Temperature Predicts the Population of Aceria cajani Chan. (Acari: Eriophyidae) and Efficacy of Insecticides and Acaricides in its Control on Pigeonpea [Cajanus cajan (L) Millsp.]

Pigeonpea (Cajanus cajan L. Millsp.) is an important tropical legume crop. It is also known as red gram, arhar and tur dal and belongs to the Leguminosae family (Ghadge et al., 2008). It is the world’s sixth most important pulse crop, with India contributing more than 70% of the total production (Jorrin et al., 2021).

Fusarium wilt and sterility mosaic disease are two diseases that cause significant yield losses in India (Kaushik et al., 2013). Sterility mosaic disease (SMD) is caused by the pigeonpea sterility mosaic virus (PPSMV), belonging to the emaravirus family and is semi-persistently transmitted by the eriophyid mite, Aceria cajani Chan. (Acari: Eriophyidae) (Seth, 1962; Ghanekar et al., 1992). The SMD-infected plants become stunted and bushy in appearance. Infected plants become partial or completely sterile. Both the disease and the vector are host specific and are also found in a few of its wild relatives (Patil and Kumar, 2015). The infected perennials (perennial grown pigeonpea crops) and volunteer plants (self-sown pigeonpea) both serve as potential sources of the inoculum (Kumar et al., 2007). The mite does not transfer the virus transovarially.

The population of mites, their life cycle and the incidence of disease were observed to be affected by seasonal temperature fluctuations, relative humidity, wind direction, speed and rainfall, etc. (Hill et al., 2014). In the case of viral diseases transmitted by insects and mites, management practices are primarily focused on vectors. So, the aim of the study was to determine the incidence pattern of mites across the different seasons to find the peaks and lows in population of mites. Secondly, we evaluated the efficacy of chemical acaricides, insecticides and entomo-pathogenic fungi formulations against A. cajani.

The population dynamics of A. cajani was monitored in field plots from January 2021 to December 2021. Sampling of mites was done in two field plots. The field studies include one winter crop and one summer crop. The field study experiments were conducted at Tamil Nadu Agriculture University, Coimbatore, India.

Population dynamics of A cajani in field
    
Experiments were conducted on the susceptible cultivar ICP 8863 (Shree Maruti). The seeds were sown in a 100 m² plot by adopting a spacing of 150 x 30 cm. The infected hedgerow method was chosen for the artificial inoculation of disease. The 100 m² plot was divided into five sub plots (20 m²) and a buffer zone of 0.3 meter maintained between subplots. Each sub plot was treated as replication and from each subplot ten plants were selected for data collection. At two-week intervals, mites were sampled and at each sampling, random five trifoliate leaves at different canopy levels were collected in each plant. The leaves were collected and brought back to the laboratory and viewed under a stereo zoom microscope (Magnus 40x) to take a mite count. All stages of mites except (egg) were counted. The weather parameters data collected from the TNAU meteorological observatory located at 2 km from the experimental site.

In the first study plot, sampling was started in January 2021 sown in October 2020 at a pulses research farm in Coimbatore. The sampling of mites was done at fortnightly intervals and continued until the harvest of the crop (up to April 2021). The second study plot was pigeon pea grown in the month of April 2021. In second field study plot infected leaf stapling was adopted as artificial inoculation of disease. Sampling of mites was done at fortnightly intervals in this plot from May 2021 and continued up to December 2021.
 
Acaricides and insecticide efficacy trial on A. cajani
 
Aceria cajani mite colony was established on ICP 8863 (Shree Maruthi), a susceptible cultivar grown in pots (25 x 25 cm) in a greenhouse (plot size 5 x 5 m) by stapling the infected leaves having mites more than ten in number. These mite populations were used for infestation of the new plants. A completely randomized design was organized, having three replications per treatment. Twelve treatments were tested against A. cajani on pigeonpea (var. ICP 8863 (Shree Maruti). At 14 DAP (days after planting), all the seedlings (12 seedlings/ treatment) were infested with A. cajani by attaching leaflets (3 x 3 cm) with 30 mites (all stages except eggs) to the adaxial surface of the young leaves using paper clips. Mites were allowed to develop on these experimental plants for up to 30 days after infestation.

