Crop Protection 144 (2021) 105581

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Crop Protection
journal homepage: www.elsevier.com/locate/cropro

Characterization of herbicide use and factors responsible for herbicide

resistance in Phalaris minor in wheat in Haryana, India
Raghuveer Singh a, *, Dharam Bir Yadav b, Ashok Yadav c, Satbir Singh Punia c
a
ICAR-Indian Institute of Farming Systems Research, Modipuram, Meerut, 25110, India
b
CCS Haryana Agricultural University, RRS, Karnal, Haryana, 132001, India
c
CCS Haryana Agricultural University, Hisar, 125004, India

A R T I C L E I N F O A B S T R A C T

Keywords: This study aims to characterize herbicide use and identify the factors responsible for herbicide resistance in
Herbicide resistance Phalaris minor Retz. in wheat in Haryana, India. The pre-tested questionnaire-based survey was conducted
P. minor involving 300 farmers during Rabi (winter) 2017-18 covering five districts (Yamuna Nagar, Kaithal, Karnal,
Spray technique
Fatehabad, and Rohtak) of Haryana. Binary logistic regression analysis established that besides consistent use of
Rice-wheat cropping system
Binary logistic regression
herbicides primarily with a similar mode of action; cultural variables are significantly determining the proba­
bility of facing herbicide resistance viz. crop rotation, field capacity on time (<14 days), time of first irrigation
(<24 days), and zero-till sowing contributed negatively to the herbicide resistance. In contrast, intensive rice-
wheat cropping system (>30-years of practice) and rotavator use for wheat sowing contributed positively.
The study revealed that farmers at some locations applied 3–4 times the recommended dose (X) of herbicides and
ended up with unsatisfactory control (~70%). Clodinafop, though it did not provide satisfactory results,
contributed to about 50% of herbicide use in wheat in Haryana while; sulfosulfuron and pinoxaden share 20%
each and mesosulfuron + iodosulfuron (ready-mix) shares <5%. Recently, farmers have started using pendi­
methalin (750–1000 g a.i. ha-1) as pre-emergence and metribuzin (50–140 g a.i. ha-1) as post-emergence tank-
mix with already recommended herbicides to get desirable control. More than 90% of farmers used 225–300 L
water ha− 1 (standard 500 L ha− 1) and used flood jet or hollow cone nozzles (recommended flat-fan) and, most
farmers (75%) adopted delayed application (standard 30–35 days), resulted in reduced herbicide efficacy.
Farmers’ perception analysis indicates that half of the farmers felt poor quality herbicides as the prime reason for
ineffectiveness. Simultaneously, the rest believed that mono-cropping, higher use of nitrogenous fertilizer, and
under/over-dose of herbicides contributed to the evolution of resistance. The study revealed an increase in the
cost of cultivation by 6.6% to manage P. minor in wheat, and an extra amount of around US$ 38 million was
spent annually by farmers in the rice-wheat cropping system of Haryana.

1. Introduction weed to manage in wheat (Rana and Rana, 2015). With the introduction
of short-statured high yielding wheat varieties, which are less compet­
Herbicide resistance in Phalaris minor Retz. (little seed canary grass) itive than traditional long-statured varieties, management of weeds,
in wheat is the major sustainability issue, which puts the rice-wheat especially P. minor became a big issue for farmers in IGP. To tackle it,
cropping system (RWCS) in north-western Indo-Gangetic Plains (IGP) farmers started using herbicide isoproturon in the 1980s. Due to
under serious threat. It is an associated weed of RWCS because of high over-dependence on a single herbicide for a more extended period
surface moisture, high use of inputs (mainly nitrogenous fertilizers), and coupled with mono-cropping, it evolved resistance against isoproturon
a fixed time table of emergence, growth, and development (Yadav and in 1992-93, the first instance of herbicide resistance in India (Malik and
Malik, 2005). Other than the morphological similarity, seed shedding Singh, 1995). By 1993, the resistance affected area reached up to
behavior (matures earlier than crop and sheds seeds), nonsynchronous 0.8–1.0 million hectares in north-western India; the highest affected was
maturity, and germination in multiple flushes make it a cumbersome Haryana (0.56–0.6 m ha), followed by Punjab (0.3 m ha) (Franke, 2002).

* Corresponding author.
E-mail addresses: raghuveer.singh@icar.gov.in (R. Singh), dbyadav@gmail.com (D.B. Yadav), aky444@gmail.com (A. Yadav), puniasatbir@gmail.com
(S.S. Punia).

https://doi.org/10.1016/j.cropro.2021.105581
Received 29 January 2020; Received in revised form 9 February 2021; Accepted 12 February 2021
Available online 17 February 2021
0261-2194/© 2021 Elsevier Ltd. All rights reserved.
R. Singh et al. Crop Protection 144 (2021) 105581

