*Corresponding author: jconde@utmachala.edu.ec

José Lauro Conde Solano

1,2

Adriana Beatriz Sánchez-Urdaneta

3,4

Ciolys Beatriz Colmenares de Ortega

Edison Ramiro Vásquez

Jorge Ortega-Alcalá

Rev. Fac. Agron. (LUZ). 2023, 40(1): e234003

ISSN 2477-9407

DOI: https://doi.org/10.47280/RevFacAgron(LUZ).v40.n1.03

Crop production

Associate editor: Dr. Jorge Vilchez-Perozo

University of Zulia, Faculty of Agronomy

Bolivarian Republic of Venezuela

Keywords:

Corn biomass

Drip irrigation

Subsurface irrigation

Corn yield

Growth and yield of corn under surface and subsurface drip irrigation

Crecimiento y rendimiento de maíz bajo riego por goteo supercial y subsupercial

Crescimento e produtividade do milho sob irrigacão por gotejamento supercial e subsupercial

Universidad Técnica de Machala-Ecuador.

Programa de Doctorado en Ciencias Agrarias, Facultad de

Agronomía, Universidad del Zulia.

Instituto de Investigación, Facultades de Ingeniería

Agronómica y Ciencias de la Salud, Carrera Bioquímica y

Farmacia. Grupo de Investigación en Manejo, Nutrición y

Ecosiología de Cultivos. Universidad Técnica de Manabí,

Ecuador.

Departamento de Botánica, Facultad de Agronomía,

Universidad del Zulia. Maracaibo, Venezuela.

Departamento de Estadística, Facultad de Agronomía,

Universidad del Zulia. Maracaibo, Venezuela.

Universidad Nacional de Loja-Ecuador.

Received: 17-10-2022

Accepted: 30-11-2022

Published: 22-12-2022

Abstract

To evaluate the eect of surface and subsurface drip irrigation on the

growth and yield of corn, a trial was carried out at the Technical University

of Machala-Ecuador, 1,600 m

of hybrid corn (PIONEER 30K75) were

cultivated to apply the treatments: irrigation by surface and subsurface drip

at 10, 20 and 30 cm depth. The seed was sown in August 2019 at 80 cm

between rows and 40 cm between plants, two seeds per point, with a plant

density of 62,500 plants.ha

-1

. The experimental design was randomized

blocks with four treatments and four repetitions. Plant height, fresh and dry

biomass of leaves, stalks, and roots, biomass of 100 dry kernels, and yield

of dry kernel were evaluated. The highest plant height and biomass of 100

dry kernels was 2.79 m, and 39.08 g, which corresponded to the subsurface

drip irrigation treatment at a depth of 30 cm; the highest fresh and dry

biomass of leaves, 13,631.3 kg.ha

-1

and 3,800 kg.ha

-1

respectively, as well as

the highest yield of dry kernel 10,337.5 kg.ha

-1

was for the subsurface drip

irrigation treatment at 20 cm depth. The highest fresh and dry biomass of

stalks 32,768.8 kg.ha

-1

and 10,381.3 kg.ha

-1

, and the fresh and dry biomass

of roots of 6,381.3 kg.ha

-1

and 2,150 kg.ha

-1

, corresponded to the supercial

drip irrigation treatment. With drip irrigation, at 20 and 30 cm depth, higher

growth and yield were obtained.

This scientic publication in digital format is a continuation of the Printed Review: Legal Deposit pp 196802ZU42, ISSN 0378-7818.

Rev. Fac. Agron. (LUZ). 2023, 40(1): e234003. Enero-Marzo. ISSN 2477-9407.

2-6 |

Resumen

Para evaluar el efecto del riego por goteo supercial y

subsupercial en el crecimiento y rendimiento del maíz, se efectuó

un ensayo en la Universidad Técnica de Machala-Ecuador, se

cultivaron 1.600 m

de maíz híbrido (PIONEER 30K75) para aplicar

los tratamientos: riego por goteo super

cial y subsupercial a 10,

20 y 30 cm de profundidad. La semilla fue sembrada en agosto del

2019 a 80 cm entre surcos y 40 cm entre plantas, dos semillas por

punto, con una densidad de siembra de 62.500 plantas.ha

-1

. El diseño

experimental fue bloques al azar, con cuatro tratamientos y cuatro

repeticiones. Se evaluó altura de planta, biomasa fresca y seca de

hojas, tallo y raíces, biomasa de 100 granos secos y rendimiento en

grano seco. La mayor altura de planta y biomasa de 100 granos secos,

fue de 2,79 m y 39,08 g que correspondió al tratamiento riego por

goteo subsupercial a 30 cm de profundidad; la mayor biomasa fresca

y seca de hojas, 13.631,3 kg.ha

-1

y 3.800 kg.ha

-1

respectivamente

así

como el mayor rendimiento de grano seco 10.337,5 kg.ha

-1

fue para

el tratamiento riego por goteo subsupercial a 20 cm de profundidad.

