Use of natural insecticides and biocontrol agents in
the control of fall armyworm (Spodoptera
frugiperda J. E. Smith) of maize
Uso de
insecticidas naturales y biocontroladores en el control de gusano cogollero del
maíz (Spodoptera frugiperda J. E. Smith)
Julio Gabriel-Ortega1
George Fabian Holguín Pincay2
Gema Burgos López3
Jessica Morán Morán4
Published Instituto
Tecnológico Superior Corporativo Edwards Deming. Quito - Ecuador Periodicity January - March Vol. 1, Num. 28, 2026 pp. 1-17 http://centrosuragraria.com/index.php/revista Dates of receipt Received: September 12, 2025 Approved: November 15, 2025 Correspondence author j.gabriel@proinpa.org Creative Commons License Creative Commons License,
Attribution-NonCommercial-ShareAlike 4.0
International.https://creativecommons.org/licenses/by-nc-sa/4.0/deed.es
Doctor of Science, tutor for the Master's Degree in Agriculture at the Postgraduate Institute of the State
University of Southern Manabí, Jipijapa, Ecuador. j.gabriel@proinpa.org, juliogabrielortega6@gmail.com,
http://orcid.org/0000-0001-9776-9235
Agricultural Engineer, Master's student in Agriculture at
the Graduate Institute of the State University of Southern Manabí,
Jipijapa, Ecuador,holguin-george5628@unesum.edu.ec , https://orcid.org/0009-0005-5219-960X Master's Degree in Agriculture, Independent Consultant, Portoviejo,
Ecuador.burgosgema38@gmail.com ,
https://orcid.org/0000-0002-0025-3679 Master's Degree in Agriculture, Lecturer on the Master's Degree in
Agriculture programme at the
Postgraduate Institute of the State University of Southern Manabí,
Jipijapa, Ecuador.jessica.moran@unesum.edu.ec , https://orcid.org/0000-0002-6487-1038
Keywords: yield, severity percentage, incidence
percentage, grain weight.
Resumen: Con el objetivo de controlar el gusano
cogollero del maìz (Spodoptera frugiperda J. E. Smith) aplicando insecticidas
naturales y biocontroladores, fue implementada una parcela experimental en un
diseño de bloques completamente aleatorios (DBCA) con 4 tratamientos, 4
repeticiones y 16 unidades experimentales en el Recinto Los Laureles de la
parroquia Julcuy, Manabí. Los tratamientos fueron cuatro (T1: testigo (sin
aplicación), T2: Bacillus thuringiensis (Bt), 150 mL/20 L, T3: Beauveria
bassiana (Bb), y T4: Neem (Azadirachta indica), 25 mL/20 L). Las variables
estudiadas fueron: porcentaje de incidencia (Pinc), porcentaje de severidad
(Psev), altura de planta (ADP), número de entrenudos (NDEN), ancho de tallo
(ADT), área foliar (AF), número de hileras por mazorca (NHPM), número de granos
por mazorca (NDGPM), tamaño por mazorca (TDM), ancho de mazorca (ADM), peso de
100 granos (P100G) y peso de mazorca (PDM). Los resultados determinaron que Bb
y Bt fueron los mejores tratamientos con un menor Psev. Bb fue el mejor
tratamiento para NHPM con 15,12 líneas y NDGPM con 549, 02 granos, respecto del
testigo con 14,24 hileras y 496,53 granos. Hubo una correlación alta, positiva
y significativa (P<0,05) para el NDEN con la ADP, el NFGPM con el NDEN y el
NHPM, el ADM con el TDM y el PDM con P100G.
Palabras clave: rendimiento, porcentaje de severidad,
porcentaje de incidencia, peso de grano.
Introduction
The fall armyworm (FAW) (Spodoptera frugiperda J. E. Smith) is
the most important pest worldwide, causing considerable losses in maize yield.
The FAW was first reported in 1797 as an endemic devouring pest of the
subtropical and tropical regions of America (Abbas et al., 2022). This insect
belongs to the Noctuidae family, order Lepidoptera,
and was first reported on the African continent (Goergen et al., 2016). The BOL
is a devastating pest that damages 186 plant species belonging to 42 families.