Table 1 Table 2
List of villages along with key respondent name covered under the survey. Independent variables included in the model and descriptive statistics.
Districts Blocks Villages covered Variable Code Data entry Frequency
a (percentage)
Yamuna Bilaspur Pabnikalan (Ran Singh) , Malakpur (Ravinder) &
Nagar Nagla Jagir (Rai Singh) 1 0
Radaur Bhagu Majra (Arvind), Nangla Sadhan (Jangser) &
Personal factor
Topra Kalan (Manish)
Landholding size LH 1 = up to 2 ha, 0= > 2 72 226
Karnal Nissing Prem Khera (Sumit), Agondh (Bhag Singh) & Bastali
ha (24.2%) (75.8%)
(Rajpal)
Age AGE 1 = up to 45 year, 175 123
Nilokheri Bhaini Khurd (Dharambir), Sagga (Dalbir) & Bir
0=>45 year (58.7%) (41.3%)
Nariana (Lovepreet)
Education status EDU 1 = up to 12th, 109 189
Kaithal Kaithal Kheri Raiwali (Prem Gurjar), Teek (Shyamlal) &
0=>above 12th (36.6%) (63.4%)
Peoda (Kitab Singh)
Source of SI 1 = Agric. department, 60 238
Kalayat Lamba Kheri (Surender), Kailram (Faqir Chand) &
information 0 = others (20.1%) (79.9%)
Batta (Sekhar Rana)
Lease status LS 1 = Leased, 0 = Own 266 32
Fatehabad Tohana Pirthala (Radheshyam Banger), Samain (Amarjeet) &
(89.3%) (10.7%)
Kanheri (Balraj)
Cultural factor
Jakhal Jhakhal (Labh Singh), Talwara/Talwari (Amarjeet) &
Percent area under AUW 1=>75%, 0 = up to 75% 231 67
Der (Rupinder)
wheat (77.5%) (22.5%)
Rohtak Lakhan M Bainsi (Baldev), Khrek Jatan (Mahabir) &
cultivation
Lakhanmajra (Ram Kumar)
Zero-till sowing ZT 1 = Zero tillage, 0 = rest 111 187
Rohtak Dhamar (Wazir Singh), Bhalaut (Karmveer Singh) &
(37.2%) (62.8%)
Kiloi (Bijender)
Rotavator sowing RV 1 = Rotavator, 0 = rest 76 222
a (25.5%) (74.5%)
Name mentioned in parentheses is denoting the key respondent in the
respective village. Days took to reach DFC 1 = with in 14 days, 0 = 208 90
field capacity above 14 days (69.8%) (30.2%)
First irrigation FI 1 = with in 24 days, 0 = 99 199
During the nineties, farmers forced to cut their immature crops as fod­ (DAS), above 24 days (33.2%) (66.8%)
ders due to field overcrowded by P. minor (1500–2000 plants m− 2), as Follow crop FCR 1 = Yes, 0 = No 40 258
wheat yields could be reduced up to 30% by 150 plants m− 2 (Malik and rotation, and (13.4%) (86.6%)
Intensive rice- IRWCS 1=> 30 years only rice- 149 149
Singh, 1995).
wheat cropping wheat, 0 = break in the (50.0%) (50.0%)
To deal with resistance in P. minor, four alternate herbicides viz. system rice-wheat
clodinafop, sulfosulfuron, tralkoxydim, and fenoxaprop were brought in Herbicide application factor
recommendation during 1997-98 (Yadav and Malik, 2005). These her­ Spraying done in SD 1 = Presence, 0 = 268 30
Absence (89.9%) (10.1%)
bicides also lost efficacy within 10–15 years resulting in farmers
Sprayer type ST 1 = Kanpsack, 0 = 229 69
doubling the rate of application with repeated spray to get desirable Power (76.8%) (23.2%)
control (Bhullar et al., 2014). Now, it is confirmed and well-established Nozzle a
NT 1 = Flat-fan, 0 = rest 19 279
that P. minor evolved multiple herbicide resistance against prevailing (6.4%) (93.6%)
a
herbicides, by three modes of action viz. photosynthesis at the photo­ Water volume WV 1 = 500 L/ha, 0 = rest 5 (1.7%) 293
(98.3%)
system II site A, acetyl-CoA carboxylase (ACCase), and acetolactate
Spraying timea ST 1 = 30–35 DAS, 0 = rest 5 (1.7%) 293
synthase inhibition (Chhokar et al., 2008; Yadav et al., 2016; Punia (98.3%)
et al., 2017). Many field surveys were conducted to know the patterns of a
Not included in the model because they do not have sufficient event (<10%).
spray technique and herbicide use against resistant P. minor, but these
were random and inconclusive (Yadav et al., 2006; Punia et al., 2013;
Bhullar et al., 2014). Most of the studies conducted so far were oriented 2.2. Data collection
to quantify the dose required to eradicate or manage the weed based on
lab, pot, or field experiments. But the identification of factors deter­ A pre-tested questionnaire-based survey proforma was used, and its
mining the probability of herbicide resistance was not covered system­ validity was checked before the initiation of the survey by consulting
atically. Therefore, the present farmer participatory study was made to with progressive farmers, excluding the target group. Other than face-to-
elucidate the herbicide use along with factors accountable for multiple face interviews of all respondents, field visits on the key respondents’
herbicide resistance in P. minor in wheat under RWCS. fields and focussed group discussion was also carried out for the in-depth
review of the problem. The absolute value of herbicide used by the
2. Materials and methods farmer’s in one acre (4000 m− 2) area was asked and then converted into
times of recommended dose/hectare (X). Recommended doses of her­
2.1. Study area bicides for wheat viz. pendimethalin (1000 g a.i. ha− 1) and metribuzin
(210 g a.i. ha− 1) as pre-emergence (PRE), and clodinafop (60 g a.i.
A systematic household survey was conducted during the Rabi ha− 1), sulfosulfuron (25 g a.i. ha− 1), pinoxaden (50 g a.i. ha− 1) and
(winter) season of 2017-18 (end of January to February 2018) in five mesosulfuron + iodosulfuron (12 + 2.4 g a.i. ha− 1) as post-emergence
districts (Yamuna Nagar, Kaithal, Karnal, Fatehabad, and Rohtak) of (POST) were used for the above calculation. In the case of tank-mix
Haryana state (lies between 28◦ 39′ 35.1′′ - 30◦ 29′ 06.8′′ N to 75◦ 13′ 56.6′′ - application, for metribuzin, 175 g a.i. ha− 1 was taken as X-dose; at
77◦ 36′ 11.1′′ E) of India. Districts were selected purposively, two this dose, P. minor can be controlled without causing much toxicity in
belonging to intensive RWCS (Karnal and Kaithal) representing typical wheat (Yadav et al., 2016). Among the sample farmer’s, one farmer was
resistance prone areas in the center, and three districts with lesser practicing organic cultivation, and another farmer left wheat cultiva­
intensive RWCS along with some diversification under other cropping tion. Therefore, an analysis was made from 298 farmers’ data for the
systems, representing northern (Yamunanagar), southern (Rohtak) and current study. The prevailing market price of herbicide viz. pendime­
western (Fatehabad) part of the state. Randomly two blocks were thalin ($20.4 US ha− 1), metribuzin ($9.2 US ha− 1), clodinafop ($8.5 US
selected from each district and three villages from each block, and ten ha− 1), sulfosulfuron ($8.5 US ha− 1), pinoxaden ($22.1 US ha− 1), mes­
farmers from each village, thus covering 300 farmer’s from 30 villages osulfuron + iodosulfuron ($19.6 US ha− 1), was considered for
(Table 1). benefit-cost calculation. One time spray application cost was taken as