La mayor biomasa fresca y seca de tallos 32.768,8 kg·ha

-1

y 10.381,3

kg.ha

-1

y la biomasa fresca y seca de raíces de 6.381,3 kg.ha

-1

y 2.150

kg.ha

-1

, correspondió al tratamiento riego por goteo supercial. Con

el riego por goteo, a 20 y 30 cm de profundidad se obtuvo mayor

crecimiento y rendimiento.

Palabras clave: biomasa del maíz, riego por goteo, riego

subsupercial, rendimiento del maíz.

Resumo

Para avaliar o efeito da irrigação por gotejamento supercial e

subsupercial no crescimento e produção de milho, foi realizado um

experimento na Universidade Técnica de Machala – Equador, 1,600

de milho híbrido (PIONEER 30K75) foram cultivados para aplicar

os tratamentos: irrigação por gotejamento supercial e subsupercial

a 10, 20 e 30 cm de profundidade. A semente foi semeada em agosto

de 2019 a 80 cm entre linhas e 40 cm entre plantas, duas sementes por

ponto, com densidade de plantio de 62.500 plantas.ha

-1

. O delineamento

experimental foi em blocos ao acaso, com quatro tratamentos e quatro

repetições. Foram avaliadas a altura da planta, biomassa fresca e seca

de folhas, caule e raízes, biomassa de 100 grãos secos e rendimento de

grãos secos. A maior altura de planta e biomassa de 100 grãos secos

foi de 2,79 m e 39,08 g, que correspondeu ao tratamento de irrigação

por gotejamento subsupercial na profundidade de 30 cm; a maior

biomassa de folhas frescas e secas, 13.631,3 kg.ha

-1

e 3.800 kg.ha

-1

respectivamente, assim como a maior produtividade de grãos secos

10.337,5 kg.ha

-1

foi para o tratamento de irrigação por gotejamento

subsupercial a 20 cm de profundidade. A maior biomassa fresca e

seca de caules 32.768,8 kg·ha

-1

e 10.381,3 kg.ha

-1

e a biomassa fresca

e seca de raízes de 6.381,3 kg.ha

-1

e 2.150 kg.ha

-1

, corresponderam ao

gotejamento supercial tratamento. Com irrigação por gotejamento,

a 20 e 30 cm de profundidade, obteve-se maior crescimento e

produtividade.

Palavras-chave: biomassa de milho, irrigação por gotejamento,

irrigação subsupercial, produtividade de milho.

Introduction

Corn is one of the most important cereals in the world, due to its

use in human food, animal feed, and as a raw material for industry

(Coral et al., 2019). Corn yields have increased over time, thus in

2012 it was reported 886 million tons grown on 171.5 million

hectares, and in 2017 it was 1.1 billion tons grown on 195 million

hectares (FAOSTAT, 2018). According to OECD-FAO (2019), by

2028, world corn production will be 1,311 million tons, due to high

planting density, technied irrigation supply, improved fertilization,

and planting of improved seeds.

The country with the largest corn production is the United States

of America, with approximately 32.4 % (392.45 million tons), China

ranks second with 22.7 % (257.17 million tons), Brazil ranks third

with 8.1 % (82.29 million tons), Argentina fourth with 4.8 % (43.46

million tons), and Ukraine fth with 3.1 % (35.8 million tons) of

global production (OECD-FAO, 2019).

In general, corn production in South America has increased with

much variability in terms of yields achieved, which can be higher

than 10 t.ha

-1

, or lower than 2.12 t.ha

-1

(Carvajal and Cepeda, 2019).

One of the countries where the crop has experienced a signicant

rise has been Ecuador, registering in 2020 a harvested area of 365,334

ha, yields of 4,580 kg.ha

-1

, and a production of 1,479,700 t (FAOSTAT,

2021). It has spread throughout the territory, with hard yellow corn

predominating on the coast and soft white corn in the Andean

Region. Total production of hard corn was 1,304,884 t, harvested on

341,301 ha (ESPAC, 2020); production is concentrated in the coastal

provinces of Los Ríos, Manabí, and Guayas with a production of

643,000, 281,000, and 248,000 t, respectively, representing 40.31 %,

28.64 %, and 16.10 % of the total cultivated area. In the province of

Loja located in the Andean Region, the cultivated area represents 5.9

% (INEC, 2021; ESPAC, 2020).

There are multiple factors that have a direct and indirect inuence

on the morphophysiological

and productive behavior of the corn

crop (Bonilla and Singaña, 2019). It has been established that

sustainability of production is possible with the ecient application

of agricultural practices such as irrigation, without underestimating

the eect of elements such as planting material, climate, soil, water,

and population density, among others (Moran et al. (2020).

The search for alternatives that help reduce water consumption

in corn production is currently having a great impact. Within these

actions, localized drip irrigation becomes a viable alternative since it

reduces water doses, with signicant savings, while achieving greater

utilization by the plant (Wittling et al., 2019). It has been determined

that with drip irrigation, water is saved in a range of 70 % to 90 %

in corn production (Bahena-Delgado et al. 2017). However, it has

been shown that when the crop’s water requirement is reduced, it

can aect both the vegetative and reproductive stages, impacting

morphophysiological parameters such as plant height, stalk diameter,

and ear of corn insertion, as well as yield variables (Tapia et al., 2021).

