The Fall Armyworm Endemic: Contriving the perspicacity in the outbreak of Fall Armyworm (Spodoptera frugiperda) in relation to push–pull technology
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This study examined farmer perceptions of the Fall Armyworm (FAW) outbreak in western Kenya. It found that both push-pull technology (PPT) farmers and non-PPT farmers reported being affected by FAW, though the spread was slightly higher among non-PPT farms. Farmers also noted that FAW causes more damage and is harder to control than stemborers. Common control strategies like spraying and removing infected crops did not seem to effectively control FAW. While PPT provided some control of FAW, further research is still needed to better address the threat posed by FAW outbreaks.
![© 2018, AEXTJ. All Rights Reserved 89
Available Online at www.aextj.com
Agricultural Extension Journal 2018; 2(2):89-94
RESEARCH ARTICLE
The Fall Armyworm Endemic: Contriving the perspicacity in the outbreak of Fall
Armyworm (Spodoptera frugiperda) in relation to push–pull technology
Nicholas O. Ogot
International Centre of Insect Physiology and Ecology, P.O. BOX 30772-00100 Nairobi, Kenya
Received: 01-02-2018; Revised: 10-03-2018; Accepted: 20-04-2018
ABSTRACT
Fall armyworm (FAW) is a moth native to tropical and subtropical regions of the Americas whose larva
causes damage to crops. As of May 23, 2017 it has affected more than 143,000 hectares of land in major
maize- and wheat-producing counties in Kenya. In response to its severity, this study was conducted to
determine the perception of farmers in respect to; the challenges they faced through FAW endemic; the
differences depicted between FAW and stemborers; and strategies farmers apply to attempt controlling
them. This study was descriptive, and it was conducted in Homabay and Migori using a sample size of 51
households (push–pull technology [PPT] - 25 and non-push–pull technology [NPPT] - 26). It was found
that 7 push–pull households and 8 non-push–pull households expressed FAWs outbreak as a threat to cereal
production. The ratio statistics across the sub-counties interviewed indicated that the spread of FAW was
higher among the non-push–pull farms by 69.9% when push–pull farms showed 63.1%. Moreover, the
ratio statistics of FAWs to stemborers negatively impacting on crop production among the push–pull farms
yielded a 34.2% in comparison to non-push–pull farms that had 74.2%. Furthermore, farmers explained that
FAW was quicker, bigger, and uncontrollable compared to stemborers. The common strategies that farmers
had used to control FAW included spraying of crops, uprooting of the infected crops, and application of ash.
Unfortunately, they did not seem to work effectively both among the PPT and NPPT farms. The regression
model provided showed acceptable significance level. Therefore, FAW outbreak was determined to be a
danger disease to crops both on PPT and NPPT farms. However, push–pull technology reflected a slight
control, but further research would be essential for a further recourse on eliminating FAW.
Key words: Fall armyworms, non-push–pull technology, push–pull technology, stemborers
INTRODUCTION
The fall armyworm (FAW) (also known
scientifically as, Spodoptera frugiperda) is a
specimen of the order Lepidoptera and the larval
lifestageofaFAWmoth.Itisregardedasapestthat
can wreak havoc on crops if left to multiply.[7]
FAW
is a moth native to tropical and subtropical regions
of the Americas, whose larva causes damage to
crops. It mainly affects maize, with potential hosts
from 26 plant families. Significant yield loss can
be caused by FAW if not well managed. FAW has
several generations per year, and the moth can fly
up to 100 km per night. FAW was first detected in
Address for correspondence:
N. O. Ogot,
E-mail: nicholasogot@gmail.com
Central and Western Africa in early 2016 and later
in Southern Africa (except Lesotho and the Island
States). In 2017, it was detected in Eastern Africa
and is expected to spread further. For the time
being, its modality of introduction and its spread
to Africa and adjustments of its bio-ecology are
still speculative.[3]
FAW can be one of the more difficult insect pests
to control in field corn.[6]
The moth is a severe
pest of maize and other grass family crops such
as sorghum. It poses a serious threat to African
agricultureandfoodsecurityaswellasinternational
trade through quarantine restrictions.[2]
Endemic to the Americas, FAWs can fly long
distances, and females can lay up to 1000 eggs at
a time, according to scientists. They proliferate
in tropical climates, making Africa a choice
ISSN 2521 – 0408](https://image.slidesharecdn.com/5aextj2018ra-200722062853/85/The-Fall-Armyworm-Endemic-Contriving-the-perspicacity-in-the-outbreak-of-Fall-Armyworm-Spodoptera-frugiperda-in-relation-to-push-pull-technology-1-320.jpg)
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AEXTJ/Apr-Jun-2018/Vol 2/Issue 2 90
destination; however, experts are still unclear as
to how the pests got here in the first place.[1]
The pest has been recently detected in Kenya and
is suspected to have entered the country from
Uganda. It is also known to be present in Burundi,
Ethiopia, and Rwanda. The FAW was first reported
in Western Kenya by farmers in March 2017 and
immediately confirmed by the Kenya Plant Health
Inspectorate Service and Kenya Agricultural and
Livestock Research Organization. The initial
counties infested were Busia, Trans Nzoia,
Bungoma, Uasin Gishu, and Nandi.[3]
As of May 23, FAWhas affected more than 143,000
hectares of land in major maize- and wheat-
producing counties (in Kenya). The FAO and the
Ministry of Agriculture have adopted a planning
response figure of 800,000 hectares, which requires
US$33.5 million for pesticides and awareness
campaigns in the medium term. US$6.6 million is
required for an immediate response.[4]
In response to the severe effects perceived from the
FAW in the entire agricultural practices, this study
was determined to find how FAW was perceived
among the push–pull technology (PPT) farmers;
how they posed a challenge on cereals production
between the PPT households and the non-push–pull
technology (NPPT) households; how they impacted
differently from Stemborers; and the practices that
farmers strategize to control the infestation of FAW.
