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Revista mexicana de ciencias agrícolas

versão impressa ISSN 2007-0934

Rev. Mex. Cienc. Agríc vol.8 no.3 Texcoco Abr./Mai. 2017 


Agronomic response of hybrid maize to fertirrigation in Xalostoc, Morelos

Gregorio Bahena Delgado1  § 

Antonio Castillo Gutiérrez1 

Elizabeth Broa Rojas2 

María Dolores Olvera Salgado3 

Miguel Ángel Jaime Hernández4 

Francisco García Matías4 

1Escuela de Estudios Superiores de Xalostoc. Parque Industrial Cuautla. CP. 62715. (;

2Colegio de Postgraduados Campus Puebla. Carretera Federal México-Puebla, km 125.5. Santiago Momoxpan. CP. 72760. (

3Instituto Mexicano de Tecnología del Agua. Blvd. Paseo Cuauhnáhuac 8532, Progreso, Jiutepec, Morelos. CP. 62550. (

4Facultad de Ciencias Agropecuarias. Av. Universidad 1001, Colonia Chamilpa, Cuernavaca, Morelos. CP. 62209. (;


Small maize producers are unaware of the agronomic behavior of new genotypes in their work area and the use of technical irrigation systems. The objective of this paper was to evaluate the agronomic behavior of hybrid maize cultivated in fertirrigation. The study was carried out in the 2014 winter-spring cycle in the School of Higher Studies of Xalostoc. The number of leaves above the cob, total leaves, cob weight, cob diameter and grain yield were measured. A completely random block design was used. The best hybrid for leaves above the cob (6.46), total leaves (13.66), cob weight (206.88) and grain yield (7 613.3 kg ha-1) was H-377. It was confirmed that the new introduced genotypes should be evaluated and technification for water saving and yield raise is required.

Keywords: drip irrigation; fertigation; irrigation technification


Los pequeños productores de maíz desconocen el los nuevos genotipos en su zona de trabajo y el empleo de sistemas tecnificados de riego. El objetivo de este trabajo fue evaluar el comportamiento agronómico de maíces híbridos cultivados en fertirrigación. El trabajo se realizó en el ciclo invierno- primavera 2014 en la Escuela de Estudios Superiores de Xalostoc. Se determinó número de hojas arriba de la mazorca, hojas totales, peso y diámetro de mazorca y rendimiento de grano. Se utilizó un diseño de bloques completamente al azar. El mejor hibrido en cuanto a hojas arriba de la mazorca (6.46), hojas totales (13.66), peso de mazorca (206.88) y rendimiento de grano (7 613.3 kg.ha-1) fue el H-377. Se confirmó que deben evaluarse los nuevos genotipos y se requiere de tecnificación para el ahorro del agua y elevar los rendimientos.

Palabras clave: fertirrigación; riego por goteo; tecnificación del riego


Maize cultivation is one of the most important crops in the world after wheat and rice, in Mexico it is distributed in practically all ecological and edaphic regions. Like other crops such as beans, pumpkins, chili peppers, this cereal is the main food for Mexicans as it provides carbohydrates and protein to consumers. It is a traditional crop with great social and economic importance, is used by the agroindustry and animal feed for the elaboration of oils, fried foods, flour and other derivatives generating numerous jobs. Maize producers in Mexico grow eight million hectares a year, of which 1.5 million are irrigated, while 6.5 million are grown under temporary conditions (Turrent et al., 2012).

In the state of Morelos, corn is the second most important crop after sugar cane, since it is cultivated in an area of 29 268 hectares (INEGI, 2009). Of this, 1 614 ha are planted under irrigation conditions with an average yield of 3.63 t ha-1 and 25 401 ha are planted under temporary conditions with an average yield of 3.36 t ha-1, with the main use of improved varieties in both culture systems (SAGARPA-SIAP, 2014).

However, due to global warming and climate change, corn yields will be seriously affected by water scarcity, especially in arid and semi-arid areas comprising two-thirds of Mexico. It is estimated that at present time 15% of its territory, is highly exposed to the risk of direct adverse impacts of climate change (Landa et al., 2008).