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R. Singh et al. Crop Protection 144 (2021) 105581

Table 3
The binary logistic regression model- Enter method (first-run).
Model summary

− 2 Log likelihood Cox & Snell R Square Nagelkerke R Square

Step1 226.727a .441 .597

Hosmer and Lemeshow Test
Chi-square df Sig.
Step1 7.538 8 .480
Observed 0.0 1.0 Precentage correct
Problem faced 0.0 89 29 75.4
1.0 23 157 87.2
Overall percentage 82.6
Parameter β SE Wald df Significance Exp(β)
Step 1a LH -.264 .428 .381 1 .537 .768
AGE -.288 .378 .582 1 .446 .749
EDU .251 .420 .357 1 .550 1.286
SI -.235 .451 .272 1 .602 .790
LS .713 .656 1.181 1 .277 2.040
AUW .677 .530 1.635 1 .201 1.969
ZT -.765 .378 4.106 1 .043 .465
RV 1.309 .668 3.835 1 .050 3.701
DFC − 1.617 .438 13.658 1 .000 .198
FI − 1.291 .379 11.598 1 .001 .275
FCR − 2.354 .799 8.682 1 .003 .095
IRWCS 1.206 .411 8.628 1 .003 3.340
SD -.213 .637 .112 1 .738 .808
ST -.229 .463 .245 1 .621 .795
Constant 2.529 .957 6.983 1 .008 12.547
a
The cut value is 0.500.
b
Estimation terminated at iteration number 6 because parameter estimates changed by less than 0.001.
c
Variable(s) entered on step 1: LH, LS, AUH, SI, AGE, EDU, RV, ZT, DFC, FI, IRWCS, SD, FCR, ST.

$6.8 US ha− 1. Farmers were asked to give cause for the low efficacy of contributed by the predictor variable if it has a higher value; it better
herbicides on a scale from 1 to 7 (1 = prime cause and 7 = trivial cause). explains the variability.

2.3.1.1. Selection of dependent and independent variables. The dependent

2.3. Data analysis
variable was grouped into two categories, based on the dose applied and
percent control observed at the individual farmer’s field. If farmers need
Survey data were analyzed using the IBM SPSS 16.0 (Statistical
to apply up to the recommended dose (0-X) of herbicide or get above
Package for Social Science). The binary logistic regression model was
70% control up to double dose (>1X-2X), was assumed that there was no
used to identify the factors determining the probabilities of herbicide
major issue of herbicide resistance (0). Considering poor spray meth­
resistance. Henery Garrett’s (1969) rank technique was used to rank the
odology (improper application time, lower spray volume, and improper
factor responsible for poor efficacy. Kruskal Wallis H test was used to
nozzle) or other limitations (trained manpower, lack of proper moisture
compare group means.
or poor field preparation etc.) on real ground, farmers who reported
above 70% control even up to 2X were counted under first category. This
2.3.1. The binary logistic regression model
was short of grace for poor spray management in the prevailing land­
The linear regression model works when the dependent variable is a
scape and only limited to reach some tangible conclusions rather than a
continuous type, as our outcome is dichotomous; either farmer faced the
general practice to recommend 2X to achieve 70% control or above. But
problem (1) or not encountered it (0). So, the binary logistic regression
when a farmer needed to apply >2X to get satisfactory control or got
model was found to be most appropriate. Logistic regression gives a
below 70% control at 2X, it was assumed that the problem of herbicide
transformed value based on the independent variable, logit (p):
resistance (1) was encountered. Total fourteen independent variables
logit ⋅ (p) ⋅ = ⋅ ln ⋅ p/(1 − p) ⋅ = ⋅ ln⋅(odds ​ ratio) (1) were included in the regression model under three categories as a)
personal factors (land holding, age, education, source of information,
where p is the probabilities of facing the problem of herbicide resistance land leasing), b) cultural factors (percent area under wheat cultivation,
and 1-p, not encountered it, and; an odds ratio is the ratio of two sowing method including zero-till or rotavator, days taken to reach field
probabilities: p/(1-p). capacity, time of first irrigation days after sowing (DAS), follow crop
The general regression model is as the below and code detail given in rotation, and continuity of the rice-wheat cropping system), and c)
(Table 2) herbicide application factor (spraying done in the farmer’s presence and
type of sprayer). Some herbicide application variables such as boom,
logit (p) = ln p/(1-p) = Bo + B1LH + B2AGE + B3EDU + B4SI + B5LS +
nozzle, weather at spray time, and water volume used for spray (liters/
B6AUW + B7ZT + B8RV + B9DFC + B10FI + B11FCR + B12IRWCS +
ha) were not included in the model because they did not have sufficient
B13SD + B14ST (2)
events (<10%) and unable to give satisfactory prediction (Table 2).
Before subjecting to modeling, multi-collinearity was tested among
the independent variables with value of Pearson correlation >0.7, 2.3.2. Henery Garrett’s rank technique
tolerance limit of <0.1, and the variance inflation factor (VIF) of >5.0. To identify the prime cause for poor efficacy of herbicides, Henery
Those variables that did not fulfill these criteria were excluded from the Garrett’s (1969) rank technique was used. The order given by farmers
model for better inferences of results. Model fitness checked by Hosmer converted was into percent position with the help of the following for­
and Lemeshow test; if p > 0.05, it means null hypothesis is accepted. mula; Percent position = 100 (Rij-0.5)/Nj where.
Nagelkerke r-square explains the variability in the dependent variable Rij = Rank given for ith variable by the jth farmer.

