Research Article

Assessment of Extension Interventions for Management of PBW for Enhancing Cotton Production through Frontline Demonstrations among Cotton Growers in Khammam District of Telangana

B. Raja Madhu Shekar, J. Hemanth Kumar, K. Ravikumar, V. Chaitanya and R. Uma Reddy

  • Page No:  1471 - 1481
  • Published online: 22 Dec 2022
  • DOI : HTTPS://DOI.ORG/10.23910/1.2022.3286

  • Abstract
  •  madhushekar80@gmail.com

Frontline Demonstrations were conducted at Krishi Vigyan Kendra, Wyra, Khammam district, Telangana, India during kharif (June–December) from 2019, 2020 and 2021 in different villages of Khammam district. Total 30 demonstrations were laid out on farmers’ fields in the district. The main objective was management of PBW with various technological interventions. The study revealed that 70.00% of the respondents had high school or above education, 46.67% of the respondents had more than 10 years of experience in farming, 100.00% gap was observed on use of pheromone traps and Trichogamma cards. The average yield recorded was 2207 kg ha-1 in demonstration plot, a 22.75% increase over farmer’s practice (1808 kg ha-1). The technology gap under 3 year FLD programme was 1043 kg ha-1,extension gapwas 399 kg ha-1 with a technology index of 32.09%. The demonstrated plots gave higher gross returns, net return with higher benefit cost ratio when compared to farmer’s practice. In present study efforts were also made to study the impact of FLDs on horizontal spread which increased by 221.42%, adoption levels by 130.60%. The study also revealed that there was significant increase in knowledge level of the farmers due to frontline demonstrations, a significant and positive relationship existed between age of the respondent, education, farm size, farming experience, trainings received and extension contacts with yield of cotton.

Keywords :   Cotton, frontline demonstrations, gross returns, net returns, yield

  • INTRODUCTION

    Cotton (Gossypium hirustum L.) is the most prominent commercially cultivated fibre crop of India after jute producing natural fibre, fuel and edible oil, playing an important role in Indian economy (Prasad et al., 2018) grown in India under diverse agro climatic conditions, varying from 8°−32° N latitude and 70°−80° E longitude (Ramprasad, 2022). It is a perennial semi−shrub grown as an annual crop both in tropical and warm temperate regions (Rahman et al., 2012, Chakravarthy et al., 2012, Sushila et al., 2015) for domestic consumption and export needs of 111 countries in the world hence called “King of Fibres” or “White Gold”. India is the largest producer of cotton in the world accounting for about 22% of the world’s production. It is cultivated in an area of 123.50 l ha in India, with an output of 340.62 l bales (170 kg bale-1) and productivity of 469 kg ha-1 (lint) against the world average yield of 787 kg ha-1 (Anonymous, 2021–22). In Telangana, it occupies an area of 20.51 l ha with a production of 65.87 lakh bales with the productivity of 546 kg ha-1 (Anonymous, 2021–22).

    In India area under cotton cultivation is more than the world, but productivity is low, major yield–limiting factors for low productivity are attack of insect pests in almost all cotton growing countries (Luttrell et al., 1994, Hladik et al., 2014). Cotton crop harboured 1326 insect-species from sowing to maturity in all cotton growing areas of the world (Hargreaves, 1948, Atwal, 2004) and 162 species have been reported on cotton crop in India alone (Kranthi et al., 2002, Puri et al., 1999, Chavan et al., 2010), of which 24 species have attained pest status (Sundramurthy and Chitra, 1992, Kannan et al.,2004). The introduction of Bacillus. thuringiensis (Bt) reduced the problem of bollworms (Edge et al., 2001, Shelton et al., 2002, Sharma and Pampapathy et al., 2006). Bt-Cotton cultivation occupied a major share (>90%) in India (Hofs et al., 2004, Carrière et al., 2015). Among the array of insects, the bollworms (Dhurua and Gujar 2011, Mounica and Goverdhan, 2013) viz., Pink bollworm (PBW), Pectinophora gossypiella (Saunders) pose greater threat to cotton production (Ghosh, 2001, Kranthi, 2015).

