Correlation Studies of Morpho-physiological Characters with Seed Yield in Rapeseed (Brassica rapa var. Toria)

Rapeseed (Brassica rapa var. Toria) belongs to genera Brassica, species rapa with chromosome number of 2n=20 (Mahendra et al., 2020). It is a short duration, self-pollinated and long day crop. Toria is characterized by hollow, weak stem, shallow roots with less biological yield, but high harvest index. The crop is one of the most popular and widely used oil seed crops among the people of Assam and North-East India. It contains 33-45% oil, 18-36% protein and other important fatty acids like linolenic acid, oleic acid, etc. It is also used as vegetable, edible oil, spices, preservatives, seed meal, fertilizer and feed.  The average area, production and productivity of rapeseed in India during the period from 2017-18 to 2021-22 is 67.30 lakh hectares, 97.96 lakh tones and 14.56 quintal, respectively (Anonymous, 2023). In Assam, the crop accounts for nearly one-third of the oil produced in India, making the state as country’s key edible oilseed producer. The total area under rapeseed in Assam is 2.89 lakh hectares with a total production of 1.86 lakh tones and the productivity is 6.44 quintal per hectare (Anonymous, 2022). In the North-Eastern states, Assam is the highest in terms of area of cultivation of rapeseed and has the potential to increase productivity to great extent (Deka et al., 2018). To fulfil the increasing demand of edible oils, appropriate interventions must be paid for improvement of existing oilseed genotypes, introduction of new species or varieties. The suitable genotype for a particular region has to be identified based on morpho-physiological efficiency and higher productivity. The important morpho-physiological parameters, such as leaf area index (LAI), absolute growth rate (AGR), crop growth rate (CGR), relative growth rate (RGR), net assimilation rate (NAR), specific leaf weight (SLW), total leaf chlorophyll, biomass, source-sink ratio, sink capacity, harvest index (HI) may contribute substantially for boosting up the productivity in rapeseed (Malek et al., 2012 and Mondal et al., 2020). Only a few research works on the existing rapeseed varieties with regard to physiological efficiency has been conducted. Indeed, there is a need to identify the most important morpho-physiological parameters which govern the productivity of rapeseed and to find out the relationships among different morpho-physiological characters and yield attributes with seed yield through correlation studies. Keeping these points in view, the present study was conducted.

The present experiment was carried out at the Instructional-cum-Research (ICR) Farm, Assam Agricultural University, Jorhat-13, Assam, during rabi seasons of 2021-22 and 2022-23. The experimental farm is situated at 26°47 N latitude and 94° 12 E longitudes at an elevation of 86.6 m above mean sea level (MSL). The climate of experimental site of Assam Agricultural University, Jorhat is characterized by subtropical, humid climate with dry summer and cold winter. The soil of the experimental plot was sandy-loam, acidic pH with medium levels of N, P and K. The seeds were collected from the Zonal Research Station, AAU, Shillongani, Nagaon, Assam. The experiment was laid out in randomized block design with 3 replications and the crops were raised following the recommended package of practices. The statistical analysis was done by the method of Panse and Sukhatme (1967). The data of both the years were pooled and correlation of different parameters was analysed with seed yield per plant.
 
Morphological parameters
 
Five numbers of plants (avoiding the boarder rows) were randomly selected from each replication, tagged and all the data related to morpho-physiological parameters, yield attributes and yield were taken from these plants and average values were computed.
       
Plant height was measured at harvest from the ground level upto the tip of the upper most leaf using meter scale. The number of primary branches at harvest was recorded. The number of young, actively growing green leaves was counted from the base to the top of the plant at 60 DAS. Newly emerging underdeveloped young leaves and senesced leaves were avoided. Root volume was measured at harvest by water displacement technique using measuring cylinder (Bohm, 1979).
       
For stomatal index (SI), fresh leaf samples were collected from field and brought to the laboratory. Selected parts of the leaves were pained using light coloured nail polish on both the sides. Then on cello tape was pressed. After pressing the tape for some time, it was removed from the leaf. The cello tape was then put on a slide and observed under a microscope. Micrographs were captured from various regions of the sections using different magnifications through mobile camera. Stomatal density (No. mm^-2 of leaf area) on abaxial and adaxial surfaces of the leaf was counted. Stomatal index was calculated according to the method of Meidner and Mansfield (1968) using the following formula-
   
Where:
SI= Stomatal index.
SD= Stomatal density.
ED= Epidermal pore density.
 
Morpho-physiological growth parameters
 
Absolute growth rate (AGR) was calculated by using the formula given below (Hunt, 1978):
   
Where:
W₁ and W₂ = Total dry weights per plant in g at time T₁ and T₂ respectively.
 
Crop growth rate (CGR) was calculated by the formula given below (Hunt, 1978):
   
Where:
W₁ and W₂ = Whole plant dry weight at time T₁ and T₂ respectively,
r = Ground area in m² on which W₁ and W₂ are recorded.
       
Relative growth rate (RGR) was calculated by the formula given below:
   
Where:
W₁ and W₂ = Total dry weights per plant in g at time T₁ and T₂ respectively.
       