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R. Singh et al. Crop Protection 144 (2021) 105581

Nj = Number of variables ranked by the jth farmer. soil disturbance under CTD brings P. minor seed on the upper surface,
The percent position derived for each rank was converted into a score contributing to higher germination and severe infestation. Many farmers
with Henery Garrett’s table. The score of an individual farmer for each in Karnal and Kaithal districts who were earlier practicing ZT now
factor added and divided by the total number of farmers for whom scores shifted to RV sowing due to easy and speedy operation. Because the field
were added. Higher mean value denotes the prime cause, means scores is well prepared by rotavator in one go and crop is sown by broadcasting
for all factors were arranged in rank order, and a conclusion was drawn. (similar to as it was traditional a few years back) in place of line sowing.
In general, under RV, residual moisture is used, and wheat is sown on the
2.3.3. Kruskal Wallis H test same day of rice harvesting. Rice stubble incorporation and mixing of
To compare the group means, one-way ANOVA was used, but as our seed in the soil are done simultaneously or one after another by
data (herbicide use rate across the districts and percent control received) repeating rotavator operations. Other than the easy/reduced operation
did not follow normality, so Kruskal Wallis H test was adopted. with RV, they also experienced more challenging/complex to manage
P. minor under ZT. The seed germinated during the previous rice crop
3. Results and discussion (harvesting stage) gets seedlings/weed plants bigger and harder enough
at the time of the first irrigation in wheat, and these can’t be controlled
3.1. Factors determining the probabilities of herbicide resistance in satisfactorily by any herbicides under ZT. It happens because the farmers
P. minor generally do not apply non-selective herbicides (paraquat/diquat or
glyphosate) before sowing (a pre-requisite for ZT in the situations where
Hosmer and Lemeshow Test value (Chi-Square 7.538, DF = 8 and p = weeds pre-germinate before sowing). Zero-till wheat sowing has created
<0.480) is higher and null hypothesis is accepted that the model sizeable niche areas in the rice-wheat belt, particularly in the late
adequately fits the data (Table 3). Nagelkerke r-square value is also on adopter Rohtak district of Haryana. There is a need to focus again on ZT
the higher side, explaining 59.7% variability in the dependent variable (with crop residue retention) with a complete package as this is
(herbicide resistance) contributed by 14 predictor variables. The result comparatively more sustainable and better resource-conserving tech­
of the classification table indicates that the model predicts 82.6 of cases nology. Also, there is a need to discourage RV wheat sowing. Generally,
correctly. With the help of the Wald test result (Table 3), estimates can it results in patchy crop germination, an induced infestation of P. minor
be made on statistically significant (p = >0.05) and not significant (p = after the first irrigation, and subsequent flushes, besides exaggerated
>0.05) coefficients. With the help of Exp(β), representing the odds ratio, crop lodging and yield losses. Intensive RWCS (>30-year rice-wheat
the role of individual factors in probabilities of occurring events (her­ only) creates a problem, and chances of facing herbicide resistance are
bicide resistance) can be predicted. Mathematical model results 3.3 times [RWCS, Exp(β), 3.340] higher than the diversified cropping
(Table 3) establishes that besides the consistent herbicide use as a system or those who gave a break in rice-wheat system. High iso­
common factor, cultural factors viz. sowing method (zero tillage-ZT or proturon resistance (95%) and 1.67-time expenditure on herbicide in
rotavator-RV), days taken to reach field capacity, time of first irrigation the intensive RWCS region of Haryana compared to diversified cropping
(DAS), crop rotation, and continuity of RWCS significantly determined system has also been reported earlier (Franke et al., 2002). The
the probabilities of herbicide resistance in P. minor. If farmers follow ecological factor of RWCS and P. minor seed inheritance characters play
crop rotation, then there was a lesser (90%) chance of facing herbicide a major role, as its seed is susceptible to soil solarization (Om et al.,
resistance [FCR, Exp(β)-0.095]. Farmers know the importance of crop 2004). But persistent stagnating water conditions in the rice field help
rotation, and it is considered a critical factor in the delaying or man­ maintain lower soil temperature and deep placement of P. minor seed
agement of herbicide resistance by many researchers (Gill and Holmes, during puddling operation, further protecting the P. minor seed exposure
1997; Powles et al., 1997). However, only 14% of farmers followed to high temperature (Om et al., 2004). Hard seed coat resist against
diverse crop rotation, and 86% were continuously growing rice-wheat. If water penetration and inherent capacity of seed to use NO3 as an
field capacity is acquired within two weeks, there were fewer (80%) alternate electron acceptor in Electron transport system (ETS) helps to
chances of facing herbicide resistance [DFC, Exp(β)-0.198]. Field ca­ remain viable in anaerobic condition (Parasher and Singh, 1984).
pacity (vattar/optimal soil moisture) represents the soil properties as Overall, monocropping helps build up P. minor seed bank; intensive
P. minor flourishes in fertile and humid soil (Walia and Gill, 1985), and RWCS provides ecological support for successful survival of P. minor
moisture supplying capacity of soil provide strength to P. minor to fight seed, soil distributing sowing method (CTD/RV) helps to right place­
against the detrimental effect of post-emergence herbicides. High soil ment of P. minor seed, fine-textured soil provide desirable moisture for
moisture for a prolonged period after rice harvesting favor P. minor to sufficient period for its emergence. So a combo pack is there in favor of
emerge earlier than wheat (Chhokar et al., 2012). Further, it influences P. minor to make it an endemic weed of wheat across IGP.
the farmers’ decision to apply irrigation and deploy timely herbicide Personal and herbicide application factors further help to explain the
application. With time span/advance stage, P. minor plants get hard variability’s in the model, but they do not found to contribute signifi­
enough to resist any herbicides. The convenient application of first cantly. It was observed that those who were in touch with the agriculture
irrigation within first 24 DAS reduces the chances of facing herbicide department, small-holders (up to 2 ha), and younger (up to 45 years)
resistance by 72% [FI, Exp(β)-0.275]. encountered fewer problems. Low P. minor density at small farms of
Those farmers who opted for zero-till (ZT) sowing encountered with Haryana (0–2 ha) was also recorded by (Franke et al., 2002), mainly
53% fewer probabilities of herbicide resistance [ZT, Exp(β), 0.465] than crop rotation and manual weeding contributing to it. On the other hand,
conventional-till-drill (CTD) and Rotavator (RV). On the other hand, those who had low education status and taken land on lease faced more
those farmers who did sowing using rotavator; faced 3.7 times herbicide problems. The results also revealed that 88% of farmers knew about
resistance [RV, Exp(β), 3.701] than ZT and CTD. Undisturbed soil under herbicide resistance; despite that, they do not follow herbicide rotation
ZT delays the emergence of P. minor (Om et al., 2004; Franke et al., till they do not face such a problem; and tend to use the same herbicide
2007). Puddling operation in the previous rice crop also contributes to until up to the time it gave some favorable results. Few farmers change
the concentration of P. minor seeds in lower soil layers because of the only the brand formulation, not the chemical. Continuous use of the
higher density (61.3 kg hL− 1). Under ZT, the soil is not or minimally same molecule or from the same group/brand/mode of action speed up
disturbed, making the weed seed unable to come to the upper soil sur­ the resistance development (Caseley et al., 1991; Beckie, 2006) by
face, contributing to lower germination (Chhokar et al., 2007). Under imposing selection pressure (Qasem, 2003).
CTD, a fine seedbed is prepared by implementing 2–3 disc harrows
followed by shallow tiller and planking operation; after that wheat,
sowing is done in line with the help of seed drill. Thus, the exaggerated