In the previous research, with the application of 120 % of the

total gross irrigation lamina calculated, equivalent to 376.31 mm,

the highest yield was achieved with 13.49 t.ha

-1

, with a water use

eciency of 8.98 kg.m

-3

of dry corn; while when 80 % of the total

gross lamina was applied, the yield decreased signicantly, achieving

4.25 t.ha

-1

, and a water use eciency of 3.88 kg.m

-3

, showing that

a reduction in the water requirement of the corn hybrid (PIONEER

4039) can signicantly reduce crop yield. The results showed that

yields without water deciency were between 13.5 and 15.3 t.ha

-1

This scientic publication in digital format is a continuation of the Printed Review: Legal Deposit pp 196802ZU42, ISSN 0378-7818.

3-6 |

approximately. Water deciencies during the critical period of the

crop produced yield losses of approximately 50 % of the potential.

Water stress at kernel lling caused yield decreases of about 30 %,

and deciencies in the vegetative stage and the critical period caused

a yield decrease of 56 % (Giménez, 2012). With this background,

the objective of the research was to evaluate the eect of surface and

subsurface drip irrigation on growth and yield of corn.

Materials and methods

The trial was developed in the experimental eld of the Santa

Inés farm, Faculty of Agricultural Sciences, Technical University of

Machala, located at km 5 1/2 Pasaje road, belonging to the province

of El Oro, Planning Zone 7, Ecuador; between coordinates 620,000

W and 963,800 S, Geographic Zone 17 S, Universal Transverse

Mercator Projection, where the alluvial plain of the Jubones river

watershed ends. The climate is tropical megathermal semi-humid,

at an altitude of 5 meters above sea level; the average multiannual

temperature oscillates around 25 °C, while the average multiannual

precipitation is around 600 mm, with two well-marked pluviometric

periods, the rainy period from January to April, and the dry period

from May to December. The reference potential evapotranspiration is

1,300 to 1,500 mm; the annual water decit ranges from 225 to 925

mm (Development and Land Management Plan for the Province of

El Oro, 2015). The soil texture in the rst 30 cm of depth is silt loam,

with a pH of 6.5 and a bulk density of 1.47 gr.cm

-3

The plant material used was hybrid corn (PIONEER 30K75)

sown in August 2019 at 80 cm between rows and 40 cm between

plants, with two seeds per point, with a plant density of 62,500 plants.

-1

. The last irrigation was provided at 100 days after sowing (DAS),

and the analysis of the variables was performed until 110 (DAS).

The experimental design was totally randomized blocks, with four

treatments: 1) surface drip irrigation, 2) subsurface drip irrigation

at 10 cm, 3) subsurface drip irrigation at 20 cm and 4) subsurface

drip irrigation at 30 cm depth. Four replications were used. The

experimental unit was a 100 m

plot planted with hybrid corn, totaling

16 experimental units, giving a total corn cultivated area of 1600 m

Irrigation was planned to respond adequately to the water

requirements of the crop. The irrigation system was designed with a

40 mm diameter PVC main pipe and a 32 mm diameter polyethylene

secondary pipe. The irrigation laterals were 16 mm diameter irrigation

tape with self-compensating drippers inserted at 50 cm (Hydrodrip

Super Flat Integral Dripline, PLASTRO) with a ow rate of 1.65 L.h

-1

and a working pressure of 10 meters of the water column. The design

ow rate was 1.76 L.s

-1

. The energy provided for the operation of the

irrigation systems was through an electric motor pump supplied from

an underground well.

The irrigation supply was independent for each treatment, through

control valves; the volume supplied was recorded by volumetric

valves; the frequencies and times of irrigation were determined by

the reading of the tensiometers installed at a depth of 20 cm since the

greatest volume of roots is found at this depth. To evaluate the growth

and yield variables, 10 plants were selected per experimental unit (40

plants per treatment), for a total of 160 plants. The variables were: 1)

plant height (m), 2) fresh and dry biomass of leaves, stalks and roots,

3) biomass of 100 dry kernels, and 4) dry kernel yield.

For plant height, recording began 30 days after sowing with an

interval of 10 days until 100 days after sowing. To determine the fresh

biomass of leaves, stalks, and roots, a precision balance (Memmert,

Conde et al. Rev. Fac. Agron. (LUZ). 2023 40(1): e234003

Model: V-10801065-800699) was used; subsequently, they were

placed in an oven at 60 °C for 72 hours; after 12 days of drying, the

dry biomass of each selected plant was recorded. For the dry kernel

biomass, the selected ears were collected, whose moisture content

was approximately 25 %, then they were dried in the oven at 60 °C

for 72 hours; subsequently, the shelling was performed manually and

taken to the laboratory to determine the moisture content at 13 %,

and record the biomass of the dry kernels. The dry kernel yield at 13

% moisture was estimated through the biomass of the dry kernel per

plant.