The threat of global climate change will significantly affect the climatic factors essential to crop growth, such as precipitation and temperature, negatively impacting agricultural production. In semiarid areas, a greater frequency and severity of droughts and excessive heat are expected, conditions that can significantly limit crop growth and yield. Jones (2003) indicates that small corn producers could expect a decrease in productivity of around 10%, with strong regional variations where temperature and precipitation play a significant role in the availability of water for agriculture.

The consequences may be very profound for subsistence farmers located in fragile environments, where large changes in productivity are expected, as these farmers depend on crops that would be potentially heavily affected, for example, basic foods such as corn, beans, potatoes or rice (Altieri and Nicholls, 2009). Although important modeling of climate change has taken place in recent years, it is necessary to integrate uncertainty into the decision-making process and policy development (Schneider 2003) that defines preventive actions for food production purposes.

On the other hand, Nelson et al. (2009) mention that the temperature increase will end up reducing the production of the crops, as well as provoking the proliferation of weeds and pests. Changes in rainfall regimes increase the likelihood of short-term crop failure and long-term production reduction. Although some crops in certain regions of the world can benefit, the impacts of climate change are generally expected to be negative for agriculture, threatening global food security that could reach 9 billion people by 2050.

Therefore the actions to be taken in response to the climate change situation in the world are the transfer of technology mainly in irrigation systems, the validation of hybrids and varieties that adapt to the conditions that are expected to be changing in the different regions and, together with the construction of infrastructure in rural communities, are essential factors for small farmers to make more efficient use of available water and to increase yields to meet the feeding needs of both humans and animals. Therefore, this research aimed to evaluate the agronomic behavior of six hybrids recommended for the eastern region of Morelos cultivated in a drip irrigation system and fertirrigation technique.

Material and methods

The study was carried out during the 2014 winter-spring cycle in the experimental field of the School of Higher Studies of Xalostoc of the Autonomous University of the State of Morelos, located in the Ejido de Xalostoc, municipality of Ayala Morelos, geographically located in the coordinates 18° 44’ 36.30” north latitude and 98° 54’ 31.88”west longitude with respect to the Greenwich meridian, with a height of 1 294 masl (Google Earth, 2015) (Figure 1).

Figure 1 Location of the experiment.  

The predominant climate is warm, low humidity, rainfall ranging between 720 and 820 mm and has an average annual temperature of 24 °C, the wind has a direction from northeast to southwest (INAFED, 2012). The ground preparation consisted of fallow, crawling and furrowed with mechanical traction. Furrows were at a distance of 1 meter. The installation of the irrigation system was done once the soil was finished. The secondary lines of PVC pipe were drilled, the pipe was drilled with a 5/8 drill bit, gaskets, initial connectors, blind tube, quick connectors and strap were placed, and the system was then tested to observe its adequate functioning. Later, stakes were placed at the end of the groove and the final plugs at the belts to then tie them and prevent them from moving due to temperature and wind. The selection of hybrids to be evaluated in fertirrigation was done by the seed supply by INIFAP-Zacatepec (Table 1).

Table 1 Vegetative material evaluated in fertirrigation 2014 winter-spring cycle, Experimental field School of Higher Studies of Xalostoc of UAEMOR. 

Seeding was carried out at a distance of 30 cm between plants, depositing two seeds per bush, having a density of 66 666 plants per hectare. For weed control, glyphosate was applied at a rate of 2.5 l of i.a. ha-1 and for weeds that could cause a problem to the crop was applied Gesaprim caliber 90 in preemergence at the rate of 2.5 kg of i.a. ha. Subsequently, to control weeds postemergently, 2-4-D amine was applied at a rate of 1.5 l of i.a. ha-1. The application of water was done through the drip irrigation system. To calculate the amount of water that was used, the indirect method was used considering the average monthly evaporation and the crop phenology, using the following formula:


Where: ETC= maximum monthly evapotranspiration, mm; ETo= evapotranspiration of the reference crop, mm; EV= evaporation in mm; Lr = irrigation sheet in mm; Kc= coefficient of adjustment in function of the vegetative development of the crop; using the unique Hansen curve, dimensionless; Kp= coefficient of the “A” evaporimeter tank (0.75) (Doorembos and Pruit, 1977); Ea = application efficiency of the irrigation system, dimensionless.