Poaceae, Fabaceae, Solanaceae, Asteraceae, Rosaceae, Chenopodiaceous
Brassicaceae, and Cyperaceae are the most affected (Abbas et al., 2022). It
results in a yield loss of approximately 58% in maize [Kumar et al., 2022,
Kenis et al., 2022). GC is known to voraciously feed on more than 350 plant
species, especially maize, rice and sorghum, causing significant agricultural
losses worldwide (Kenis et al., 2022, Montezano et al., 2018, Wang et al.,
2022). GC is the most important pest affecting maize cultivation in Ecuador and
in various producing countries in the region (González-Maldonado et al., 2015,
Yasem de Romero y Romero, 2013). The losses it causes are substantial, reducing
yields by 0.8 t/ha of dry maize, which is equivalent to 40% of production.
Historically, Ecuador has managed
250,000 hectares of maize. In previous years, 214,000 hectares were reported as
planted; however, the area is trending downward, with an estimated 50% located
in the province of Los Ríos, 40% in Manabí, and the rest in Guayas. Ninety per
cent of maize planting takes place in winter. In the summer season, 16,000
hectares were planted with a lower than normal average yield of 1.82 tonnes per
hectare (Drouet Candell, 2018, Llanos et al., 2020).
Large-scale farming creates
conditions conducive to the pest's reproduction and spread. The corn rootworm
is one of the most aggressive insects, acting as a soil worm, cutworm or
armyworm and as a corn earworm, which is its most characteristic habit in corn
(Santos et al., 2014). This pest is of tropical origin and attacks late
plantings on the coasts and in warm irrigated regions more severely. Less
infested are the cornfields of the highlands, where the earworm attack
decreases when the rains begin or when the plants reach a metre in height. To
reduce the harmful effects of the earworm, chemical insecticides are used,
which are sprayed or dusted on the crop ( ). The effects of control have been
low, because these measures have been taken after the critical moment of the
pest and the most appropriate phenological stage of the crop, or after the
damage is irreversible. Attempts have even been made to reduce the damage when
the crop has practically reached a size that makes it impossible for machines
to enter the field (Drouet Candell, 2018).
Biological control strategies are
more appropriate for farmers who do not have the financial capacity to purchase
chemical insecticides and expensive seeds (Abate et al., 2000). Microbial and
natural insecticide formulations are available on the market, made from
pathogens, natural enemies of arthropods, and organic substances, which are
more cost-effective in agricultural systems (Angulo-Escalante et al., 2004,
Arias et al., 2009, Pilkington et al., 2010, Morales,
2015, Kenis et al., 2022). Recently, the production costs of microbial
formulations have been significantly reduced because they are mainly
mass-produced in liquid media (Mahmoud,
2016, Angel-Ríos et al., 2021, Kenis et al., 2022). The repetitive use
of synthetic pesticides in the field can be harmful to humans and the
environment, has increased the cost of inputs, and can also lead to resistance
and resurgence (Ullah et al., 2019, 2020a, 2020b, Qu et al., 2020). Fall
armyworm larvae burrow deep into corn leaves and cobs, resulting in control
failures. However, it feeds on plants at night, dawn, and dusk (Day et al.,
2017, Avila-martínez et al., 2023).
The simplest way to control insect
pest outbreaks is to formulate a self-propelling, self-perpetuating system for
the restoration or stimulation of self-sustaining biological control tactics.
Biological control agents, such as predators, parasitoids, and pathogens, were
supplied to maintain close synchronisation with the community of other
organisms (Sánchez et al., 2019, Valverde et al., 2020). Trichogramma and Telenomus are
the most active biological control agents, parasitising the eggs of GC and
other key pests (Desneux et al., 2010, Zang et al.,
2021, Barrera, 2023). Parasitoids are closely associated with one of the
stages of the pest and have a higher level of specificity (Gowda et al., 2021).
Predators are rarely linked to a specific insect pest. They feed on prey with a
lower trophic level of specificity th , than other animals. For example,
earwigs, ladybirds, podisus and orius feed on different life stages of GC.