METHODOLOGIES
This study employed a descriptive research design
to elaborate on the perception of farmers in the
outbreak of FAWs. Descriptive research designs
help provide answers to the questions of who,
what, when, where, and how associated with a
particular research problem; a descriptive study
cannot conclusively ascertain answers to why. It is
used to obtain information concerning the current
status of the phenomena and to describe “what
exists” with respect to variables or conditions in a
situation.[7]
A cross-sectional survey was therefore
a definite and appropriate establishment for this
study as it could compare different population
groups at a single point in time under descriptive
design. It could compare between the PPT and
the NPPT with the relativity of variables linked to
identifying the outbreak of FAW.
It was conducted in two counties of Kenya:
Homabay and Migori. FAW was lately discovered in
these two counties after its outbreak in other regions.
The majority of the push–pull farmers had a new
challenge from which they sought answers. This was
onthebasisoftheexperiencedsuddeninfestationand
fall of production. This came after the confidence of
alleviated pests’ infestation (Stemborers and Striga)
by PPT after some period of time.
Sample size used to collect data was obtained
in response to the FAW case studies in Kenya.
This study selected 51 households from where
respondents were questioned. Moreover, these
were taken from Homabay and Migori Counties
for precision. Semi-structured questionnaires
were used to probe for the accurate data.
This study analyzed the data obtained from the field
usingSPSSversion 22.Ratiostatistics,correlations,
regressions, and other statistical parameters were
Figure 1: Pie charts of age, gender, push–pull, and years of push–pull technology farming](https://image.slidesharecdn.com/5aextj2018ra-200722062853/85/The-Fall-Armyworm-Endemic-Contriving-the-perspicacity-in-the-outbreak-of-Fall-Armyworm-Spodoptera-frugiperda-in-relation-to-push-pull-technology-2-320.jpg)
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AEXTJ/Apr-Jun-2018/Vol 2/Issue 2 91
used. Data presentations and interpretations were
then done by use of graphs, pie charts, and tables.
Validity of the study was tested by running the data
on the explore statistics to find out its normality.
Validity is arguably the most important criteria for
the quality of a test. The term validity refers to
whether or not the test measures what it claims
to measure. On a test with high validity, the items
will be closely linked to the test’s intended focus.
Reliability test was carried out to find if the data
were consistent, reproducible, and performing.
RESULTS
The data provided a range of findings that depicted
a source of knowledge on push–pull and FAW.
Validity test showed significant statistics. Table 1
provides a descriptive summary that proves the
validity of the data obtained.
Demographic study
The demographic statistics was composed of
regions of survey, age, gender, push–pull analysis,
and years of PPT farming [Table 2].
Household studies
In this study, 49% of the household heads
interviewed were aged between 21 and 40 years,
which formed the majority. The minority 2% were
aged between 15 and 20 years. Males formed 49%
of the sample as female were 51%. Farmers who
were practicing PPT were 51% as the NPPT had
49% of the sample population. Of the PPT farmers
interviewed, 36% had practiced push–pull for
a range of 1–3 years, and another 36% also had
practiced for 4–6 years. 7 and above years of PPT
farming had 28% of PPT farmers, where over
10 years had the least of 4% sample population.
Does FAW impose challenge to the farmers?
The distribution of the FAWs was expressed
by farmers as indicated in Table 3. 7 push–pull
farmers and 8 non-push–pull farmers expressed
FAW as a threat to cereal production. However,
majority had not been infested by FAWs (18 PPT
and 18 NPPT households).
The ratio statistics across the sub-counties
indicated that the spread of FAWwas higher among
the non-push–pull farms by 69.9%. The push–
pull farms showed a relatively less prevalence of
63.1%. Table 4 presents the ratio statistics.