    In recent years’ heavy incidence of PBW (Dhawan et al., 1988) in Bt cotton lead to reduction in production and productivity. The survival rate of Pink Boll Worm larvae in Bt II cotton hybrids showed progressive increase (Naik et al., 2018, Biradar and Venilla, 2008). Its incidence goes unnoticed to the farmers since young larvae enter the bolls in developing stages and remains inside by feeding on seeds (Ippolito et al., 2015). Its effect will be seen only when bad opened bolls with damaged seeds were found at harvesting stage (Simwat and Sidhu, 1982).

    The FLD’s are important in transfer of latest technologies, package of practices in totality to farmers (Tankodara et al., 2018, Hiremath and Hilli, 2012) and main objective is demonstration of proven crop production technologies (Choudhary and Suri, 2014, Kumar et al., 2020, Madhushekar et al., 2022) and to introduce suitable agriculture practices on large-scale under real-farming situations (Patel et al., 2013, Kushawah et al., 2016, Meena and Singh, 2019) in different agro-climatic regions accompanied with organizing extension programmes for horizontal dissemination of technologies (Madhushekar et al., 2021, Venkatarajkumar et al., 2020, Singh et al., 2018). FLD’s help in changing the scientific treatment by seeing and believing principle to have better impact (Singh et al., 2019, Singh et al., 2020). In view of above facts, present study was initiated to assess the impact of Extension Interventions on management of PBW for Enhancing Cotton Production through Frontline demonstrations among Cotton farmers of Khammam dist.


  • MATERIALS AND METHODS

    KVK Wyra has conducted Front Line Demonstrations in 30 locations under real farming situations from 2019, 2020 and 2021 during kharif (June–December) in different villages located in different blocks under KVK in Khammam district. FLDs were conducted along with check plot and they were taken into consideration for the study to find out the impact of extension interventions on management of PBW. Each demonstration is conducted in an area of 0.4 ha along with farmer’s practice or check consisting of 0.4 ha with improved technologies for monitoring of PBW such as Deep summer ploughing, Timely sowing (Sowing after receiving more than 60mm rainfall), Sowing of non-Bt as refugee crop, Growing of trap crops, Weekly monitoring, Installation of pheromone traps, Collection and destruction of rosette flowers, Damaged bolls, Spraying of neem oil and need based insecticides, Release of Trichogramma cards soon after appearance of bollworms, Termination of crop by December. The FLDs neighbouring plot acted as farmers practice. The detailed recommended practices demonstrated in demo plot and farmer’s practices are given in Table 2. The differences in the packages were in line with the findings of Singh et al. (2019), Shah et al. (2019) and Morwal et al. (2018).

    Data expenditure incurred by the farmer (Farmer’s practice) and expenditure of demonstration plots were collected and analyzed. Gross income was calculated based on local market prices of cotton and net income by subtracting the total cost of cultivation from gross income. B:C ratio was computed by dividing gross returns with cost of cultivation in Cotton. To estimate the technology gap, extension gap and technology index the following formula as mentioned below were used as suggested by Samui et al. (2000).

    percent Increase in yield=(Demonstration yield-farmers yield)/(Farmers yield)×100                           …………..(1)

    Technology Gap=Pi (Potential Yield)-Di (Demonstration Yield)                                                            …………..(2)

    Extension Gap=Di (Demonstration Yield)-Fi (Farmers yield)                                                           ……………..(3)

    Technology index=(Potential yield-Demonstration yield )/( Potential yield)×100                                  ……………(4)

    The data on adoption and horizontal spread of technologies were collected from selected farmers with the help of schedule. Data were subjected to suitable statistical methods. The following formulae were used to assess the impact on different parameters of cotton.