Foliar sprays of various treatments were applied after 30 days after infestation (DAI) using a hand-held pump pressure garden sprayer of 2L capacity (Kishan Kraft). All the pesticide chemicals (commercial products) in the recommended dosage (Table 3) were mixed and made up to 1000 ml of water. For control treatment, only water was applied as spray. Three to four days after treatment, mites were counted using a stereo zoom microscope on the entire plant (Magnus, 40x). The entire plants from the pots were plucked out and counting of mites was done from each trifoliate by detaching it from the plant.
 
Data analysis
 
The basic statistical measures, such as mean, standard deviation and standard error of mean and ANOVA were calculated. Associations between climate variables and mite populations were investigated by using the Pearson correlation coefficient, multiple linear regression and principal component analysis (PCA). In the acaricides and insecticide efficacy trail on A. cajani, the mean mite data per plant was calculated from three replications. The values were converted into arcsine transformation. A Tukey test was conducted to determine significance among means at the 5% probability level. The mean comparison alphabets were generated. All statistical analyses were conducted using SPSS 26.0.

Population dynamics of Aceria cajani
 
The mite populations per trifoliate was varied in all experimental studies, ranging from 15 to 160 mites/ trifoliate. The lowest mean mite populations/trifoliate was recorded in the winter (during December) and the population reached its peak in the summer (March) and in the post monsoon period (October) (Fig 1). In the first study plot from January to April (2021), the lowest mean number of mites was recorded in the first two weeks of January (15.3 mites/ trifoliate) and the peak number of mites was found in the last two weeks of April (159.6 mites/trifoliate) (Fig 1). In the second experimental plot from May to December 2021, the peak population was found in the first two weeks of October (136.0 mites/trifoliate), whereas the low population was recorded in the last two weeks of December (15.0 mites/trifoliate) (Fig 1).



The degree of linear association between mite populations and weather parameters (T_max-Maximum temperature, T_min-Minimum temperature, Rh1-Morning Relative humidity and Rh2-Evening relative humidity), rainfall (mm) and wind speed (km/hr) were explained by correlation. (Table 1).



The mite population exhibited a significant positive correlation with both maximum (r= 0.610, p= 0.002) and minimum temperature (r= 0.762, p<0.001), respectively. The population exhibited a non-significant positive correlation with rainfall (r= 0.028, p= 0.896) and wind speed (r= 0.009, p=0.96) and a non-significant negative correlation with both Rh1 (r= -0.383, p=0.65) and Rh2 (r= -0.033, p=0.87) (Table 1). The significant positive correlation with both maximum and minimum temperature explains that temperature plays a role in the dynamics of the mite population. It was found that mite numbers were too low during the winters and mite numbers were high in the summers.

The correlation between weather parameters also existed, so here principal component analysis (PCA) was used to group the correlated variables into data subsets called principal components, which are uncorrelated to each other. The principal components (PC₁, PC₂ and PC₃) explain the maximum variation (92.67%). PC₁ captures 47.04% variability, whereas PC₂ and PC₃ capture 26.75% and 18.26% variability, respectively. The variables T_max, T_min and wind speed are positioned on the same side axis, whereas least correlated variables like Rh₁, Rh₂ and rainfall lie on the opposite quadrants of the mite density axis. T_max and T_min variables contribute significant variation to the mite population. The length of the vector explains the variance due to that vector, i.e., the longer the vector length, the more the variation is caused by the vector (Fig 2). According to PC₁, maximum and minimum temperature are important variables that influence mite density (Fig 2).