Impact comparison between FAW and
stemborer
The impact of FAW in relation to stemborers
showed significant percentages between push–
pull and non-push–pull. The ratio of FAWs
to stemborers negatively impacting on crop
Table 1: Correlations of age, gender, and PPT/NPPT
Variables Age Gender PPT or NPPT
Age
Pearson correlation 1 −0.065* −0.342*
Significant (two‑tailed) 0.650 0.014
N 51 51 51
Gender
Pearson correlation −0.065* 1 0.058*
Significant (two‑tailed) 0.650 0.684
N 51 51 51
PPT or NPPT
Pearson correlation −0.342* 0.058* 1
Significant (two‑tailed) 0.014 0.684
N 51 51 51
*Correlation is statistically significant at the 0.05 level (2‑tailed). PPT: Push–pull
technology, NPPT: Non‑push–pull technology
Table 2: Regions of survey
County Sub‑county Villages
Migori Awendo Ringa
Nyambija
Kabar
Wawaga
Kadongo
Rongo Kamondi
Rare
Kabuoro
Mtue
Homabay Ndhiwa Kombe
Bwanda
Mbita Ogongo
Agulo Kiuwo
Bung Kwach
Sigulei
Gamba
Rachuonyo South Aolo
Kasipul Bonde
Table 3: Fall armyworm to PPT/NPPT cross‑tabulation
Variables PPT or NPPT Total
PPT NPPT
Fall armyworm
Yes 7 8 15
No 18 18 36
Total 25 26 51
PPT: Push–pull technology, NPPT: Non‑push–pull technology](https://image.slidesharecdn.com/5aextj2018ra-200722062853/85/The-Fall-Armyworm-Endemic-Contriving-the-perspicacity-in-the-outbreak-of-Fall-Armyworm-Spodoptera-frugiperda-in-relation-to-push-pull-technology-3-320.jpg)
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AEXTJ/Apr-Jun-2018/Vol 2/Issue 2 92
production among the push–pull farmers yielded
a 34.2% in comparison to NPPT that had 74.2%.
Table 5 depicts the ratio statistics as provided by
the data obtained from the field.
In an analysis of this study by descriptive design,
the explanations of the farmers (both PPT and
NPPT) relating to the differences between FAW
and stemborers were reviewed. The common
answers given during the study provided a frame
for a better analysis. Table 6 (descriptive statistics)
shows the responses obtained from farmers on the
differences between FAW and stemborers.
Farmers’ practices of controlling FAWs
Table 7 shows the strategies tried by farmers to
controlFAWinfestation.Itincludestheshortcomings
that were expressed by farmers on applying the
strategies. The answers obtained from the farmers
as in Tables 6 and 7 were derived from the pretrial
survey tool (Unstructured questionnaire).
Regression
The significance of this study was placed in
regressionanalysisasinthemodelsbelow.ANOVA
proves no significance for the variables in question,
i.e. knowledge on FAW, imposed challenge, and
difference between FAW and stemborer. However,
correlations provides significance in FAWimposed
challenge to PPT/NPPT. Further significances are
found in differences of FAW and stemborers to
FAW as a challenge and FAW as a challenge to
PPT/NPPT correlations [Table 8].
DISCUSSIONS
The implication of FAWs outbreak is seen in
its extended reach to farmers’ fields in Migori
and Homabay Counties. The cross-tabulation of
FAW and PPT/NPPT farming practices indicates
that farmers from both push–pull and non-push–
pull households are affected at an almost equal
number; 7 of push–pull and 8 of non-push–pull
farmers’ fields were affected. However, many of
the farmers from both farming practices had not
yet been reached by this havoc-wreaking pest.
However, strangely, they also showed some fear
over FAW extending out to their farms sooner or
later.
The rate through which FAWs could spread at a
certain time was tried on a ratio statistics model
across the sub-counties. The outcome was that the
PPT households had a relatively lower prevalence
of 63.1% comparedto NPPTs 69.9%.This depicted
that PPT, to some extent, can slow the rapidness
of the FAW. However, FAW still remains a bigger
challenge worrying the push–pull farmers.