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R. Singh et al. Crop Protection 144 (2021) 105581

Table 4 Table 5
Time of spray and P. minor growth stage (N = 298). Information about the herbicide use against P. minor during the last three years
Time of spray P. minor growth stage First spray Second
(2015-16 to 2017–18) (N = 298).
spray 2017–18 2016–17 2015–16
District
0 DAS No germination 14 (4.7%)a 0 (0%) X-dose Percent X-dose Percent X-dose Percent
20-25 DAS ~25–30% germination 50 (16.7%)b 1 (0.7%) control control control
25-30 DAS >50% germination (1–2 leaf 5 (1.7%) 0 (0%)
stage) Fatehabad 2.84 79.6 2.56 86.3 2.32 91.7
30-35 DAS 2-3 leaf stage 5 (1.7%) 0 (0%) (148.7) (173.7) (163.9) (188.4) (168.7) (196.7)
35-40 DAS 2-4 leaf stage 29 (9.7%) 1 (0.7%) Y Nagar 2.13 80.8 1.65 86.5 1.43 91.4
40-45 DAS 3-4 leaf stage 145 (48.3%) 13 (9.1%) (110.4) (183.6) (105.3) (193.8) (100.1) (193.0)
45-50 DAS 4-5 leaf stage 37 (12.3%) 25 (17.6%) Kaithal 3.64 74.0 2.88 79.2 2.57 85.2
>50 DAS >5 leaf stage 13 (4.3%) 102 (71.8%) (193.0) (132.9) (188.8) (122.1) (195.2) (123.3)
Karnal 4.13 69.1 3.33 72.7 2.89 79.2
a
Pre-emergence herbicide. (214.5) (119.1) (220.3) (92.0) (218.5) (86.3)
b Rohtak 1.80 75.1 1.22 83.4 1.07 89.0
Few farmer apply sulfosulfuron at 20 DAS (in the dry field) before the first
irrigation. (85.9) (138.3) (69.6) (151.0) (64.6) (147.7)
Average 2.91 75.7 2.33 81.6 2.06 87.3
Chi- 98.43 25.0 127.8 61.3 147.0 72.6
3.2. Spray techniques square
df 4 4 4 4 4 4
Regarding spray technique about 49.3% of farmers used a flood jet P value 0.00 0.00 0.00 0.00 0.00 0.00