The multiple regression equation developed between the mite and weather variables was mite density/per trifoliate = 0.99 (T_max) + 0.40 (T_min)-0.44 (Rh₁) + 0.36 (Rh₂) + 0.70 (rainfall) - 0.074 (wind speed) and the coefficient of determination (at p<0.001 R₂= 0.80, R = 0.90)

The analysis of variance suggests that individual impact variables on the mite population. The effect of maximum temperature (R₂=37.3, F=13.06, p=0.002), minimum temperature (R₂ =58.1, F=30.49, p=<0.001), morning relative humidity (R₂=14.6, F=3.77, p=0.065) evening relative humidity (R₂=0.01, F=0.024, p=0.878), rainfall (R₂=0.001, F=0.018, p=0.896) and wind speed (R₂=0.09, F=0.002, p=0.965) (Table 2). The minimum temperature was the most important factor, followed by the maximum temperature, were the most significant factors contributing to the variability.   



In this study, it was found that the mite A. cajani population varied throughout the experimental period. Mite population density peaked in the summer (March and April), then declined and again reached a second peak in the post-monsoon season (August to October). The decline in mite population density during the winter may have been caused by low temperatures. The mean temperature during this period was 20°C. Based on this study, climate variables such as temperature (both maximum and minimum) were important variables in contributing to significant variability in mite populations.

The seasonal variation of mean mite densities was consistent with results supported by (Kaushik et al., 2013), who noted that the peak population of A. cajani was observed in April and March whereas (Pallavi et al., 2019) found the highest mite population in May and August. These findings indicate that management is required in the summer and in the post-monsoon period where mite populations reach their peak.

In Kharif crop pest management practices should be done in the post monsoon period (August-October). In Rabi crop, pest management practices should be done in summer. More than 90 per cent of the crop would be lost if infection occurs at the early stage of the crop’s growth (Bhaskaran and Muthiah, 2005). Infection before flowering causes yield losses of up to 95% to 100%; late infections can lead to a yield loss of between 26% and 97% (Kannaiyan et al., 1984). So, management practices should be taken at early stages of crop growth if infection has been established, to prevent further spread of SMD disease and economic damage. The left-over stubbles and ratooning of the crop should be avoided, which acts as a source of infection.
 
Acaricides and insecticides efficacy trial on Aceria cajani
 
The insecticide and acaricide trials on A. cajani found that spiromesifen, propargite, combination of (fenpyroximate + profenophos), fipronil and etoxazole (96%) are effective in reducing the number of mites, followed by diafenthurion, profenophos and dimethoate (86-89%). The entomopathogenic  fungi formulations such as H. thompsonii and B. bassiana were comparatively less effective compared to the chemical formulations. The B. bassiana formulation was least effective compared to other formulations (Table 3).



Acaricides and insecticides are commonly used for the management of vectors transmitting viral diseases (Van et al., 2010; Hoy, 2011; Marcic, 2012). It was found that all synthetic chemicals were effective in reducing mite numbers (80-98 per cent reduction over the control). The EPFs (entomopathogenic fungi products) such as B. basssiana and H. thompsonii were not effective as chemicals.

The chemicals were tested against the mite A. cajani and found that all chemicals reduced the mite up to 71 per cent, increasing the yield (Manjunatha et al., 2012). Rajeshwari et al., (2016) found that fenazaquin (0.1%) spray reduced the population by 81.9 per cent.

Application of synthetic chemicals for management of vectors will be beneficial when it is grown as the sole crop on large farms. The timing of management is also an important factor for managing the vector. Regular monitoring of fields is essential to detect the SMD disease and timely spraying of the chemicals is required, which is unrealistic for the farmers in India.

Multiple sprays at 30, 45 and 60 DAS (Days after sowing) are required to manage the disease. Generally, pigeonpea is grown in marginal lands under rainfed conditions, in such situations, application of synthetic chemicals to manage vector is not economical (Singh et al., 2021).

Finding host plant resistance genes from the diverse germplasm is the most practical way to lessen the losses brought on by disease. To identify the cultivars that yield large yields and have long-lasting resistance to the sterility mosaic disease, a thorough screening of the germplasm should be conducted.

The results from the studies indicate that populations are active throughout the year and reach their peak when environmental factors are conducive. Frequent field scouts should be done from initial stages of the crop growth to detect the disease and timely management practices will reduce the further spread of the disease in the field. All the chemicals tested for the management of mites were effective, whereas entomo pathogenic formulations were not as effective as chemicals.

All authors declared that there is no conflict of interest.