Understanding cowpea yield: A comprehensive analysis of physiological traits' contribution through path analysis

Ankrumah Emmanuel

Department of Crop Science, Alex Ekwueme Federal University Ndufu-Alike, Ebonyi State, Nigeria.

https://orcid.org/0000-0001-9983-2453

Ogbonna Peter Ejimofor

Department of Crop Science, University of Nigeria Nsukka, Enugu State, Nigeria.

https://orcid.org/0000-0003-4434-7922

Onyia Vincent Nduka

Department of Crop Science, University of Nigeria Nsukka, Enugu State, Nigeria.

https://orcid.org/0009-0004-9446-251X

Omoigui Lucky

Project-Seed System, International Institute of Tropical Agriculture, Kano Station, Sabo Bakin Zuwo Road Kano, Kano State, Nigeria.

Kamara Alpha Yahya

Project-Seed System, International Institute of Tropical Agriculture, Kano Station, Sabo Bakin Zuwo Road Kano, Kano State, Nigeria.

https://orcid.org/0000-0002-1844-2574

Ndifon Elias M’jaika

Department of Crop Science, Alex Ekwueme Federal University Ndufu-Alike, Ebonyi State, Nigeria.

https://orcid.org/0000-0001-6027-4714

DOI: https://doi.org/10.20448/aesr.v12i1.6570

Keywords: Breeding program, Correlation coefficient, Cowpea, Grain yield, Path analysis, Physiological traits, Planting date, Yield partitioning.


Abstract

This study investigates the physiological processes affecting the grain yield of cowpea (Vigna unguiculata), a key protein, vitamin, and mineral source in human diets. Gaining an understanding of these mechanisms can be crucial for developing high-yielding cowpea varieties in breeding programs. A field experiment was conducted with 30 treatments, including three sowing dates (Early August, Late August, Early September) and ten cowpea genotypes (UAM09-1051-1, UAM09-1046-6-1, UAM14-126-L33, IT99K-573-1-1, IT89KD-288, UAM14-126-L6, UAM14-122-17-7, UAM14-123-18-3, UAM14-127-20-1-1, and UAM14-130-20-4). These treatments were arranged in a split-plot design within a Randomized Complete Block Design, replicated three times. Key physiological traits like Leaf Area Index (LAI), Intercepted Photosynthetically Active Radiation (IPAR), Stomatal Conductance, Photosynthetic Rate, Transpiration Rate, and Chlorophyll Content were measured. Data collected were analyzed using correlation and path coefficient methods; the results showed significant positive correlations between grain yield and traits like LAI, stomatal conductance, and photosynthetic rate. In contrast, the transpiration rate negatively correlated with yield. Path analysis revealed that the net photosynthetic rate had the most direct impact on grain yield, highlighting its role in photosynthesis and grain filling. The study suggests that cowpea breeding efforts should focus on improving photosynthetic efficiency and optimizing traits like LAI and stomatal conductance to boost cowpea grain yields.

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