Results and discussion

From 30 to 100 DAS plant height was aected by irrigation

treatments, with signicant statistical dierences (p < 0.002). Drip

irrigation at 20 and 30 cm depth was statistically dierent compared

to surface and subsurface drip irrigation at 10 cm depth. When

comparing the results of the subsurface drip irrigation treatments at

20 and 30 cm depth, there were no signicant dierences in terms of

plant growth, as in the application of the irrigation lamina (Table 1).

The greatest length range was observed between 40 and 60 DAS in

all treatments, stabilizing at 70 dds, when the plant stopped growing.

The results indicated that the subsurface drip irrigation treatment

at 30 cm depth recorded the greatest length (0.58 and 2.79 m at 30

and 70 DAS, respectively), where 129.2 mm of irrigation lamina

was applied; while the surface drip irrigation treatment recorded

the lowest height

(0.52 and 2.66 m at 30 and 70 DAS, respectively),

where 152 mm of irrigation lamina was applied (table 1).

Table 1. Plant height (m) and irrigation lamina applied (mm)

in corn crop (Zea mays L.) irrigated with surface and

subsurface drip irrigation at 10, 20, and 30 cm depth.

Plant height (m)

Days after sowing

Drip

irrigation

treatment

30 40 50 60 70 80 90 100

Surface

0.52 b 1.07 b 1.73 b 2.35 b 2.66 b 2.66 b 2.66 b 2.66 b

Subsurface

10 cm

depth

0.57 a 1.07 b 1.73 b 2.34 b 2.70 b 2.70 b 2.70 b 2.70 b

Subsurface

20 cm

depth

0.60 a 1.15 a 1.85 a 2.39 b 2.78 a 2.78 a 2.78 a 2.78 a

Subsurface

30 cm

depth

0.58 a 1.16 a 1.87 a 2.56 a 2.79 a 2.79 a 2.79 a 2.79 a

Accumulated applied irrigation lamina (mm)

Surface

36.9 a 54.8 a 75.4 a 97.3 a 113.5 a 123.7 a 138.8 a 152.0 a

Subsurface

20 cm

depth

39.2 a 52.9 b 68.1 b 83.2 b 96.9 b 109.1 b 120.7 b 130.4 b

Subsurface

30 cm

depth

38.1 a 51.0 b 66.4 b 82.2 b 95.1 b 105.9 b 117.6 b 129.2 b

Dierent letters within each column indicate that there were statistical

dierences according to Tukey’s multiple means test (p < 0.05) due to the eect

of the treatments applied.

Alvarez and Alvarez (2018), and Uzátegui (2019) in relation to

the growth of corn plants, reported that these reached a maximum

height of 2.59 m which was lower than that obtained in this research.

This scientic publication in digital format is a continuation of the Printed Review: Legal Deposit pp 196802ZU42, ISSN 0378-7818.

Rev. Fac. Agron. (LUZ). 2023, 40(1): e234003. Enero-Marzo. ISSN 2477-9407.

4-6 |

Likewise, Campuzano et al. (2014) indicated averages in eight

hybrid varieties, whose values ranged between 1.85 and 2.01 m of

plant height, which was also lower than those indicated in this study.

Likewise, Tapia et al. (2021), when evaluating the eect

of dierent irrigation laminas and plant densities, determined

signicant dierences between the variables evaluated. Plants that

received 120 % of the gross lamina, reached an average height of

243.11 cm, lower than the one obtained in this study.

Rodriguez et al. (2016) indicated a maximum growth of 2.36

m at 60 DAS. In contrast, in this research the maximum height of

the plants was presented at 70 dds; this suggests that at this stage,

in which the development of the reproductive structures begins,

the corn plant decreased or stopped its growth, to concentrate its

photoassimilates to the production of its fruits.

While Hidalgo (2012) found a maximum plant height of hybrid

corn of 2.68 m, planted at 90 x 40 cm, values closer to those

obtained in this research.

Regarding the production of biomass of leaves, although

no statistical dierences were detected between treatments, the

subsurface drip irrigation at 20 cm depth recorded the highest yield,

corresponding to 218.1 g.plant

-1

(13,631 kg.ha

-1

) of fresh biomass,

equivalent to 1,362.8 g.m

-2

; while the dry biomass was 60.8 g.plant

-1

(3,800 t.ha

-1

), equivalent to 380 g.m

-2

. The lowest yield was for the

subsurface drip irrigation treatment at 10 cm depth, which reached

201.9 g.plant

-1

(12,619 kg.ha

-1

of fresh leaf) equivalent to 1,262 g.m

, while the dry biomass was 57.1 g.plant

-1

(3,569 kg.ha

-1

) equivalent

to 357 g.m

-2

Table 3. Fresh and dry biomass of stalks, volume of water applied, and water use eciency in corn crop (Zea mays L.) irrigated with

surface and subsurface drip irrigation at 10, 20, and 30 cm depth.