nozzle, followed by a hollow cone nozzle (45.3%), and only 6.4% of Kruskal Wallis H test; Figure given in paranthesis showing mean rank value.
farmers used the flat-fan nozzle (the recommended one). A flat fan
nozzle is the most appropriate for herbicide application as it generates a time being, without knowing the role of standard spray techniques in
flat spray swath and thoroughly covers the entire weed in the swath limit weed control farmer uses an arbitrarily increased dose of herbicide to
(Qasem, 2011). The hollow cone nozzle is designed for fungicide and overcome the effect of poor coverage, which further imposes selection
pesticide application and flood jet for total weed killer (Miller and pressure and contributing to resistance.
Bellinder, 2001). It was evident in the discussion that farmers did not use
the recommended flat fan nozzle because of the convenience of using the
same nozzle for insecticides, fungicides and herbicides and due to more 3.3. Herbicide use pattern
time and energy required to finish up spray work and empty the spray
tank. Information about the herbicide use pattern at X-dose or more
In case of water volume used for herbicides spray, less than 2% used applied by farmers has been presented in Table 5 and Fig. 1. In 2017–18,
the standard volume 500 L ha− 1 for post-emergence herbicide. Around on average, farmers applied 2.91 times of X-dose of total herbicides to
90% of farmers used water volume from 225 to 300 L ha− 1 (51.7 and control P. minor, which was maximum in the case of Karnal district (4.13
39.3% using 300 and 225 L ha− 1, respectively). Farmers do not use X) and lowest in Rohtak (1.80 X), however, recorded only 69–81%
standard water volume due to the high cost (labor charge for each spray control, which was lowest in Karnal and highest in Yamuna Nagar dis­
tank) and time factors. Also, some farmers had misconceptions trict. A similar trend was observed in 2016-17 and 2015–16. Farmers
perceived through pesticide dealers that concentrated sprays provide accepted that clodinafop was not showing any results, but it still
better results and higher water volume dilutes the herbicides and thus, contributed to about half (48.5%) of the total herbicide use in 2017-18.
reduces the efficacy. With this mindset, the farmers tend to use even the Whereas sulfosulfuron and pinoxaden contributed one-fifth, i.e., 21.6
more concentrated spray to deal with the consistently increasing prob­ and 19.2%, respectively, of the total herbicide use. Mesosulfuron +
lem of herbicide resistance. The maximum number of farmers (48.3%) iodosulfuron (ready-mix) contributed very less (<5%) to total herbicide
go for the first herbicide application at 3–4 leaf stage (40–45 DAS), and use. Clodinafop was a major contributor because it is one of the
only <2% farmers apply herbicides at the recommended time of 30–35 cheapest, safest (no phytotoxicity even at higher doses), with no residual
DAS (Table 4). Overall, three-fourth of farmers (74.6%) were spraying effect on succeeding crops and having a wider application window.
the first post-emergence herbicide after 35 DAS. Fields in general, on the Farmers also believed that it works like a fertilizer as the crop turns dark
one hand, receive delayed first irrigation (30–35 DAS), and then the after its application as it might increase the chlorophyll content. Farmers
fields also take time to come to field capacity (vattar) condition, and also tend to apply clodinafop with other herbicides because of its low
ultimately these two prime reasons delay the herbicide application. price, glorious history, and better compatibility with other herbicides.
Other than this, some farmers also had the perception that the appli­ The maximum number of farmers (mainly in Fatehabad district)
cation of herbicides at later stages (4–5 leaf stage of P. minor) gave better were using clodinafop and sulfosulfuron as tank mix, as they perceived
control. Farmers think that the application of herbicide at a later stage that sulfosulfuron worked well at an early growth stage/smaller size
will cover all the weeds germinated in a particular season; they go for (2–3 leaf stage) of P. minor and clodinafop worked at delayed growth
herbicide application at the threshold level. The farmers do not bother stage/bigger one (4–5 leaf stage); hence their combination gave com­
or having awareness about the importance of herbicide application in a plete control. None of the farmers in the focussed group discussion
crop at a critical period. At later stage weeds easily resist the recom­ challenged/contradicted this observation. In terms of performance,
mended dose, so farmers indirectly sub-labeled the herbicide dose and farmers have given preference to pinoxaden, and reported that it was
give chances to acquire resistance. In the present survey, it was found effective compared to clodinafop and sulfosulfuron resistant P. minor
that most of the farmers were not following the standard spray tech­ and widely used in Kaithal, Karnal districts, and Bilaspur block of
niques; as in the previous study also, it was categorically reported that Yamuna Nagar district. The high price of pinoxaden was one of the
suboptimal spraying techniques were followed by IGP farmers (Yadav constraint to its wider adoption as it was 2.5 times costlier than clodi­
et al., 2006; Punia et al., 2013), resulted into harvest lower yield nafop and sulfosulfuron. Mesosulfuron + iodosulfuron (ready-mix)
(Lathwal and Ahalawat, 2011). These factors are responsible for the provided reasonable control, but farmers were afraid of using it due to
poor efficacy of herbicides and inadequate coverage at farmers’ fields fear of its phytotoxicity, particularly in wet field conditions or over­
(Qasem, 2011). Weeds receive under/overdose, which leads to the lapped/repeated spraying. The present spray techniques adopted by
speedy development of resistance (Norsworthy et al., 2012). With the farmers with low water volume, improper nozzle, and delayed appli­
cation could also result in crop injury; however, this herbicide is quite

5
R. Singh et al. Crop Protection 144 (2021) 105581

Fig. 1. Information about the per cent of different herbicides [CDF- clodinafop; SSN- sulfosulfuron; PXD-pinoxaden; MSN + ISN- mesosulfuron + iodosulfuron
(ready-mix); PMN- pendimethalin; MBZ-metribuzin] used against P. minor in last three year (2015-16 to 2017–18) in different districts of Haryana.