Comparatively, stemborers were found to have a
lesser impact than FAW. A ratio statistic model
providing for FAW against stemborer indicated
Table 4: Ratio statistics for fall armyworm/sub‑counties
Group Price‑related
differential
Coefficient
of dispersion
Coefficient of
variation
Median centered
PPT 1.453 0.444 63.1
NPPT 1.626 0.538 69.9
Overall 1.540 0.492 66.0
PPT: Push–pull technology, NPPT: Non‑push–pull technology
Table 5: Ratio statistics for fall armyworm/stemborer
Group Price related
differential
Coefficient
of dispersion
Coefficient of
variation
Median centered
PPT 1.066 0.210 34.2%
NPPT 1.176 0.596 74.2%
Overall 1.134 0.275 41.2%
PPT: Push–pull technology, NPPT: Non‑push–pull technology
Table 6: Differences between FAW and stemborers as perceived by PPT and NPPT farmers
PPT farmers’ responses NPPT farmers’ responses
FAW Stemborers FAW Stemborers
They act on entire plant (leaves,
stems, and roots)
Does a lot more damage and one
can lose everything planted
They act very fast
They are bigger
They have remained uncontrollable
They burrow into the ground
They act on stems majorly
The damage is on the stems
They act much slower
They are smaller
Can be controlled by push–
pull technology
The effect remains on the
stem
Feed on the tip of the crop
Is voracious in its feeding pattern
It destroys a plant much faster
Totally prevents growth and is
very dangerous
It affects cob more than
stemborers
Majorly affects the young crops
Has a lot of eggs associated/laid
on leaves
It affects all types of crops
Mostly feeds on stalks
It breaks the stem in its feeding
pattern
Destroys a plant much slower
Reduces the growth rate of
a plant but does not totally
prevent
Slightly affects the cob
Majorly affects the old crops
Has comparatively less eggs
Majorly affects the cereal crops
PPT: Push–pull technology, NPPT: Non‑push–pull technology, FAW: Fall armyworm](https://image.slidesharecdn.com/5aextj2018ra-200722062853/85/The-Fall-Armyworm-Endemic-Contriving-the-perspicacity-in-the-outbreak-of-Fall-Armyworm-Spodoptera-frugiperda-in-relation-to-push-pull-technology-4-320.jpg)
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AEXTJ/Apr-Jun-2018/Vol 2/Issue 2 94
that the PPT households had greatly reduced
effects of infestation by 34.2% as the NPPT
occupied largely at 74.2%. It is likely that both the
pests totally diminish any cereal production by the
non-push–pull farmers.
An understanding between both the farming groups
regarding FAW and stemborer showed common
behaviors of the pests. For instance, they explained
that FAWs were quick, bigger, and uncontrollable
while stemborers were slower, smaller, and
controllable (controllable to push–pull farmers).
To complete the farmers’ perception on this
outbreak of FAW, the farmers’domestic strategies/
practices for controlling them were focused on.
Several common strategies used among the PPT
and NPPT farmers were the use of insecticide/
pesticide sprayers, uprooting of the infected
crops, and application of ash. Using PPT method
still remained a unique approach by the push–
pull farmers. However, there were shortcomings
involved over the strategies that the farmers tried
to control the FAWs. Spraying and ash application
did not seem to work for farmers. Moreover, some
of the farmers could not afford the pesticides/
insecticides for spraying onto their farms.
Furthermore, some had no effective control and
hence did not know what to do.
The regression model having three variables
studied (Do you know FAW?, FAW as a challenge,
and Can you tell the difference between FAW and
stemborer?) showed that PPT/NPPT provided a
great significance on FAW (P 0.05; −0.030). The
indication of the impact of FAW as expressed by
farmers is real and hence is the significance level
of this study.
CONCLUSION AND
RECOMMENDATION
Farmers’ perception on FAW outbreak is
apprehensive. Explanations obtained from both
the push–pull farmers and the non-push–pull
farmers reveal the scary perception that FAW
infestation has impacted on the fields and that
has reduced the yields substantially in a brisk
of time. The spread and action of FAW are
quick, making it a more dangerous pest than
stemborers. As a new outbreak, FAW infestation
has surprised many farmers. Push–pull farmers
have tried the PPT on their plots to control the
FAW as used earlier to control the stemborers,
but the result has proven a slight control
compared to the non-push–pull; PPT derived a
slight impact.
Therefore, this study gives way (or recommends)
to further research on PPT, that is, to invent a
further recourse that can help deal with this havoc-
wreaking pest, the FAW.
REFERENCES
1. Craig J. Fall Armyworms Descend on East Africa;
2017. Available from: https://www.voanews.com/a/
armyworms-east-africa/3853083.html. [Last retrieved
on 2017 Jul 14].
2. Kruger K. Why it’s Hard to Control the Fall Armyworm
in southern Africa. The Conversation; 2017. Available
from: theconversation.com/why-its-hard-to-control-
the-fall-armyworm-in-southern-africa-72890. [Last
retrieved on 2017 Jul 14].
3. Report From Food and Agriculture Organization of the
United Nations; 2017.
4. Report from UN Office for the Coordination of
HumanitarianAffairs,UNCountryTeaminKenya;2017.
5. Species Spodoptera Frugiperda - Fall Armyworm
Moth - Hodges#9666.Available from: https://bugguide.
net/node/view/40787/bgimage. [Last retrieved on
2017 May 25].
6. UK Cooperative Extension Service: University of
Kentucky-College of Agriculture. Available from:
https://www.entomology.ca.uky.edu/files/efpdf1/ef110.
pdf. [Last retrieved on 2017 Jul 14].
7. University of South California Libraries, Research
Guides Link. Available from: http://www.libguides.usc.
edu/writingguide/researchdesigns. [Last retrieved on
2017 Jul 14].
8. Professional testing intranet. Available from: http://
www.proftesting.com/test_topics/pdfs/test_quality.pdf.