Drip irrigation system

Fresh biomass of stalks

(kg.ha

-1

)

Dry biomass of stalks

(kg.ha

-1

)

Volume of water applied

.ha

-1

)

Water use eciency

(fresh biomass kg.m

-3

)

Water use eciency (dry

biomass kg.m

-3

)

Surface 32,768.8 a 10,381.3 a 1519.3 a 21.6 b 6.8 b

Subsurface

10 cm depth 28,650.0 a 8,887.5 a 1392.3 b 20.6 b 6.4 b

Subsurface

20 cm depth 31,775.0 a 10,018.8 a 1303.5 b 24.4 a 7.7 a

Subsurface

30 cm depth 30,162.5 a 9,356.25 a 1291.8 b 23.4 a 7.2 a

Dierent letters within each column indicate that there were statistical dierences according to Tukey’s multiple means test (p < 0.05) due to the eect of the treatments

applied.

Regarding water use eciency, it should be noted that

subsurface drip irrigation can avoid excessive water consumption

by reducing soil evaporation losses. The water that is found in the

supercial part of the soil and that is evaporated by solar radiation

has been called “non-benecial consumption for the plant” (Ayars et

al., 2015; Eranki et al., 2017; Sinha et al., 2017; Bringas et al., 2020).

The eciency of water use in the biomass yield of leaves, the

results show that the highest eciency was for the subsurface

drip irrigation treatment at 20 cm depth, with 10.5 kg.m

-3

, being

numerically equal to that achieved with irrigation at 30 cm; the

lowest eciency of water use was for the surface drip irrigation

treatment with 8.8 kg.m

-3

, showing no dierences with subsurface

irrigation at 10 cm (table 2).

The results obtained for dry biomass of leaves were much

higher than those determined by Uzátegui (2019), who obtained

yields of 50.3 g.plant

-1

. Similarly, Rodríguez et al. (2016) reported

fresh biomass yields of leaves between 150 and 206 g.plant

-1

. While

Espósito et al (2007) in dry-farmed corn, obtained dry biomass

yields of leaves of 250.17 g.m

-2

with a plant density of 72,000 seeds.ha

-1

The results corresponding to stalk biomass including ears, the

surface drip irrigation treatment recorded the highest yield with

524.3 g.plant

-1

(32,768.8 kg.ha

-1

) of fresh biomass, equivalent to

3,146 g.m

-2

, with no statistical dierences between treatments; while

the dry biomass was 166.1 g.plant

-1

(10,381.3 kg.ha

-1

), equivalent to

1,038 g.m

-2

. The lowest value was for the subsurface drip irrigation

treatment at 10 cm depth, which obtained 458.4 g.plant

-1

(28,650

kg.ha

-1

) of fresh biomass, equivalent to 2,865 g.m

-2

; dry biomass

was 142.2 g.plant

-1

(8,887.5 kg.ha

-1

), equivalent to 889 g.m

-2

(table 3).

Table 2. Fresh and dry biomass of leaves, volume of water applied, and water use eciency in corn crop (Zea mays L.) irrigated with

surface and subsurface drip irrigation at 10, 20, and 30 cm depth.

Drip irrigation treatment

Fresh biomass of leaves

(kg.ha

-1

)

Dry biomass of leaves

(kg.ha

-1

)

Volume of water applied

.ha

-1

)

Water use eciency

(fresh biomass kg.m

-3

)

Water use eciency (Dry

biomass kg.m

-3

)

Surface 13,431.3 a 3,606.3 a 1,519.3 a 8.8 b 2.4 b

Subsurface

10 cm depth

12,618.8 a 3,568.8 a 1,392.3 b 9.1 b 2.6 b

Subsurface 20 cm depth 13,631.3 a 3,800.0 a 1,303.5 b 10.5 a 2.9 a

Subsurface

30 cm depth

13,568.8 a 3,787.5 a 1,291.8 b 10.5 a 2.9 a

Dierent letters within each column indicate that there were statistical dierences according to Tukey’s multiple means test (p < 0.05) due to the eect of the treatments

applied.

This scientic publication in digital format is a continuation of the Printed Review: Legal Deposit pp 196802ZU42, ISSN 0378-7818.

5-6 |

Regarding water use eciency in biomass yield of stalks, the

results showed that the highest water use eciency was for the

subsurface drip irrigation treatment at 20 cm depth with 24.4 kg.m

-3

for fresh biomass, and 7.7 kg.m

-3

for dry biomass, with no dierences

with the subsurface treatment at 30 cm; the lowest water use eciency

was for the subsurface drip irrigation treatment at 10 cm depth with

20.6 kg.m

-3

for fresh biomass and 6.4 kg.m

-3

for dry biomass, not

diering from the surface irrigation treatment (table 3).

These results were higher than those obtained by Uzátegui

(2019), who reported values of 79.8 g.plant

-1

of dry biomass of stalks.

Likewise, in trials conducted in the province of Santa Elena-Ecuador

by Tumbaco (2019), results of fresh biomass of stalks of 28,200

kg.ha

-1

were obtained.

The results showed that the water use eciency in the biomass

yield of stalks and the subsurface drip irrigation treatment at 20 cm

were the most ecient due to the lower water consumption.