The fertilization was carried out with the general formula 140-160-180, applying the fertilizer at the time of irrigation according to the phenological stages of the crop. Employing soluble fertilizers. Initial 15-30-15, development 18-6-18, growth 25-10-10, production 13-6-40. The spiderworm (Spodoptera frugiperda) was present, but there was not significant damage and no insecticide was applied. The experimental design used was randomized complete blocks with six treatments and three replicates. The experimental plot consisted of 20 m2 with four furrows of five meters long. Plant and cob variables were measured using the descriptors for corn of CIMMYT (IBPGR, 1991). The variables were: leaves above the cob. Ten plants were counted per entry, after the milky state when physiological maturity was reached. Total sheets. They were counted on 10 plants after both male and female flowering. Cob diameter (mm). Ten cobs were measured with electronic vernier in the center of the cob. Number of rows. The total number of rows was counted in 10 cobs in the central part. Cob weight (g). Ten cobs were weighed with using Torrey electronic scale SX-B30 model.

Performance. In order to calculate grain yield, the formula of Combe and Picard (1994) was used.

R=NPha-1*NP P-1*NG M-1* Plg

Where: R= yield in kg ha-1; NP ha-1= number of plants ha-1; NP P-1= number of cobs per plant; NG M-1= number of grains per cob; P1g= specific weight of a grain.

Harvesting was done manually by harvesting the two central furrows of each experiment and then stripped when the grain had an approximate humidity of 14%. Regarding the Analysis of data, analysis of variance for the six variables was calculated. The comparison of means between treatments was carried out with the Tukey test at 5% of significance. Statistical Analysis System (SAS) version 9.4 was used for statistical and correlation analysis.

Results and discussion

The results obtained from the analysis of variance at (p≤ 0.05) probability for the evaluated variables are shown in Table 2, which shows that there were significant statistical differences for all variables. The hybrid with the highest number of leaves above the cob was the H-377 with an average of 6.4 and the lowest number of leaves above the cob was the H-515 with an average of 5.4, the others oscillated in a range of 5.6 and 6.1.

Table 2 Average values of the evaluated hybrids characteristics in fertirrigation in Xalostoc. 

HRMZ= hojas arriba de la mazorca; HT= hojas totales; PM= peso de mazorca; DM= diámetro de mazorca; NHI= número de hileras; RG= rendimiento de grano.

This indicates that although they are improved materials and have a more homogeneous genetic base, they respond differently to management, levels of fertilization, irrigation, weed control, pests, diseases and environmental conditions for which they have to be evaluated in environments different from the origin place so that the producers have reliable information to determine which vegetative material to acquire and to establish them in their culture plots.

The coefficient of variability (CV), used as a measure of precision in conducting experiments (Wong et al., 2007) for grain weight was 21.9%, considered as acceptable. The CV of the other characteristics fluctuated between 2.3 and 8.9%, so the data management is considered adequate and homogeneous.

These results indicate that one of the characteristics of agronomic importance is the number of leaves that the corn plant can develop since they are the ones that provide photosynthesis necessary for the physiological activity of the plants, so that the leaves above the cob are more important than the number of leaves below the cob because they are responsible for capturing more solar radiation and as a consequence directly influence the size of the grain and increase in yield since they are the youngest leaves of the plant and are the ones with the highest photosynthetic rate. These results coincide with those reported by Fischer et al. (1987), who found that in tropical corn populations the number of leaves and greater leaf area above the cob resulted in a significant increase in grain yield. Lambert (2010) considers that leaves are the site of photosynthesis and constitute a factor that contributes to the biomass production and grain production.

The leaves above the cob and the cob leaves are the youngest in the plant, so they have the highest photosynthetic rates and are kept longer (Thiagarajah et al., 1981), as well as the leaves above the cob are the ones that contribute in greater proportion the photoasimilates to the cob during the grain filling (Tollenaar, 1977), in contrast the leaves below the cob do not contribute great amount of photoasimilates since they are in the shaded area , in addition to the senescence that they show since they are the first leaves to appear (Dwyer and Stewart, 1986).