[Last retrieved on 2017 July 04]](https://image.slidesharecdn.com/5aextj2018ra-200722062853/85/The-Fall-Armyworm-Endemic-Contriving-the-perspicacity-in-the-outbreak-of-Fall-Armyworm-Spodoptera-frugiperda-in-relation-to-push-pull-technology-6-320.jpg)
The Fall Armyworm Endemic: Contriving the perspicacity in the outbreak of Fall Armyworm (Spodoptera frugiperda) in relation to push–pull technology
- 1. © 2018, AEXTJ. All Rights Reserved 89 Available Online at www.aextj.com Agricultural Extension Journal 2018; 2(2):89-94 RESEARCH ARTICLE The Fall Armyworm Endemic: Contriving the perspicacity in the outbreak of Fall Armyworm (Spodoptera frugiperda) in relation to push–pull technology Nicholas O. Ogot International Centre of Insect Physiology and Ecology, P.O. BOX 30772-00100 Nairobi, Kenya Received: 01-02-2018; Revised: 10-03-2018; Accepted: 20-04-2018 ABSTRACT Fall armyworm (FAW) is a moth native to tropical and subtropical regions of the Americas whose larva causes damage to crops. As of May 23, 2017 it has affected more than 143,000 hectares of land in major maize- and wheat-producing counties in Kenya. In response to its severity, this study was conducted to determine the perception of farmers in respect to; the challenges they faced through FAW endemic; the differences depicted between FAW and stemborers; and strategies farmers apply to attempt controlling them. This study was descriptive, and it was conducted in Homabay and Migori using a sample size of 51 households (push–pull technology [PPT] - 25 and non-push–pull technology [NPPT] - 26). It was found that 7 push–pull households and 8 non-push–pull households expressed FAWs outbreak as a threat to cereal production. The ratio statistics across the sub-counties interviewed indicated that the spread of FAW was higher among the non-push–pull farms by 69.9% when push–pull farms showed 63.1%. Moreover, the ratio statistics of FAWs to stemborers negatively impacting on crop production among the push–pull farms yielded a 34.2% in comparison to non-push–pull farms that had 74.2%. Furthermore, farmers explained that FAW was quicker, bigger, and uncontrollable compared to stemborers. The common strategies that farmers had used to control FAW included spraying of crops, uprooting of the infected crops, and application of ash. Unfortunately, they did not seem to work effectively both among the PPT and NPPT farms. The regression model provided showed acceptable significance level. Therefore, FAW outbreak was determined to be a danger disease to crops both on PPT and NPPT farms. However, push–pull technology reflected a slight control, but further research would be essential for a further recourse on eliminating FAW. Key words: Fall armyworms, non-push–pull technology, push–pull technology, stemborers INTRODUCTION The fall armyworm (FAW) (also known scientifically as, Spodoptera frugiperda) is a specimen of the order Lepidoptera and the larval lifestageofaFAWmoth.Itisregardedasapestthat can wreak havoc on crops if left to multiply.[7] FAW is a moth native to tropical and subtropical regions of the Americas, whose larva causes damage to crops. It mainly affects maize, with potential hosts from 26 plant families. Significant yield loss can be caused by FAW if not well managed. FAW has several generations per year, and the moth can fly up to 100 km per night. FAW was first detected in Address for correspondence: N. O. Ogot, E-mail: nicholasogot@gmail.com Central and Western Africa in early 2016 and later in Southern Africa (except Lesotho and the Island States). In 2017, it was detected in Eastern Africa and is expected to spread further. For the time being, its modality of introduction and its spread to Africa and adjustments of its bio-ecology are still speculative.[3] FAW can be one of the more difficult insect pests to control in field corn.[6] The moth is a severe pest of maize and other grass family crops such as sorghum. It poses a serious threat to African agricultureandfoodsecurityaswellasinternational trade through quarantine restrictions.[2] Endemic to the Americas, FAWs can fly long distances, and females can lay up to 1000 eggs at a time, according to scientists. They proliferate in tropical climates, making Africa a choice ISSN 2521 – 0408
- 2. Ogot: The Fall Armyworm Endemic AEXTJ/Apr-Jun-2018/Vol 2/Issue 2 90 destination; however, experts are still unclear as to how the pests got here in the first place.[1] The pest has been recently detected in Kenya and is suspected to have entered the country from Uganda. It is also known to be present in Burundi, Ethiopia, and Rwanda. The FAW was first reported in Western Kenya by farmers in March 2017 and immediately confirmed by the Kenya Plant Health Inspectorate Service and Kenya Agricultural and Livestock Research Organization. The initial counties infested were Busia, Trans Nzoia, Bungoma, Uasin Gishu, and Nandi.[3] As of May 23, FAWhas affected more than 143,000 hectares of land in major maize- and wheat- producing counties (in Kenya). The FAO and the Ministry of Agriculture have adopted a planning response figure of 800,000 hectares, which requires US$33.5 million for pesticides and awareness campaigns in the medium term. US$6.6 million is required for an immediate response.