Regarding root biomass, although there were no dierences

between treatments, the highest yield was for the surface drip

irrigation treatment with 102.1 g.plant

-1

(6,381 kg.ha

-1

) of fresh

biomass, representing 638 g.m

-2

; while the dry biomass was 34.4

g-plant

-1

(2,150 kg.ha

-1

), equivalent to 215 g.m

-2

. The lowest yield

was for the subsurface drip irrigation treatment at 10 cm depth with

86.1 g.plant

-1

(5,381.3 kg.ha

-1

) of fresh mass, equivalent to 538 g.m

-2

;

while dry biomass was 27.5 g.plant

-1

(1,718.8 kg.ha

-1

), equivalent to

172 g.m

-2

(table 4).

Conde et al. Rev. Fac. Agron. (LUZ). 2023 40(1): e234003

The highest eciency was for the subsurface drip irrigation

treatment at 30 cm depth, with 4.5 kg.m

-3

for fresh biomass, and

1.6

kg.m

-3

for dry biomass, showing no dierences with subsurface

irrigation at 20 cm and with surface irrigation; the lowest water use

eciency was for the subsurface drip irrigation treatment at 10 cm

depth with 3.9 kg.m

-3

for fresh biomass and 1.2 kg.m

-3

for dry biomass

(table 4).

In trials conducted by Delgado et al. (2008), values between

30 and 35 g.plant

-1

of dry root biomass were obtained 75 days after

sowing, resulting dierent from those obtained in this research. While

for the variable biomass of 100 dry kernels, no statistical dierences

were generated between treatments, the highest yield was for the

subsurface drip irrigation treatment at 30 cm depth with a value

of 39.1 g.100 kernels

-1

, and the lowest was for the subsurface drip

irrigation treatment at 10 cm depth, whose yield was 37.2 g.100

kernels

-1

(table 5).

Regarding yield of the dry kernel when comparing the results of

the surface and subsurface drip irrigation treatments at 10 cm depth

with the results of the subsurface drip irrigation treatments at 20

and 30 cm depth, signicant dierences were found. The subsurface

drip irrigation treatment at 20 cm depth obtained the highest yield

165.4 g.plant

-1

(10,337.5 kg.ha

-1

) not diering from the treatment at

30 cm depth; the lowest yield was for the subsurface drip irrigation

treatment at 10 cm depth of 147.7 g.plant

-1

(9,232.8 kg.ha

-1

), showing

no dierences with surface irrigation (table 6).

Table 4. Fresh and dry root biomass, volume of water applied, and water use eciency in corn crop (Zea mays L.) irrigated with surface

and subsurface drip irrigation at 10, 20, and 30 cm depth.

Drip irrigation

system

Fresh root biomass (kg.ha

-1

) Dry root biomass (kg.ha

-1

)

Volume of water applied

.ha

-1

)

Water use eciency

(fresh biomass kg.m

-3

)

Water use eciency

(dry biomass kg.m

-3

)

Surface 6.381,3 a 2.150,0 a 1.519,3 a 4.2 a 1.4 a

Subsurface

10 cm depth

5.381,3 a 1.718,8 a 1.392,3 b 3.9 b 1.2 a

Subsurface

20 cm depth

5.725,0 a 1.856,3 a 1.303,5 b 4.4 a 1.4 a

Subsurface

30 cm depth

5.781,3 a 2.025,0 a 1.291,8 b 4.5 a 1.6 a

Dierent letters within each column indicate that there were statistical dierences according to Tukey’s multiple means test (p < 0.05) due to the eect of the treatments

applied.

Table 5. Biomass of 100 dry corn kernels.

Drip irrigation treatment Weight of 100 dry kernels (g)

Surface 38.2 a

Subsurface at 10 cm depth 37.2 a

Subsurface at 20 cm depth 38.4 a

Subsurface at 30 cm depth 39.1 a

Table 6. Yield of dry corn kernel, volume of water applied, and water use eciency.

Drip irrigation treatment Yield (kg.ha

-1

) Volume of water applied (m

) Water use eciency (kg.m

-3

)

Surface 9,259.4 b 1519.25 a 6.10 b

Subsurface 10 cm depth 9,232.8 b 1392.25 b 6.63 b

Subsurface 20 cm depth 10,337.5 a 1303.5 b 7.95 a

Subsurface 30 cm depth 10,189.1 a 1291.75 b 7.89 a

This scientic publication in digital format is a continuation of the Printed Review: Legal Deposit pp 196802ZU42, ISSN 0378-7818.

Rev. Fac. Agron. (LUZ). 2023, 40(1): e234003. Enero-Marzo. ISSN 2477-9407.

6-6 |

Regarding water use eciency in yield of the dry kernel, the

highest eciency corresponded to the subsurface drip irrigation

treatment at 20 cm depth with 7.95 kg.m

-3

, but did not dier from

irrigation at 30 cm depth; the lowest water use eciency was for the

surface drip irrigation treatment at 10 cm depth with 6.10 kg-m

-3

showing no dierences with surface irrigation (Table 6).

The highest yield of the dry kernel and water use eciency

obtained with subsurface irrigation is explained by the lowest N

loss due to evaporation and drainage compared to surface irrigation

(Lamm et al., 2001).