As for the total leaves number variable, the results of the analysis of variance at (p≤ 0.05) detected significant differences among the evaluated treatments, the hybrid with the highest number of leaves was the H-377 with 13.6 and the one with the least amount of leaves was the H-443 with an average of 12.3 leaves, showing a reduction of 30 and 35% of leaves regarding to the behavior of the materials in their place of origin (20 leaves). This is probably due to the fact that the place where the materials come from is a region with a higher temperature which influences the plant to emit a larger number of leaves when there is more solar radiation. Although at the end of the productive cycle of the plant the leaves of the lower part are not so important due to the senescence and little amount of photo-assimilates that they contribute, if they grow before the time of formation of male and female flowers which are the ones that provide the greatest amount of photosynthesis for growth and development. The total of leaves that the plant forms during its productive life influences considerably the pollination, a better grain filling, and therefore into a greater yield.

These results coincide with those reported by Ospina et al. (2012) who recorded an average of 12 to 14 leaves in hybrids evaluations and considered that temperature is the factor that influences the most in the amount of total leaves produced by the plant, while other factors such as lack of water or nutrients, affects to a lesser extent this characteristic. While INTA (2006) mentions that the production of grains of a crop will depend on its ability to grow (produce biomass) and provide that biomass to the grains. In order to do this it must develop its foliar apparatus and intercept the maximum possible radiation and reach the maximum growth rate a few weeks before flowering; in addition the photosynthetic apparatus must prolong its activity to ensure a good grain filling (late leaves senescence) and must generate properly their reproductive structures.

For the cob diameter variable the results of the analysis of variance show that there were statistically significant differences (p≤ 0.05) among the evaluated treatments. The hybrid that had the best behavior in this variable was the H-382 with an average cob diameter of 51.03 mm and the one that presented a smaller cob diameter was the H-443A with an average of 42.38 mm. This behavior is probably due to the effect of the fertilizer application according to the phenological stages of the plants, distance between rows, distance between plants and density of planting, since when there was a single plant per bush, bigger cobs both in length and diameter were obtained, as well as genotypic differences among the evaluated materials. Also, it is considered that the corn production under irrigation conditions provides the adequate amount of water at the time of male and female flowering and because of this there is a greater pollination and fertilization of the cob ova, influencing the cob diameter in the weight of grains.

These results coincide with those reported by Otahola and Rodríguez (2001) who found that the greatest diameter of cobs were obtained when they sowed the plants at 0.90 m between rows. While Vásquez (1998) found that the largest diameter of the cob was obtained by planting the plants at a distance of 0.2 and 0.25 m. On the other hand, Chura and Tejada (2014) found a higher correlation between the cob diameter with the yield in yellow corn, since the greater cob diameter correspond to a greater number of grains per row and it results in a higher yield.

For the number of rows per cob variable the results of the analysis of variance indicated that there were statistically significant differences (p≤ 0.05) among the treatments evaluated. The largest number of rows was shown by the H-374C with an average of 17.8 rows and the lowest number of rows was shown by the H-515, the other evaluated materials fluctuated in a range of 14.4 and 15.4 rows. This behavior was probably due to the topological arrangement of the plants in the field, the vigor of the plants, adequate irrigation sheets, adequate pest control, weeds and adequate levels of fertilization according to the phenological stages of the plants, besides planting more distance between furrows and between plants has a better use of sunlight and the plant produces more nutrients, resulting in longer cobs, with bigger diameter and greater number of rows, being one of the desirable characteristics in the cobs to increase crop yields, since there is a direct relationship between the number of rows and the amount of grain per cob.

These results coincide with what was found by Díaz et al. (2009) who reported up to 15.5 rows per cob for hybrid materials. On the other hand, Cervantes et al. (2014) found hybrids with a range of 12.7 to 16.6 rows in average per cob and that one of the factors that influences the number of rows is the initial vigor of the plants.