[4] In response to the severe effects perceived from the FAW in the entire agricultural practices, this study was determined to find how FAW was perceived among the push–pull technology (PPT) farmers; how they posed a challenge on cereals production between the PPT households and the non-push–pull technology (NPPT) households; how they impacted differently from Stemborers; and the practices that farmers strategize to control the infestation of FAW. METHODOLOGIES This study employed a descriptive research design to elaborate on the perception of farmers in the outbreak of FAWs. Descriptive research designs help provide answers to the questions of who, what, when, where, and how associated with a particular research problem; a descriptive study cannot conclusively ascertain answers to why. It is used to obtain information concerning the current status of the phenomena and to describe “what exists” with respect to variables or conditions in a situation.[7] A cross-sectional survey was therefore a definite and appropriate establishment for this study as it could compare different population groups at a single point in time under descriptive design. It could compare between the PPT and the NPPT with the relativity of variables linked to identifying the outbreak of FAW. It was conducted in two counties of Kenya: Homabay and Migori. FAW was lately discovered in these two counties after its outbreak in other regions. The majority of the push–pull farmers had a new challenge from which they sought answers. This was onthebasisoftheexperiencedsuddeninfestationand fall of production. This came after the confidence of alleviated pests’ infestation (Stemborers and Striga) by PPT after some period of time. Sample size used to collect data was obtained in response to the FAW case studies in Kenya. This study selected 51 households from where respondents were questioned. Moreover, these were taken from Homabay and Migori Counties for precision. Semi-structured questionnaires were used to probe for the accurate data. This study analyzed the data obtained from the field usingSPSSversion 22.Ratiostatistics,correlations, regressions, and other statistical parameters were Figure 1: Pie charts of age, gender, push–pull, and years of push–pull technology farming
- 3. Ogot: The Fall Armyworm Endemic AEXTJ/Apr-Jun-2018/Vol 2/Issue 2 91 used. Data presentations and interpretations were then done by use of graphs, pie charts, and tables. Validity of the study was tested by running the data on the explore statistics to find out its normality. Validity is arguably the most important criteria for the quality of a test. The term validity refers to whether or not the test measures what it claims to measure. On a test with high validity, the items will be closely linked to the test’s intended focus. Reliability test was carried out to find if the data were consistent, reproducible, and performing. RESULTS The data provided a range of findings that depicted a source of knowledge on push–pull and FAW. Validity test showed significant statistics. Table 1 provides a descriptive summary that proves the validity of the data obtained. Demographic study The demographic statistics was composed of regions of survey, age, gender, push–pull analysis, and years of PPT farming [Table 2]. Household studies In this study, 49% of the household heads interviewed were aged between 21 and 40 years, which formed the majority. The minority 2% were aged between 15 and 20 years. Males formed 49% of the sample as female were 51%. Farmers who were practicing PPT were 51% as the NPPT had 49% of the sample population. Of the PPT farmers interviewed, 36% had practiced push–pull for a range of 1–3 years, and another 36% also had practiced for 4–6 years. 7 and above years of PPT farming had 28% of PPT farmers, where over 10 years had the least of 4% sample population. Does FAW impose challenge to the farmers? The distribution of the FAWs was expressed by farmers as indicated in Table 3. 7 push–pull farmers and 8 non-push–pull farmers expressed FAW as a threat to cereal production. However, majority had not been infested by FAWs (18 PPT and 18 NPPT households). The ratio statistics across the sub-counties indicated that the spread of FAWwas higher among the non-push–pull farms by 69.9%. The push– pull farms showed a relatively less prevalence of 63.1%. Table 4 presents the ratio statistics. Impact comparison between FAW and stemborer The impact of FAW in relation to stemborers showed significant percentages between push– pull and non-push–pull. The ratio of FAWs to stemborers negatively impacting on crop Table 1: Correlations of age, gender, and PPT/NPPT Variables Age Gender PPT or NPPT Age Pearson correlation 1 −0.065* −0.342* Significant (two‑tailed) 0.650 0.014 N 51 51 51 Gender Pearson correlation −0.065* 1 0.058* Significant (two‑tailed) 0.650 0.684 N 51 51 51 PPT or NPPT Pearson correlation −0.342* 0.058* 1 Significant (two‑tailed) 0.014 0.684 N 51 51 51 *Correlation is statistically significant at the 0.05 level (2‑tailed). PPT: Push–pull technology, NPPT: Non‑push–pull technology Table 2: Regions of survey County Sub‑county Villages Migori Awendo Ringa Nyambija Kabar Wawaga Kadongo Rongo Kamondi Rare Kabuoro Mtue Homabay Ndhiwa Kombe Bwanda Mbita Ogongo Agulo Kiuwo Bung Kwach Sigulei Gamba Rachuonyo South Aolo Kasipul Bonde Table 3: Fall armyworm to PPT/NPPT cross‑tabulation Variables PPT or NPPT Total PPT NPPT Fall armyworm Yes 7 8 15 No 18 18 36 Total 25 26 51 PPT: Push–pull technology, NPPT: Non‑push–pull technology