Entomopathogens include bacteria, fungi, viruses, protozoa and nematodes, which
are the main cause of disease in insects. The GC was infected by several
entomopathogens, including Bacillus
thuringiensis (Bt), Metarhizium
anisopliae, Beauveria bassiana (Bb),
and multiple nucleopolyhedroviruses of
Spodoptera frugiperda (Portela-Dussán et al., 2013, Drouet, 2018, García et
al., 2018, Assefa & Ayalew, 2019, Litwin et al., 2020, 2022).
The excessive application of
agrochemicals, coupled with monoculture in certain agricultural areas of the
country, means that it is common to see cases where the recommended commercial
doses of certain products for pest control have to be doubled to increase their
efficiency, thus increasing their impact on the environment (Vélez et al,
2021). This is why there is growing interest in using organic products, in this
case biological and natural, to control pests without affecting crop production
(Drouet Candell, 2018, Villarreal et al., 2018). Therefore, the objective of
this research was to control the fall armyworm (Spodoptera frugiperda)
by applying natural insecticides and biocontrol agents.
Methodology
The
research was conducted on the farm of producer Galo Holguín in Los Laureles,
Julcuy parish, Manabí. The parish is bordered to the north by Jipijapa canton,
to the south by Pedro Pablo Gómez parish, to the east by América parish, and to
the west by Puerto López canton. Los
Laureles is located at 1° 25′
44″ south latitude and 80° 35′ 16″ west longitude , at an altitude of 329.22 metres above sea level,
with an average temperature of 240 , RH of 81% and an average annual
rainfall of 250 mm [Julcuy Parish Land Use Plan (PDOT, 2023)].
Factors under study
The factors under study were natural
insecticides and biocontrol agents.
Treatments
The
treatments applied were as follows (Table 1):
Table1 . Four treatments were applied in the trial, as shown
below
|
Treatments |
Dose |
|
|
T1 |
Control |
No application |
|
Bacillus thuringiensis
(Bt) |
||
|
T3 |
Beauveria bassiana
(Bb) |
150 mL/20 L of water |
|
T4 |
Neem (Azadirachta indica) |
25
mL/20 L of water |
The land was prepared one week
before sowing, stubble was removed, minimum tillage was applied, and then the
plots were marked out. Sowing was carried out at a density of 0.80 m between
rows and 0.20 m between plants, placing one seed per site. There were 16
experimental units, covering an area of 285 m2. Weeds were
controlled with the pre-emergent herbicides Glyphosate (2 L/ha), Terbutryn (500
cc/ha), and 2,4-D (2,4-dichlorophenoxyacetic acid (amine) (500 mL/ha).
Post-emergence manual weeding was carried out 35 days after sowing (dds).
Fertilisation was carried out according to the nutritional requirements of the
maize crop. Pest control was carried out using the treatments proposed in the
research, for which a 20 L Jacto
brand backpack sprayer equipped with a solid cone nozzle was used. 150 mL/20 L was
applied for the biocontrol agents and 25 mL/20 L
for the natural insecticide. Harvesting was carried out at 130
days after sowing.
The study plot was implemented in
a completely
randomised block experimental design, with 4 replicates and 4 treatments
(Gabriel et al., 2022). In 4 m long
furrows, totalling 16 experimental units, covering an area of 285 m2.
The following variables were evaluated: Percentage of incidence (%) (Pinc). Using the scale suggested by Agrofy News (2018), which
consists of evaluating the percentage of affected leaves out of the total
number of leaves evaluated in each experimental unit, multiplied by 100. Percentage of severity (%) (Psev). The
percentage incidence of damage caused by Spodoptera frugiperda was
determined at the phenological stages of maize cultivation (development stage,
flowering stage, and reproduction stage) at 20, 30, and 45 days after sowing.
Data were collected in each useful plot, for which an evaluation scale was
developed according to the Davis scale (Table 2 and Figure 1).