safe to the crop under proper spray conditions. Nowadays, farmers had
Table 6
started applying sulfosulfuron before first irrigation at 20 DAS (as dis­
Farmers’ perception on causes responsible for poor efficacy of herbicides (N =
cussed earlier) and reported reasonable control. Rasool (2016) also
268a).
found that the application of sulfosulfuron (25 g a.i. ha− 1), either 14 or
21 DAS before the first irrigation, had provided effective control of Cause Percent of farmers Garette Rank
given the first rank value %
P. minor (>80%) and gave statistically equivalent yield with weed-free
treatment. Absorption of sulfosulfuron by both shoots as well as root Poor quality herbicides 54.1 68.9 1
Everything fine but now can’t 32.8 64.7 2
(Senseman, 2007) and a wide range of half-life (14–75) in soil (Shaner,
get the same results
2014) further support such results. Farmers are also using pendime­ Faulty spray 6.0 53.0 3
thalin (750–1000 g a.i. ha− 1) as PRE and metribuzin (50–140 g a.i. ha− 1) Late application 0.7 49.9 4
as POST-tank-mix with alternate herbicides (clodinafop, sulfosulfuron, Improper dose 2.6 49.7 5
and pinoxaden) to get desirable results. Different field experiments also Rotavator 0.0 35.9 6
Soil, Basmati rice 3.7 27.9 7
reported that the sole application of pendimethalin or metribuzin would
a
manage the multiple herbicide-resistant in P. minor up to some extent Few farmers (mainly Raduar block, Yamuna Nagar) not faced poor efficacy,
but did not give complete control (Punia et al., 2017). So, pre-emergence so put blank this question.
application of pendimethalin and tank mix of metribuzin at lower doses
with alternate herbicides may solve the purpose to some extent (Yadav results. Radaur farmers faced no problem of herbicide resistance, and
et al., 2016), and it may also help to reduce the selection pressure they gave credit to sugarcane cultivation. Sometimes even they did not
against the resistance population (Wrubel and Gressel 1994; Cavan need to apply any herbicide against P. minor because of its satisfactory
et al., 2000; Chhokar et al., 2008). Even farmers are experimenting/­ management in sugarcane-based rotation. It is easy to break P. minor
trying few anti-thesis/unethical practices at their level. Few farmers association with RWCS by introducing sunflower, berseem, sugarcane,
reported that they applied metribuzin (175–350 g a.i. ha− 1) at first oat, vegetable pea, etc. in the crop cycle (Chhokar et al., 2012).
irrigation by mixing with urea and found satisfactory control. A similar
practice was used earlier also and that too very widely in the case of 3.4. Farmers’ perception regarding poor efficacy
isoproturon that actually compounded the resistance issue, and then a
lot of efforts were employed to discourage/curtail it. Use of herbicide as Perception analysis resulted in two groups of farmers. About 54% of
broadcast, in particular, is mostly discouraged otherwise also. farmers considered poor quality herbicides as prime reason for poor
More problem was faced by Karnal (4.13 X-dose) and Kaithal (3.64 control of P. minor (Table 6). It was reported that a lot of variation in the
X-dose) farmers because these districts are continuously growing rice- price among retail outlets or even for same chemical with different
wheat from the last 3-4 decades and having >80% area under the brand names at the same outlet, which indicated spurious products in
rice-wheat system. In a few instances of herbicide use, it was as high as 5 the market. However, another group of farmers informed that in spite of
to 9 times of X-doses and still not getting satisfactory control. Other than no issue with respect of herbicide quality, they were not getting the
this, farmers also reported that Karnal and Kaithal have a maximum area desired results. About 33% of farmers from this group perceived that
under basmati rice. It requires a long duration to reach maturity, which resistant population builds up due to continuous mono-cropping and
creates a problem because fields are not vacated timely. So either they under/over-dose of herbicides and difficulty in the monitoring of her­
go for wet seeding or late wheat sowing, and both conditions favor bicide use in the lease system. As per their view, it is difficult to manage
P. minor (Yadav and Malik, 2005). Karnal had the highest area under the P. minor in the high fertilizers (mainly urea) applied field. They expe­
lease system (one-third among all surveyed districts). It is also respon­ rienced that high use of urea supports the P. minor regeneration. The
sible for exaggerating the problem because those who have taken land high nutrient level increase P. minor competitiveness ability over wheat
on a lease usually apply an overdose of fertilizers and herbicides, which (Singh et al., 2013). Faulty spray (low water volume, improper nozzle,
further sets the high level for the next season. Moreover, they are not power sprayer, and uneven spray, etc.); late application (fields take time
aware of the previous herbicide use history of the field. The lowest for field capacity/vattar condition after first irrigation) and improper
problem was faced by farmers of the Radaur block of Yamuna Nagar who dose (under dose during initial years and intermittent overdose) was
were using only clodinafop at 1.12 times of X-dose and still getting good given 3, 4 and 5th rank, respectively. Farmers are unknown about the
role of the sowing method and soil properties and assign rank on the

6
R. Singh et al. Crop Protection 144 (2021) 105581

Table 7
Total herbicides treatment cost and increase in the cost of cultivation over most economical herbicides (clodinafop) applied once (US$ ha− 1) (N = 298).
Districts 2017–18 2016–17 2015–16

THTC ICOC–Cl PI-COC THTC ICOC–Cl PI-COC THTC ICOC–Cl PI-COC

Fatehabad 43.4 28.1 5.89 37.2 21.9 4.92 33.7 18.4 4.46
Y′ Nagar 38.7 23.4 4.91 31.2 15.9 3.56 27.7 12.4 2.99
Kaithal 58.1 42.8 8.97 45.3 30.0 6.75 39.7 24.4 5.90
Karnal 64.6 49.3 10.32 52.9 37.6 8.45 45.1 29.8 7.20
Rohtak 30.2 14.9 3.12 23.4 8.1 1.81 18.7 3.4 0.83
Average 46.9 31.6 6.63 37.5 22.2 4.99 33.1 17.8 4.30

THTC: Total herbicides’ treatment cost (INR ha− 1); ICOT-Cl: Increase in cost of treatments over clodinafop-applied once (US$ ha− 1); PI-COC: Percent increase in the
cost of cultivation (%); The US$-INR conversion rate used 1 US$ = 73.52 INR.