- 4. Ogot: The Fall Armyworm Endemic AEXTJ/Apr-Jun-2018/Vol 2/Issue 2 92 production among the push–pull farmers yielded a 34.2% in comparison to NPPT that had 74.2%. Table 5 depicts the ratio statistics as provided by the data obtained from the field. In an analysis of this study by descriptive design, the explanations of the farmers (both PPT and NPPT) relating to the differences between FAW and stemborers were reviewed. The common answers given during the study provided a frame for a better analysis. Table 6 (descriptive statistics) shows the responses obtained from farmers on the differences between FAW and stemborers. Farmers’ practices of controlling FAWs Table 7 shows the strategies tried by farmers to controlFAWinfestation.Itincludestheshortcomings that were expressed by farmers on applying the strategies. The answers obtained from the farmers as in Tables 6 and 7 were derived from the pretrial survey tool (Unstructured questionnaire). Regression The significance of this study was placed in regressionanalysisasinthemodelsbelow.ANOVA proves no significance for the variables in question, i.e. knowledge on FAW, imposed challenge, and difference between FAW and stemborer. However, correlations provides significance in FAWimposed challenge to PPT/NPPT. Further significances are found in differences of FAW and stemborers to FAW as a challenge and FAW as a challenge to PPT/NPPT correlations [Table 8]. DISCUSSIONS The implication of FAWs outbreak is seen in its extended reach to farmers’ fields in Migori and Homabay Counties. The cross-tabulation of FAW and PPT/NPPT farming practices indicates that farmers from both push–pull and non-push– pull households are affected at an almost equal number; 7 of push–pull and 8 of non-push–pull farmers’ fields were affected. However, many of the farmers from both farming practices had not yet been reached by this havoc-wreaking pest. However, strangely, they also showed some fear over FAW extending out to their farms sooner or later. The rate through which FAWs could spread at a certain time was tried on a ratio statistics model across the sub-counties. The outcome was that the PPT households had a relatively lower prevalence of 63.1% comparedto NPPTs 69.9%.This depicted that PPT, to some extent, can slow the rapidness of the FAW. However, FAW still remains a bigger challenge worrying the push–pull farmers. Comparatively, stemborers were found to have a lesser impact than FAW. A ratio statistic model providing for FAW against stemborer indicated Table 4: Ratio statistics for fall armyworm/sub‑counties Group Price‑related differential Coefficient of dispersion Coefficient of variation Median centered PPT 1.453 0.444 63.1 NPPT 1.626 0.538 69.9 Overall 1.540 0.492 66.0 PPT: Push–pull technology, NPPT: Non‑push–pull technology Table 5: Ratio statistics for fall armyworm/stemborer Group Price related differential Coefficient of dispersion Coefficient of variation Median centered PPT 1.066 0.210 34.2% NPPT 1.176 0.596 74.2% Overall 1.134 0.275 41.2% PPT: Push–pull technology, NPPT: Non‑push–pull technology Table 6: Differences between FAW and stemborers as perceived by PPT and NPPT farmers PPT farmers’ responses NPPT farmers’ responses FAW Stemborers FAW Stemborers They act on entire plant (leaves, stems, and roots) Does a lot more damage and one can lose everything planted They act very fast They are bigger They have remained uncontrollable They burrow into the ground They act on stems majorly The damage is on the stems They act much slower They are smaller Can be controlled by push– pull technology The effect remains on the stem Feed on the tip of the crop Is voracious in its feeding pattern It destroys a plant much faster Totally prevents growth and is very dangerous It affects cob more than stemborers Majorly affects the young crops Has a lot of eggs associated/laid on leaves It affects all types of crops Mostly feeds on stalks It breaks the stem in its feeding pattern Destroys a plant much slower Reduces the growth rate of a plant but does not totally prevent Slightly affects the cob Majorly affects the old crops Has comparatively less eggs Majorly affects the cereal crops PPT: Push–pull technology, NPPT: Non‑push–pull technology, FAW: Fall armyworm