With subsurface drip irrigation technology in Quevedo-Ecuador,

yields of 10,720 kg.ha

-1

were obtained (Vásconez et al., 2010); also

Álvarez and Álvarez (2018) reported yields of corn kernel of 7,050

kg.ha

-1

in the Joa valley, province of Manabí-Ecuador.

In the research carried out by Tapia et al. (2021) the yield variable

presented a signicant eect according to the percentages of the gross

lamina evaluated; with the application of 120 % of the gross lamina,

the highest yield was obtained with 10.44 t.ha

-1

with a dierence of

4.81 t.ha

-1

compared when 80 % of the total lamina was applied.

Conclusions

When irrigation was delivered subsurface at 20 and 30 cm depth,

greater plant growth and higher biomass yield of leaves, stalks,

and kernel were obtained, while when irrigation was delivered

supercially, greater root biomass was obtained. The eciency in the

use of water employed for irrigation in the corn crop for the production

of leaves, stalks, and kernel, is greater when irrigation is supplied in

the subsurface part of the soil, where the largest volume of roots of

the plant is found, maximizing the water applied and consumed.

Recommendations

In the case of hybrid corn, drippers should be buried at 20 cm

depth, at which in this work a better water use eciency was found.

Literature cited

Álvarez Álvarez, M. J., and Álvarez, P. (2018). Parámetros hídricos: Cultivo

de maíz en el Valle de Joa, Ecuador. https://repositorio.iniap.gob.ec/

handle/41000/5081

Ayars, J., Fulton, A. & Taylor, B. (2015). Subsurface drip irrigation in California—

Here to stay? Agricultural Water Management, 157(31), 39-47. https://

doi.org/10.1016/j.agwat.2015.01.001

Bahena-Delgado, G., Olvera-Salgado, M.D., Broa-Rojas, E., García-Matías, F.,

Jaime-Hernández, M.A. y Torres, S.C. (2017). Niveles de fertilización

y eciencia de agua en la producción de maíz elotero (Zea mays L.),

Agroproductividad10(3), 3-8. https://revistaagroproductividad.org/index.

php/agroproductividad/article/view/960

Bonilla, A. y Singaña, D. (2019). La productividad agrícola más allá del

rendimiento por hectárea: Análisis de los cultivos de arroz y maíz duro

en Ecuador. LA GRANJA: Revista de Ciencias de la Vida 29(1), 65-78.

https://doi.org/10.17163/lgr.n29.2019.06

Bringas-Burgos, B., Mendoza-Muñoz, I., Navarro-González, C., González-

Ángeles, Á., & Jacobo-Galicia, G. (2020). Análisis de sistemas de riego

por gravedad y goteo subsupercial basada en una encuesta de muestra de

conveniencia en el valle de Mexicali. Revista Vínculos ESPE, 5(3), 13-32.

https://doi.org/10.24133/vinculosespe.v5i3.1725

Campuzano, L., Caicedo, S., & Alfonso, H. (2014). Corpoica H5: primer híbrido

de maíz amarillo de alta calidad de proteína (QPM) para la altillanura

plana colombiana. Ciencia y Tecnología Agropecuaria, 15(2), 173-182.

https://doi.org/10.21930/rcta.vol15_num2_art:357

Carvajal-Larenas, F. E., and Cepeda, G. M. C. (2019). Análisis comparativo de

la eciencia productiva del maíz en Sudamérica y el mundo en las dos

últimas décadas y análisis prospectivo en el corto plazo. ACI Avances

en Ciencias e Ingenierías, 11(1), 94-103. https://doi.org/10.18272/aci.

v11i1.1079

Coral, J., Andrade, H., Pumisacho, M., Caicedo J. & Salazar, D. (2019).

Caracterización morfológica y agronómica de dos genotipos de maíz

(Zea mays L.) en la zona media de la Parroquia Malchinguí. Avances en

Ciencias e Ingeniería (ACI), 11(1), 40-49. https://doi.org/10.18272/aci.

v11i1.1091

Delgado, R., Castro, L., Cabrera, E., San Vicente, F.,Mújica, M., Canache, S.,

Navarro, L. & Noguera, I. (2008). Evaluación de algunas características

del sistema radical del maíz (híbrido inia 68) cultivado bajo labranza

mínima y convencionalen un suelo de maracay, venezuela. Agronomía

Tropical, 58(4), 427-438. http://ve.scielo.org/scielo.php?script=sci_

arttext&pid=S0002-192X2008000400012

Eranki, P. L., El-Shikha, D., Hunsaker, D. J., Bronson, K. F., & Landis, A. E.