Table 2. Scale of percentage
of damage caused by Spodoptera frugiperda in maize.
|
Scale |
Percentage of damage |
Characteristics
of the damage |
|
1 |
0–20 |
Healthy |
|
2 |
21–40 |
Mild |
|
3 |
41 – 60 |
Moderate |
|
4 |
61 – 80 |
Strong |
|
5 |
81 – 100 |
Severe |
1 . Davis
scale for damage assessment (Agrofy
News, 2018)
1:
No damage or pinhole-like lesions caused by first-stage larvae. It is more
common to find a greater number of hatched larvae eggs during this stage.
2-4:
This is the optimal time for control, when window-like lesions are observed,
small circular lesions 1 to 1.5 mm in diameter, scraped without holes. These
lesions are caused by second and third instar larvae
5-6:
Holes of different sizes, visible damage to the bud with signs of a small
amount of soft faeces.
7-8-9:
Obvious destruction of the bud to varying degrees with sawdust-like faecal
plugs that completely prevent control (Agrofy News, 2018).
Plant height (cm) (ADP). Measured with a flexometer at 55 dds on 10 plants chosen
at random from each useful plot (Anchundia & Tumbaco, 2021). Number of internodes
(NDEN). The nodes of each plant were counted
from 55 dds. Stem width (cm) (ADT). A vernier was used at a height of 3 cm
from the soil surface. Leaf area (cm2 ) (AF).
The length of the leaf was measured from the tip of the blade to the
ligule, and the width of the leaf was measured at the centre of the blade.
These data were multiplied by a constant factor of 0.73. Number of rows per ear (NHPM).
The NDPM was counted. Number of grains per ear (NDGPM). The
NDGPM was counted. Ear size (cm) (TDM). A tape
measure was used . Ear width (cm) (ADM). A
tape measure was used. Weight of 100 grains (g) (P100G). One
hundred seeds were weighed with a gram scale. Ear weight (g) (PDM). The harvested ears were weighed on a scale.
Based
on the defined model, analysis of variance (ANOVA) was performed to test
hypotheses about fixed effects, as well as comparisons of treatment means using
Tukey's test (P<0.05). The ANOVA was also used to estimate the variance
components for random effects. Likewise, the correlation between all variables
was performed to determine the degree of association between them using
Pearson's coefficient. All analyses were performed using Infostat software
(2020).
Normality and
homogeneity of variance analysis
Normality was analysed using the Shapiro-Wilks test at 5%, and
homogeneity of variance was analysed using Levene's test at 5% (Gabriel et al., 2022). The data for the variables evaluated
were not significant for either test, indicating normality and hom f the data,
which allowed the ANOVA and comparison of means to continue.
Results
Table 3 shows the
ANOVA for Psev and Pinc and morpho-agronomic traits in maize cultivation. There
were significant differences (P<0.05) for the treatments in Psev and highly
significant differences (P<0.01) for ADP, NDEN, ADT, and AF. The coefficients
of variation (CV) ranged from 3.97% to 17.60%.
Table 3. ANVA y
medias para variables morfo-agronómicas.
|
FV |
gl |
Mean squares |
|||||
|
Psev |
Pinc |
ADP |
NDEN |
ADT |
AF |
||
|
Tra |
3 |
27.59 * |
304.92 ns |
3176.28 ** |
2.43 ** |
0.64 ns |
2.03 ** |
|
Rep |
3 |
8.41 |
74.25 ns |
1117.96 ** |
0.74 ns |
2.38 ns |
2.11 ** |
|
Error |
9 |
4.03 |
191.58 |
131.78 |
0.23 |
1.74 |
0.15 |
|
Total |
15 |
|
|
||||
|
CV |
|
4.84 |
17.60 |
4.57 |
3.57 |
7.43 |
3.97 |
|
Comparison of means |
|||||||
|
Tra |
n |
Pseudo |
Pinc |
ADP |
NDEN |
ADT |
AF |
|
Bb |
4 |
38.87 to |
80.50 to |
271.49 to |
13.98 to |
18.01 to |
10.05 to |
|
Bt |
4 |
40.01 to |
86.00 to |
268.01 to |
13.81 to |
17.97 to |
10.34 to |
|
NEEM |
4 |
42.18 ab |
66.00 a |
210.32 b |
12.25 b |
17.81 a |
8.73 b |
|
Control |
4 |
44.83 b |
82.00 a |
255.25 a |
13.43 |
17.15 |
9.97 a |
|
DSH |
|
4.43 |
30.55 |
25.34 |
1.05 |
2.91 |
0.85 |
Psev: percentage of severity, Pinc: percentage of
incidence, ADP: plant height, NDEN: number of internodes, ADT: stem width (mm),
AF: leaf area (cm²) , Bb: Beauveria
bassiana, Bt: Bacillus thurigiensis, Neem: neem oil.