- 5. Ogot: The Fall Armyworm Endemic AEXTJ/Apr-Jun-2018/Vol 2/Issue 2 93 Table 7: Strategies of FAW control practiced by farmers and the shortcomings PPT households (strategies) NPPT households (strategies) Using buffer zones Pesticides and insecticides spraying Using push–pull technology Uprooting of affected crops Ash application Application of herbal concoction Intercropping method Shaking off of leaves Cutting off of the crops and killing the worms Pesticides/insecticide spraying Uprooting of the affected crops Using their indigenous technical knowledge Ash application Trying an early farming The shortcomings: Spraying did not work for many workers Ash did not work Some could not afford the pesticides or insecticides Some had no effective control and did not know what to do PPT: Push–pull technology, NPPT: Non‑push–pull technology, FAW: Fall armyworm Table 8: Regression model for FAW and PPT/NPPT Model summary Model R R2 Adjusted R2 Standard error of the estimate 1 0.189a 0.036 −0.026 0.511 ANOVAa Model Sum of squares df Mean square F Sig. 1 Regression 0.455 3 0.152 0.580 0.631b Residual 12.290 47 0.261 Total 12.745 50 a. Dependent variable: PPT or NPPT b. Predictors: (Constant), Do you know FAW? FAW as a challenge, can you tell the difference between FAW and stemborer? Correlations PPT or NPPT Can you tell the difference between FAW and Stemborer? FAW as a challenge Do you know FAW? Pearson correlation PPT or NPPT 1.000 0.163 −0.030** 0.139 Can you tell the difference between FAW and stemborer? 0.163 1.000 0.007** 0.355 FAW as a Challenge −0.030** 0.007** 1.000 0.091 Do you know FAW? 0.139 0.355 0.091 1.000 Sig. (1‑tailed) PPT or NPPT 0.126 0.416 0.166 Can you tell the difference between FAW and stemborer? 0.126 0.480 0.005 FAW as a challenge 0.416 0.480 0.262 Do you know FAW? 0.166 0.005 0.262 N PPT or NPPT 51 51 51 51 Can you tell the difference between FAW and stemborer? 51 51 51 51 FAW as a challenge 51 51 51 51 Do you know FAW? 51 51 51 51 PPT: Push–pull technology, NPPT: Non‑push–pull technology, FAW: Fall armyworm
- 6. Ogot: The Fall Armyworm Endemic AEXTJ/Apr-Jun-2018/Vol 2/Issue 2 94 that the PPT households had greatly reduced effects of infestation by 34.2% as the NPPT occupied largely at 74.2%. It is likely that both the pests totally diminish any cereal production by the non-push–pull farmers. An understanding between both the farming groups regarding FAW and stemborer showed common behaviors of the pests. For instance, they explained that FAWs were quick, bigger, and uncontrollable while stemborers were slower, smaller, and controllable (controllable to push–pull farmers). To complete the farmers’ perception on this outbreak of FAW, the farmers’domestic strategies/ practices for controlling them were focused on. Several common strategies used among the PPT and NPPT farmers were the use of insecticide/ pesticide sprayers, uprooting of the infected crops, and application of ash. Using PPT method still remained a unique approach by the push– pull farmers. However, there were shortcomings involved over the strategies that the farmers tried to control the FAWs. Spraying and ash application did not seem to work for farmers. Moreover, some of the farmers could not afford the pesticides/ insecticides for spraying onto their farms. Furthermore, some had no effective control and hence did not know what to do. The regression model having three variables studied (Do you know FAW?, FAW as a challenge, and Can you tell the difference between FAW and stemborer?) showed that PPT/NPPT provided a great significance on FAW (P 0.05; −0.030). The indication of the impact of FAW as expressed by farmers is real and hence is the significance level of this study. CONCLUSION AND RECOMMENDATION Farmers’ perception on FAW outbreak is apprehensive. Explanations obtained from both the push–pull farmers and the non-push–pull farmers reveal the scary perception that FAW infestation has impacted on the fields and that has reduced the yields substantially in a brisk of time. The spread and action of FAW are quick, making it a more dangerous pest than stemborers. As a new outbreak, FAW infestation has surprised many farmers. Push–pull farmers have tried the PPT on their plots to control the FAW as used earlier to control the stemborers, but the result has proven a slight control compared to the non-push–pull; PPT derived a slight impact. Therefore, this study gives way (or recommends) to further research on PPT, that is, to invent a further recourse that can help deal with this havoc- wreaking pest, the FAW. REFERENCES 1. Craig J. Fall Armyworms Descend on East Africa; 2017. Available from: https://www.voanews.com/a/ armyworms-east-africa/3853083.html. [Last retrieved on 2017 Jul 14]. 2. Kruger K. Why it’s Hard to Control the Fall Armyworm in southern Africa. The Conversation; 2017. Available from: theconversation.com/why-its-hard-to-control- the-fall-armyworm-in-southern-africa-72890. [Last retrieved on 2017 Jul 14]. 3. Report From Food and Agriculture Organization of the United Nations; 2017. 4. Report from UN Office for the Coordination of HumanitarianAffairs,UNCountryTeaminKenya;2017. 5. Species Spodoptera Frugiperda - Fall Armyworm Moth - Hodges#9666.Available from: https://bugguide. net/node/view/40787/bgimage. [Last retrieved on 2017 May 25]. 6. UK Cooperative Extension Service: University of Kentucky-College of Agriculture. Available from: https://www.entomology.ca.uky.edu/files/efpdf1/ef110. pdf. [Last retrieved on 2017 Jul 14]. 7. University of South California Libraries, Research Guides Link. Available from: http://www.libguides.usc. edu/writingguide/researchdesigns. [Last retrieved on 2017 Jul 14]. 8. Professional testing intranet. Available from: http:// www.proftesting.com/test_topics/pdfs/test_quality.pdf. [Last retrieved on 2017 July 04]