Fig. 2. Average weekly weather data of wheat sowing time (29 Oct to 18 Nov, 44 to 46 standard meteorological weeks) during cropping seasons-2015-2017.

least side. relative humidity (RHm) was also slightly higher (96.7%) than 2016
(91.9%) and 2015 (92.2%). Mean maximum temperature was recorded
3.5. Cost of cultivation and herbicide resistance 2–4 ◦ C lower in 2017 (25.9 ◦ C) than 2016 (29.2 ◦ C) and 2015 (27.9 ◦ C).
The rate of evaporation also continuously decreased in 2017 while it
The cost of cultivation is boosting up due to repeated spray with increased in 2015 and 2016. These factors played a crucial role in
multiple doses. The analysis revealed that across the districts, farmers maintaining cool and humid sowing time weather during 2017-18. This
spent $46.9 US ha− 1 on herbicides on account of multiple-dose and might have delayed the time required for the field to come to field ca­
repeated spray compared to the one-time application of clodinafop in pacity and favored more emergence of P. minor. Additionally, the
2017-18 ($15.3 US ha− 1). Therefore, additional amounts of $31.6 US farmers have been forced to either go for wet seeding or delayed wheat
ha− 1 are being spent by farmers (Table 7). The cost of cultivation in the sowing, both of which are favorable for higher infestation. Delay in
Karnal district increased by 10.3% due to herbicide resistance in wheat sowing during 2017 due to residue burning was also reported
P. minor, followed by 9% in Kaithal during 2017-18 with an average (Chaba and Jagga, 2017). Besides this, residue burning also contributes
increase 6.6%. Compared to 2015–16, additional cost spent on herbi­ to a rise in soil temperature and the smoke release, stimulates the
cides works out 1.42 times during 2017-18. Though wheat cultivation in P. minor seed germination (Singh, 1996; Chhokar et al., 2009). Instead of
2.50–2.58 m ha from 2016 to 2018, only about 50% is under the rice straw removal, straw burning of 6 and 12 t/ha recorded 1.3–1.8
intensive rice-wheat cropping system. Considering 1.20 m ha area of times higher P. minor germination at the time of wheat sowing (Singh,
rice-wheat monocropping, which is seriously affected by resistant 1996).
P. minor, additional cost incurred by farmers works out to US$ 38 million
to manage P. minor in wheat in 14 major rice-wheat growing districts of 4. Conclusions
Haryana.
Cultural practices (like mono-cropping, intensive RWCS, CTD/rota­
vator sowing, delayed sowing and first irrigation, high use of nitroge­
3.6. Pre-sowing weather and P. minor
nous fertilizers, residue burning, etc.) made P. minor ecologically fit for
the IGP region. Initial high frequency of P. minor when exposed against
Farmer’s faced more problems in 2017-18 than the previous two
prevailing poor spray techniques (like improper application time, lower
years. For exploring the possible reasons, weather data of standard
spray volume, and improper nozzle), increased the probabilities of
wheat sowing time (29th October to 18th November, 44th to 46th
resistance development by imposing selection pressure. Further, arbi­
standard meteorological weeks of 2015–2017) was analyzed (Fig. 2). In
trary use of an increased dose of herbicides by IGP farmers without
2017, out of 21 days, only 27.1 sunshine hours were recorded (just 1.29
understanding the role of herbicide rotation exaggerated the problem.
h day− 1), with 14 days having zero sunshine hours. But in 2016 and
Therefore, farmers should be encouraged to adopt good agricultural
2015, 128.9 (6.14 h day− 1) and 116.5 (5.55 h day− 1) sunshine hours
practices comprising of crop rotation displacing the existing long-term
were recorded, respectively. In 2017, mean evening relative humidity
mono-cropping of the rice-wheat system, adopt timely sowing and
(RHe) was 1.5 times higher (59.1%) than previous years. Mean morning

7
R. Singh et al. Crop Protection 144 (2021) 105581

irrigation, and Zero tillage (with crop residue retention) with a complete Lathwal, O.P., Ahlawat, K.S., 2011. Scenario of herbicide use in wheat in rice-wheat
cropping system. Indian J. Weed Sci. 43 (1&2), 90–91.
package. Educating the farmers to use the proper dose of herbicides,
Malik, R.K., Singh, S., 1995. Littleseed canarygrass (P. minor) resistance to isoproturon in
preferably with a different mode of action in a rotational manner, and India. Weed Technol. 9, 419–425.
the large scale demonstration on improved herbicide spraying tech­ Miller, A., Bellinder, R., 2001. Herbicide Application Using a Knapsack Sprayer. Rice-
niques for farmers, service providers, and even dealers is also necessary. Wheat Consortium for the Indo Gangetic Plains, New Delhi, p. 12.
Norsworthy, J.K., Ward, S.M., Shaw, D.R., Llewellyn, R., Nichols, R.L., Webster, T.M.,
There is a strong need for government policy to effectively encourage Bradley, K.W., Frisvold, G., Powles, S.B., Burgos, N.R., Witt, W., Barrett, M., 2012.
crop diversification, zero tillage with residue retention, financial sup­ Reducing the risks of herbicide resistance: best management practices and
port for purchasing implements efficient in residue management, recommendations. Weed Sci. 60 (1), 31–62.
Powles, S.B., Preston, C., Bryan, I.B., Jutsum, A.R., 1997. Herbicide resistance: impact
weeding out of spurious and ineffective herbicides from the market. and management. Adv. Agron. 58, 57–93.
Also, need of eliminating the subsidies on unfavorable tools (Rotavator). Om, H., Dhiman, S.D., Hemant, K., Sajjan, K., 2004. Biology and management of P. minor
in rice/wheat system. Crop Protect. 23, 1157–1168.
Parasher, V., Singh, O.S., 1984. Physiology of anaerobiosis in P. minor and Avena fatua L.
Declaration of competing interest seeds. Seed Res. 12 (2), 1–7.
Punia, S.S., Yadav, D.B., Sindhu, V.K., Kaur, M., 2017. Post-emergence herbicides for the
The authors declare that they have no known competing financial control of resistant littleseed canarygrass in wheat. Indian J. Weed Sci. 49 (1),
15–19.
interests or personal relationships that could have appeared to influence Punia, S.S., Yadav, D.B., Duhan, A., 2013. Herbicide adoption pattern in rice and wheat
the work reported in this paper. among Haryana farmers. Indian J. Weed Sci. 45 (3), 175–178.
Qasem, J.R., 2003. Weeds and Their Control. University of Jordan Publications, Amman,
Jordan, p. 628.
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