evaluation and Agro-Morphological Characterization of Pea Genotypes in Dry Environments

  • Author:
  • Mohammed Mareai1,*, Mohamad Maqbool2, Tawfiq Al-Omri2
  • Total Page Count: 9
  • Published Online: May 19, 2026
  • Page Number: 399 to 407

1National Genetic Resource Centre, Agricultural Research and Extension Authority, Dhamar-87148, Republic of Yemen

2Central Highlands Research Station, Agricultural Research and Extension Authority, Dhamar-87148, Republic of Yemen

*Corresponding author: mareemohammed88@yahoo.com

Online Published on 19 May, 2026.

Abstract

Pea productivity in Yemen remains low, partly due to the limited field testing of improved varieties under actual farming conditions. This study was conducted to evaluate and characterize both improved and local pea varieties based on their qualitative and quantitative traits, with the aim of promoting their adoption by farmers. Field trials were carried out at research stations and on farmers’ fields using a randomized complete block design (RCBD) with three replications at each location. A total of 29 agro-morphological traits were assessed and described. Analysis of variance (ANOVA) revealed highly significant differences (p ≤ 0.01) among the varieties for key traits such as days to flowering, pod length, biomass, grain yield, and 100-seed weight. The improved variety ‘Yahsb’ recorded the highest yield of 2.7 tons/ha in the Al-Hada district, while the ‘Amran’ variety performed best at the research station. In comparison, the highest yield among local varieties was 1.8 tons/ha across both locations. Cluster analysis showed a 93% genetic similarity among the improved varieties, reflecting strong agreement between farmer evaluations and researcher selections. Based on these findings, several improved varieties have been recommended for cultivation in the studied districts and similar agro-ecological zones. Furthermore, participatory variety evaluation proved to be an effective and economical approach for identifying farmer-preferred varieties, thereby accelerating their adoption and contributing to enhanced pea productivity in Yemen.

Keywords

Cluster Analysis, Evaluation, Phenotypic, Productive Traits