    Impact of yield=(Yield of demonstration plot- Yield of control plot)/(Yield of control plot)×100          ……….(5)

    Impact on adoption (percentage change)=(Number of adopters after demonstration-Number of adopters before demonstration/Numbers of adopters before demonstration)×100                                                              ………(6)

    Impact on horizontal Spread (percentage change)=(After area (ha)-Before area (ha)/Before area)×100      ……..(7)

    2.1.  Correlation analysis

    Pearson’s correlation coefficient when applied to a sample is commonly represented by the letter “r” and may be referred as the sample correlation coefficient or the sample Pearson correlation coefficient. It is used with two variables (independent and dependent) to determine a relationship/association.

    2.2.  Paired t-test

    A paired t-test is used to compare two population means where you have two samples in which observations in one sample can be paired with observations in the other sample.


  • RESULTS AND DISCUSSION

    3.1.  Socio-economic characteristics of respondents

    The results from the study conducted on the frontline demonstrations on Management of Pink boll worm in cotton are enumerated, profile characteristics of the selected cotton farmers are given below (Table 1).


    It can be inferred from Table 1 that nearly 63.34% of the respondents were in the middle age group, an active and agile group for doing agricultural activities, 70.00% of the respondents had high school or above education levels, with nearly three quarters of the respondents had 2.5 a or above farm size (73.33%), 56.67% of the farmers had 5 a or less than that area under cotton cultivation, 46.67% of the respondents had more than 10 years of experience in farming, 40.00% of the farmers had both Agriculture and horticulture as their farming systems, 43.33% of the respondents had membership in one organization, 50.00% of the farmers participated in one training conducted in Cotton by KVK and other extension agencies, 46.67% of the farmers had medium annual income, 40.00% of the farmers had high extension contacts which shows that KVK is well connected with the farmers in the district. The results are in tune with the findings of Madhushekar et al. (2021) who reported similar findings with regard to education and extension contacts whereas Bhattu et al. (2015), Shankara et al. (2014), Islam and Nath (2015) reported similar findings on trainings received by selected respondents.

    3.2.  Recommended package of practices

    The Gap between the Recommended practice and farmer’s practice details were given in Table 2.


    It shows that all the FLD farmers fully adopted the recommended package of practices with slight modifications as per their situation where as non-FLD farmers were unable to adopt the practices. Incorporation of stubbles was taken by most of the FLD farmers and non-FLD with implements like cultivator creating a gap of 83.34%. Awareness on deep summer ploughing and community sowing was observed there the gap is below 30.00%. Unavailability, limited supply of pheromone traps, ignorance on part of the farmers on pheromone traps usage resulted in 100.00% gap. Indiscriminate spraying of the insecticides was observed among non-FLD farmers compared to FLD farmers who monitored the pest and used prophylactic sprays with Neem oil, hence a gap of 43.34%. Release of Trichogramma cards was practiced by FLD farmers only, a gap of 100.00% was observed.

    Spraying of need based pesticides depending on pest incidence and load showed 70.00% gap, Non-FLD farmers didn’t practice the recommended interventions which are critical for pest management and these directly affect the yield. Farmers used high doses of a particular type and others are either applied or not applied fully, partial adoption is followed among Non-FLD farmers, Kundu et al., 2022 also observed similar differences in pest management. The above result of differences in recommended practices to farmers practice are in unity with the findings of Madhushekar et al. (2021), Hiremath et al. (2007), Balai et al. (2021), Singh et al. (2008) and Afzal et al. (2013) who also reported similar findings in paddy, Onion, Mustard, Cotton and Mustard respectively

    3.3.  Economic parameters

    Economic indicators i.e. gross expenditure, gross returns, net returns and BC ratio of Front Line Demonstrations are presented in Table 3.