(2017). A comparative life cycle assessment of ood and drip irrigation for

guayule rubber production using experimental eld data. Industrial crops

and products, 99, 97-108. https://doi.org/10.1016/j.indcrop.2017.01.020

Espósito, G., Culasso, V., Balboa, G., Castillo, C., Seiler, J. (2007). Producción de

Biomasa, Rendimiento y competencia entre plantas de maíz (Zea mays L.)

según su variabilidad temporal en la emergencia. Universidad Nacional

de Río. https://www.produccionvegetalunrc.org/images/fotos/839_89_

SEILER-Tesis.pdf

FAOSTAT. (2018). Organización de las Naciones Unidas para la Alimentación

y la Agricultura División estadística. Roma-Italia. https://www.fao.org/

statistics/es/

FAOSTAT. (2021). Organización de las Naciones Unidas para la Alimentación

y la Agricultura (Datos estadísticos FAOSTAT). https://www.fao.org/

statistics/es/

Giménez, L. (2012). Producción de maíz con estrés hídrico provocado en

diferentes etapas de desarrollo. Agrociencia (Uruguay), 16(2), 92-102.

http://www.scielo.edu.uy/scielo.php?script=sci_abstract&pid=S2301-

15482012000200011&lng=es&nrm=iso

Hidalgo Noel, A. O. (2013). Comportamiento de tres bioestimulantes en la

producción de maíz (Zea mays L.), híbrido XB-8010, en Tingo María.

http://repositorio.unas.edu.pe/bitstream/handle/UNAS/149/AGR-592.

pdf?sequence=1&isAllowed=y

Instituto Nacional de Estadística y Censos (INEC). (2021). Encuesta de Supercie

y Producción Agropecuaria Continua (ESPAC) 2020. Encuesta Nacional

de Empleo, Desempleo y Subempleo 2021. https://www.ecuadorencifras.

gob.ec/documentos/webinec/Estadisticas_agropecuarias/espac/

espac-2020/Presentacion%20ESPAC%202020.pdf

Lamm, F. R., Trooien, T. P., Manges, H. L., & Sunderman, H. D. (2001). Nitrogen

Fertilization FOR Subsurface Drip–Irrigated Corn. Transactions of the

ASAE, 44(3), 533. https://www.ksre.k-state.edu/sdi/reports/2001/dfert.

pdf

Moran, E., Cobos, F., Mora E., Lombeida, R. y Medina L. (2020). Sustentabilidad

del sistema de producción de maíz en la localidad de Ventanas, Ecuador

Journal of Science and Research, 5, 169-181. https://doi.org/10.5281/

zenodo.4425344

OCDE-FAO. (2019). Organización de las Naciones Unidas para la Alimentación

y la Agricultura. Perspectivas Agrícolas 2019-2028, 1-344. https://www.

fao.org/3/ca5308es/ca5308es.pdf

Plan de Desarrollo y Ordenamiento Territorial de la Provincia de El Oro. (2015).

PDOT 2014-2025. Gobierno Provincial Autónomo de El Oro-Ecuador.

https://multimedia.planicacion.gob.ec/PDOT/descargas.html

Rodríguez-Larramendi, L., Guevara-Hernández, F., Ovando-Cruz, J.,

Marto-González, J. R., & Ortiz-Pérez, R. (2016). Crecimiento e

índice de cosecha de variedades locales de maíz (Zea mays L.) en

comunidades de la región Frailesca de Chiapas, México. Cultivos

Tropicales, 37(3), 137-145. http://scielo.sld.cu/scielo.php?script=sci_

arttext&pid=S0258-59362016000300015

Sinha, I., Buttar, G. S., & Brar, A. S. (2017). Drip irrigation and fertigation improve

economics, water and energy productivity of spring sunower (Helianthus

annuus L.) in Indian Punjab. Agricultural Water Management, 185, 58-

64. https://doi.org/10.1016/j.agwat.2017.02.008

Chávez, R. G. T., Aguilar, R. V. L., & García, C. A. T. (2021). Riego decitario y

densidad de siembra en indicadores morfosiológicos y productivos de

híbrido de maíz. Revista ESPAMCIENCIA ISSN 1390-8103, 12(2), 131-

140. https://doi.org/10.51260/revista_espamciencia.v12i2.269

Tumbaco, T. (2019). Rendimiento de materia verde de dos híbridos de maíz para

ensilaje en la comuna Dos Mangas. Universidad Estatal Península de Santa

Elena, Ecuador. https://repositorio.upse.edu.ec/xmlui/handle/46000/4956

Uzátegui, T. (2019). Niveles de calcio en el rendimiento de tres híbridos de maíz

amarillo duro (Zea mays L.) bajo riego por goteo. Universidad Nacional

Agraria la Molina, Facultad de Agronomía. https://repositorio.lamolina.

edu.pe/handle/20.500.12996/3868

Vásconez, G. (2011). Determinación de las necesidades hídricas de tres híbridos de

maíz (Zea mays L.) bajo el efecto de tres densidades de siembra utilizndo

la reectometría de dominio de frecuencia. http://repositorio.ute.edu.ec/

handle/123456789/19265

Serra-Wittling, C., Molle, B., & Cheviron, B. (2019). Plot level assessment

of irrigation water savings due to the shift from sprinkler to localized

irrigation systems or to the use of soil hydric status probes. Application

in the French context. Agricultural Water Management, 223, 105682.

https://hal.inrae.fr/hal-02609656/document