Means with the same letter are not significantly different (P<0.05). HSD:
Honest Significant Difference.
Analysis
of the treatment means using Tukey's multiple range test (P<0.05) (Table 3)
showed that Bb (38.87%) and Bt (40.01%) were the best treatments,
with a lower Psev, which is not significantly different from the control, which
showed a Psev of 44.83%. With regard to ADP, the NDEN and AF were less favourable with 12.25
nodes, 17.81 mm and 8.73 cm2respectively. Variables such as Pinc and
ADT were not significant.
Table 4 shows the ANOVA of the
productive variables, where the NHPM and NDGPM in corn plants were
significantly different (P<0.05). The TDM, ADM, P100G grains and PDM were
not significant. The CVs ranged from 2.63% to 5.54%.
Table 4. ANOVA
and means
for productive variables.
|
ANOVA |
|||||||
|
FV |
gl |
Mean squares |
|||||
|
NHPM |
NDGPM |
TDM |
ADM |
P100G |
PDM |
||
|
Tra |
3 |
0.66* |
2380.22 * |
1.35 ns |
1.49 |
0.68 ns |
0.47 ns |
|
Rep |
3 |
0.16 ns |
581.39 ns |
1.13 ns |
2.63 |
11.69 ns |
0.63 ns |
|
Error |
9 |
0.15 |
411.93 |
0.44 |
1.48 |
5.48 |
0.41 |
|
Total |
15 |
||||||
|
CV |
|
2.63 |
3.93 |
3.56 |
2.71 |
5.54 |
3.92 |
|
Analysis of means |
|||||||
|
Tra |
n |
NHPM |
NDGPM |
TDM |
ADM |
P100G |
PDM |
|
BB |
4 |
15.12 to |
549.02 to |
19.33 to |
45.66 to |
42.68 to |
279.03 to |
|
BT |
4 |
14.96 ab |
523.04 ab |
18.57 to |
45.00 a |
41.79 a |
262.99 a |
|
NEEM |
4 |
14.49 ab |
499.55 b |
17.95 a |
44.23 a |
42.12 a |
273.22 a |
|
Control |
4 |
14.24 b |
496.53 b |
18.88 a |
44.60 a |
42.58 a |
249.48 a |
|
DSH |
|
0.85 |
44.8 |
1.47 |
44.60 to |
5.17 |
45.51 |
NHPM: number of rows of kernels per ear, NDGPM:
number of kernels per ear, TDM: ear size (cm), ADM: ear width (cm), P100G:
weight of 100 kernels, PDM: ear weight (g). Means with the same letter are not
significantly different (P<0.05).
Analysis of the treatment means using Tukey's multiple range test (P<0.05) (Table 7) showed that Bb was the best treatment for NHPM with 15.12 rows and NDGPM with 549.02 grains, compared to the control ( ) with 14.24 rows and 496.53 grains, respectively. The variables TDM, P100G and PDM were not significant, but a trend towards better PDM (279.03 g) was observed with the Bb treatment, compared to the control, which had a PDM of 249.48 g.
correlation
analysis
Table 5 shows the Pearson correlation analysis, indicating high and significant correlations (P<0.05) for NDEN with ADP (r = 0.92), NDGPM with NDEN (r=0.66) and NHPM (r=0.87), ADM with TDM (r = 0.88) and PDM with P100G (r = 0.86).
Conclusions
Bb and Bt were the best treatments with a lower Psev than the control. Bb was the best treatment for NHPM and NDGPM. TDM, P100G and PDM compared to the control. There was a high, positive and significant correlation for NDEN with ADP, NDGPM with NDEN and NHPM, TDM with NDGPM, ADM with TDM, P100G with ADM and PDM with P100G.
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