    The data clearly envisages that net returns from the demonstration plot were substantially higher than control plot during all the years of demonstration. Average net returns from demonstration plot were Rs. 69,140.17 ha-1 compared to Rs. 41,613.83 ha-1 in control. The average gross expenditure from the demonstration plot was recorded as Rs. 64,546.67 ha-1 compared to Rs. 67,744.67 ha-1 in control. The average gross returns from the demonstration plot were Rs. 1,33,686.83 ha-1 compared to Rs. 1,09,358.50 ha-1 in control plots. The results are in tune with the findings of Kundu et al. (2022), Singh et al. (2018) observed B:C ratio in groundnut and mustard higher in demo plots than in farmer’s practice. Hiremath et al. (2009) observed additional net returns because of FLDs in onion.

    Economic analysis of the yield performance revealed from Table 3 showed that benefit cost ratio of demonstration plots was observed to be significantly higher than farmer’s practice. The benefit cost ratio of recommended and control plots were recorded as 1.96, 1.56 and 2.62 and 1.63, 1.17 and 1.96 during 2019–20, 2020–21 and 2021–22 respectively. The cumulative effect of technological interventions over three years, revealed an average benefit cost ratio of 2.05 in demonstration plots compared to 1.59 in control plots. High BC ratio during 2021–22 is due to high procurement price of cotton. The results are in conformity with the findings of Deka et al. (2021), Madhushekar et al. (2021), Rai et al. (2012) and Puniya et al. (2021) in Toria, Maize, Paddy, Sesamum and Mustard.

    3.4.  Technology gap

    The technology gap, the difference between potential yield and yield of demonstration plots was 648, 1591 and 890 kg ha-1 during 2019–20, 2020–21 and 2021–22 respectively (Table 4).


    On an average, technology gap under three year FLD programme was 1043 kg ha-1. The technology gap is very wide and this has to be decreased through various extension interventions in crop, nutrient, pest and disease management. This gap may be due to soil fertility status, nutrient management, weather aberrations, market prices, managerial skills of individual farmer’s and climatic conditions of the selected area. Hence, location specific recommendations are necessary to bridge these gaps. These findings are similar to findings of Tunvar et al. (2017), Shankar et al. (2022) who expressed wide technology gap in groundnut, Cotton and Brinjal.

    3.5.  Extension gap

    The FLD’s conducted in cotton on Management of pink boll worm gave an extension gap of 397, 351 and 448 kg ha-1 during 2019–20, 2020–21 and 2021–22 respectively. On an average extension gap under three year FLD programme was 399 kg ha-1. This emphasized the need to educate the farmers through various techniques especially on INM, IPM, ICM, IDM, use of new ICT tools for the adoption of improved agricultural production technologies to reverse this trend of wide extension gap. More and more use of latest production technologies along with high yielding varieties will subsequently change this trend. Shankar et al. (2022), Ray et al. (2019), Morwal et al. (2018) and Shah et al. (2019) observed the same findings in of wide extension gap in Brinjal, Rice, Cumin and Pulses.

    3.6. Technology index

    The technology index results from Table 4 shows the feasibility of the demonstrated technology at the farmer’s field. The technology index varied from 19.94% to 48.95% (Table 4). On an average, technology index of 32.09% was observed during the three years of FLD programme, which shows the effectiveness, efficacy and ease of adoption of management practices for control of Pink boll worm in cotton. The results are in unity with the findings of Shankar et al. (2022), Choudhary and Suri (2014), Kumar et al. (2020) and Singh et al. (2020). It was also observed from Table 4 that percent increase in productivity was 18.00, 26.83 and 23.29 during 2019–20, 2020–21 and 2021–22 respectively. The results are in uniformity with the results of Narula et al. (2009), Madhushekar et al. (2021), Tankodara et al. (2018).

    In present study, efforts were made to study the impact of FLD’s on Management of PBW in Cotton and its horizontal spread. It is inferred from Table 5 that FLD’s organized in the target area helped to increase the area under Management of Pink Boll Worm in Cotton as the technology was feasible, profitable, easy to adopt, further the damage caused due to PBW is also high among non-FLD farmers. There was significant increase in area and horizontally spread was observed from 14–45 ha, the change in area being 31 ha and % change observed was 221.42%.