The specific leaf weight (SLW) includes the leaf thickness and it was determined as per the formula of Radford (1967):
         
Leaf area index (LAI) was calculated using the formula of Watson (1952) as follows:           
   
Net assimilation rate (NAR) is the rate of dry weight increase per unit leaf area per unit time. It was calculated by the formula of Radford (1967).
   
Where:
W₁ and W₂  = Total dry weights per plant in g at time T₁ and T₂ respectively.
L₁ and L₂ = Leaf area (dm²) at T₁ and T₂ respectively.
       
Sink capacity was calculated from numbers of siliqua per meter square, seed per pod and individual seed weight using formula as suggested by McGuire and Thurling, (1992). Stover yield was calculated by harvesting all the plants from 1 m² at physiological maturity from each plot and after proper drying seeds were separated and stover yield was recorded and converted into kg ha^-1.
 
Biochemical parameters
 
Leaf chlorophyll content was estimated after extracting by non-maceration method using Dimethyl Sulphoxide (DMSO) (Hiscox and Israelstam, 1979). Leaf proline content was estimated by the methodology of Bates et al., (1973). The nitrate reductase activity (NRA) in vivo was assayed by the method of Saradhambal et al., (1978). The oil extraction was done according to official methods of Januszewska et al., (1999) using soxhlet apparatus. Protein was estimated by using Bradford’s method (1976).
 
Yield  and yield attributing parameters
 
The number siliqua per plant was counted from five tagged plants randomly selected in each replication and average value was calculated. The number of seeds per silique and siliqua length was measured from ten randomly selected siliquae and average values were computed. The number of seed per plant was calculated by multiplying the average number of silique per plant with number of seeds per silique. The seeds from five plants were dried and weighed to record the seed yield per plant.
       
Correlation coefficients were calculated between seed yield and yield components and seed yield with important morpho-physiological parameters following the method of Panse and Sukhatme (1967).

The data for correlation studies of morpho-physiological parameters with seed yield presented in table 1 indicated that number of green leaves per plant, stem diameter, total dry weight, total leaf chlorophyll content, AGR and CGR showed highly significant positive correlation with seed yield while, number of primary branches and SLW exhibited significant positive correlation with seed yield. Total dry weight had highly significant positive correlation with total chlorophyll content, AGR and CGR. Likewise green leaf number showed high positive correlation with total dry weight, total chlorophyll content, CGR and RGR. Stem diameter was found to have high positive correlation with total dry weight, AGR, CGR and RGR.
 

       
The correlation studies of seed yield with yield components presented in table 2 indicated that siliquae per plant, seeds per siliquae, seeds per plant, sink capacity, stover yield and harvest index had high positive significant correlation with seed yield.  It was also observed that silique per plant had significant positive correlation with seed per plant and sink capacity. Seed per siliqua had significant positive correlation with seed per plant, sink capacity and stover yield.
 

       
The findings of Rashid et al., (2010) was also similar with our result who reported that leaf area index (LAI), crop growth rate (CGR) and total plant dry matter accumulation had a positive significant correlation with seed yield in rapeseed (Brassica campestris L). An evaluation of correlation coefficients by Khayat et al., (2012) forwarded the idea that the total dry matter, harvest index, 1000- grain weight, the number of grains per pod, number of pods per plant and plant height had positive significant correlation with grain yield in Brassica napus (canola), which corroborates with the results of our experiment.
       
Ahmadzadeh et al., (2019) also found similar results in rapeseed where they concluded that biomass, number of pods per branch and number of branches had high degree of positive significant correlation and high direct effect on grain yield. Mondal et al., (2020) reported that in high yielding mutants of rapeseed, the seed yield had significant positive correlation with branch number, total dry matter and leaf chlorophyll content which is similar with the results of the present study. Li et al., (2023) reported that plant biomass, siliqua number per plant, and seed yield showed a significant positive correlation with each other which is also same with the results of the present study. 
       
The correlation studies showed a highly positive correlation of different morpho-physiological parameters viz., number of green leaves per plant, stem diameter, total dry weight, total leaf chlorophyll content, AGR and CGR with seed yield. Among the yield attributes, number of siliqua per plant, seeds per silique, seeds per plant, sink capacity, stover yield and harvest index were found to contribute significantly to higher yield in rapeseed. In this context, the above parameters may be regarded as the physiological indices for higher productivity in rapeseed.

The results indicated that number of green leaves per plant, stem diameter, total dry weight, total leaf chlorophyll content, AGR and CGR showed highly significant positive correlation with seed yield, which clearly indicate their contribution towards higher yield in rapeseed. The number of primary branches and SLW exhibited significant positive correlation with seed yield. Among the yield attributes, number of siliqua per plant, seeds per silique, seeds per plant, sink capacity, stover yield and harvest index showed a highly significant positive correlation with the seed yield. However, further detailed research need to be done for a stronger conclusion.

I thank Indian Council of Agriculture Research (ICAR), New Delhi, for Senior Research Fellowship, and Assam Agricultural University, Jorhat to facilitate me to carry out my Ph.D. research work.