For the cob weight variable, the results of the analysis of variance showed statistically significant differences (p≤ 0.05) among the treatments evaluated. The largest weight of cob was shown by the H-377 with 206.8 g and the lower weight was presented by the H-374C with 142.5 g, because the cobs were smaller. And probably the grains contain more flour. The remaining materials were in the range of 201.3 to 147 grams. The obtained results show the effect of the environment, irrigation, fertilization by phenological stages, pest control, weeds, high temperatures favoring high photosynthesis, nutrients, planting density and growth rate on this yield component.

This indicates that when the production factors are handled properly, mainly the quantity of water and nutrients at the time of the pollination and formation of the grain bigger cobs are obtained, with greater weight and heavier grains, which influences notably in the yield. Similar results were reported by Faiguenbaum (1997) who found that in a well-managed and harvested crop with optimum maturity an average weight of cobs of between 380 and 400 g can be achieved. Luchsinger and Camilo (2008) found that the weight of cobs is strongly related to the influence of the environment, planting density, plant height, planting season and number of cobs per hectare, obtaining individual weights of cob ranging between 274 and 391 g.

As for the results of the analysis of variance, it shows that there were statistically significant differences between the yield of the evaluated hybrids. By comparison of means (Tuckey 0.5) of probability it was found that the best material in terms of grain yield was treatment four (H377B) with 7 613.3 kg ha-1 followed by treatment one (H-515B), with 7 350 kg ha-1 and the lowest yield was treatment 3 with 3 643.3 kg ha-1, far below the state average for corn; however, 83% of the treatments (hybrids: H377B, H-515B, H516B, H-382B and H-443a) exceeded the state average for irrigation corn of 3.5 t ha-1 (CONAGUA, 2014) as shown in Figure 2.

Figure 2.Grain yields obtained in corn genotypes. Generated from research and information from CONAGUA (2014).  

These results are probably due to the fact that corn responds to optimal levels of fertilization with nitrogen, phosphorus and potassium according to the phenological stages of the plants, suitable irrigation sheets mainly in the formation of the male and female inflorescence stage and at the pollination moment, high luminosity indexes for the elaboration of photo-assimilates, as well as the effect that the environment has on the plants growth. Similar results were found by Cirilo and Andrade (1996) who consider that in general the grains weight can represent about half of the total aerial parts of the plant (crop index), as well as the relation that exists between the growth of early flowering plants and the period of grain filling due to the intense assimilation of nitrogen. While Salazar and Martínez et al. (2009) found that the weight of corn grain is 80% influenced by the environment.

The results of the correlation analysis (Table 3) to which the study variables were subjected showed that there was a strong correlation between leaves above the cob with the total number of leaves (63%), a moderate correlation was also found with cob diameter (22%) and number of rows per cob (22%), this is important since these characteristics directly influence grain yields because leaves provide the highest amount of nutrients. As for the total number of leaves, there was a strong correlation with leaves above the cob (63%), since the same character is being measured and a moderate correlation with grain yield (25%), since the leaves are a factor that affects yield but other factors such as fertilization and the amount of water available to achieve a higher yield are also present.

Table 3 Correlation coefficients and level of significance for each of the possible pairs of characters evaluated in 2014 winter-spring-cycle of corn hybrids. 

**= significativo al 0.01 de probabilidad; ns= no significativo. HRMZ= hojas arriba de la mazorca; HT= hojas totales; PM= peso de mazorca; DM= diámetro de mazorca; NHI= número de hileras; RG= rendimiento de grano.

As for the cob diameter variable there was a very strong correlation with the cob weight variable (85%) theses are variables that are directly related since when a greater cob diameter exists there will be a greater cob weight, as well as a strong correlation with rows number (56%) and a moderately strong correlation with grain yield (34%). As for the grain yield variable a moderately strong correlation was found with the cob weight (46% and with cob diameter (34%).


Four genotypes of white corn and two genotypes of yellow corn were studied, of which the hybrids that achieved the highest yield and adaptation in this studied region were those of white color, surpassing the average yields at both state and regional levels.

The 377B hybrid was the genotype that showed the greatest adaptation and response in terms of average yield in this region, exceeding 52% of the average yield of corn grain.

On the other hand, the hybrid 443A of yellow grain, showed a good behavior in terms of yield and may be an option for producers in the region, whenever the market is secured.

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Received: January 2017; Accepted: April 2017

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