    The result of improved technology interventions on Management of PBW in Cotton brought out that adoption of recommended technology, before demonstration was negligible, which increased by 130.60% after demonstration. It can also be inferred from Table 6 that farmers were showing keen interest in use of insecticides for management of PBW compared to adoption of other technological interventions. The overall adoption increased by 130.60% due to FLD’s conducted by KVK (Table 6). The findings are in uniformity with the findings of Tunvar et al. (2017), Subbaiah and Jyothi (2019) in groundnut.


    It can be noted from Table 7 that yield change noticed due to FLDs on Management of PBW in Cotton as 397, 351 and 448 kg ha-1 during 2019–20, 2020–21 and 2021–22 respectively, the average change in yield was 399 kg ha-1.The % change in yield observed due to FLDs was 22.05%.


    3.7.  Increase in knowledge

    Knowledge level of respondent farmers on various aspects of improved PBW management interventions in cotton before conducting the frontline demonstration and after implementation was measured and compared by applying independent ‘t’ test. It could be seen from Table 8 that farmers mean knowledge score on PBW management had increased by 41.49 after implementation of frontline demonstrations. The increase in mean knowledge score of farmers observed was significantly higher. As the computed value of ‘t’ (5.24) was statistically significant at 5% probability level. The results are at par with Narayanaswamy and Eshwarappa (1998), Singh et al. (2007) and Shah et al. (2019). It means there was significant increase in knowledge level of the farmers due to frontline demonstrations. This shows positive impact of frontline demonstrations on knowledge of the farmers that has resulted in higher adoption of technological interventions for management of PBW in Cotton. The results so arrived might be due to the concentrated educational efforts in the form of trainings, On-farm trials, method demonstrations and others made by the scientists of Krishi Vigyan Kendra.

    3.8.  Relationship between personal characteristics with Yield

     Positive and significant correlation (Table 9) was observed between age, education, farm size, farming experience, trainings received and extension contacts with yield of cotton. Most of the farmers selected were middle aged which is an active and agile working period, variable education provides the respondent a broader horizon on any technology. More the education more will be the farmer’s outlook towards various sources of information. Because of education, the farmers could perceive the importance of technology better, thereby impacting on the yield. Farm size, farming experience were directly correlated with yield, bigger the farm size the farmer will be able to plan his activities properly and experience in farming will be an added advantage along with trainings on management of PBW and extension contacts with Scientists of KVK and personnel of various extension agencies helped the farmers to solve their queries. This study also revealed that Area under cotton, farming system, social participation and annual income didn’t have any significant effect on the yield.


  • CONCLUSION

    Conducting of FLDs of proven technologies helped to demonstrate productivity potential and profitability. Management of PBW with technological interventions helped to realize an additional net returns of Rs. 27,526.27 ha-1. The average yield of demonstration was 2207 kg ha-1 compared to farmer’s practice of 1808 kg ha-1. The benefit cost ratio also increased from 1.59 in farmer’s practice to 2.05 in demonstration. The impact of FLD’s was also observed and there was significant increase in area, increase in adoption and increase in knowledge levels of the respondent farmers.    


  • ACKNOWLEDGEMENT

    We are very thankful to Director of Extension, Professor Jayashankar Telangana State Agricultural University (PJTSAU), Hyderabad, Telangana, India for providing the necessary facilities and inputs for carrying out the trials in farmer’s fields.


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Cite

1.
Shekar BRM, Kumar JH, Ravikumar K, Chaitanya V, Reddy RU. Assessment of Extension Interventions for Management of PBW for Enhancing Cotton Production through Frontline Demonstrations among Cotton Growers in Khammam District of Telangana IJBSM [Internet]. 22Dec.2022[cited 8Feb.2022];13(1):1471-1481. Available from: http://www.pphouse.org/ijbsm-article-details.php?article=1742

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