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Cultivos Tropicales

versión impresa ISSN 0258-5936versión On-line ISSN 1819-4087

cultrop vol.40 no.1 La Habana ene.-mar. 2019

 

Original Article

Variability of the yield in soybean cultivars (Glycine max L.). Part I. Time of cold

Ing. Osmany Roján-Herrera1  * 

Dr.C. Lázaro A. Maqueira-López1 

Dr.C. Walfredo Torres-de la Noval1 

1Instituto Nacional de Ciencias Agrícolas (INCA), carretera San José-Tapaste, km 3½, Gaveta Postal 1, San José de las Lajas, Mayabeque, Cuba. CP 32 700

ABSTRACT

The research was developed in the areas of the Base Technological Science Unit, Los Palacios, Pinar del Río, belonging to the National Institute of Agricultural Sciences. Four soybean cultivars were used (DV-5, DVN-6, DT-84, D-2101), which were sown on three different sowing dates (December 2011, January 2012 and December 2012), corresponding to the cold season, on a Hydromorphic Gley Nodular Ferruginous Petroferric soil. The objective was to evaluate the variability of yield in soybean cultivars (Glycine max (L.) Merrill), associated to meteorological variables according to date of sowing in the cold season. A randomized block experimental design with three replications was used, and the agricultural yield and its components were evaluated, as well as meteorological variables (temperatures, solar radiation, relative humidity), in different phenological stages of the crop cycle. Taking into account the results obtained, the highest values of agricultural yield correspond to the highest values of temperature and solar radiation (December 2012), reaching a better result the cultivar D-2101 with a value of 2.31 t ha-1. The components most associated with yield were the number of pods / plants and the number of grains / plants for the three planting dates in general. Of the climatic variables evaluated, the ones that most influenced the different phases were temperature and solar radiation.

Key words: meteorological variables; phenology; grains

INTRODUCTION

Soybean (Glycine max (L.) Merrill) is the most cultivated oilseed and the fourth most produced grain after corn, wheat and rice. The world produces an average of 176.6 million tons of soybeans per year over a surface area of 75.5 million ha 1, with the United States, Argentina and Brazil accounting for 80 % of this volume, which explains why America is the continent with the highest production worldwide with 85.32 %, followed by Asia, which represents 12.78 % 2. Despite the fact that in Cuba, soy is known since the beginning of the 20th century, it has not yet been possible to stabilize its production, since around 20,000 hectares are planted and only 35 % of the national demand is satisfied that forces the country to import some 600,000 tons per year 3.

However, soybeans are subject to many abiotic stresses that reduce their yield 4, as do most economically important crops, because in order to achieve stable yields over time or increase them, it is important to take into account the interaction between genotypes and the environment (climate, soil and management practices). It is possible that any variable that produces effects on the environment in crop productivity will be reflected (5. In works carried out in order to address the stability of yield in different soybean cultivars, it has been determined that even in high production sustainable systems; there is great variability of it. Therefore, in order to achieve high yields, it is necessary to select those cultivars that have a high average productivity (adaptation) and to know their probable variation between environments (stability) 6).

Similarly, several investigations worldwide assess the incidence of climate in relation to the planting date 7. This aspect is important to point out, because most of the meteorological variables, such as temperatures and solar radiation, affect the growth and development of crops positively or negatively, while modifying their environment and altering the production of both dry matter as the yield 8.

In correspondence with the above criteria, it is necessary to know the main factors that cause variability in the yield of the soybean crop, so the present work with the objective of evaluating the variability of yield in soybean cultivars (Glycine max (L.) Merrill) associated with meteorological variables according to the sowing date in the cold season was developed.

MATERIALS AND METHODS

The experiments were carried out at the Base Scientific and Technological Unit, Los Palacios (UCTB-LP), belonging to the National Institute of Agricultural Sciences, located on the southern plain of Pinar del Río province of, at 22 ° 44 'North latitude. and at 83 ° 45 'West latitude, at 60 m asl, with an approximate slope of 1%. Four soybean cultivars of Vietnamese origin (DVN-5, DVN-6, DT-84, D-2101) were evaluated, which were sown on three different sowing dates; December 2011, January 2012 and December 2012, corresponding to the cold season.

The soil of the experimental area is classified, according to the New Version of Genetic Classification of Soils of Cuba 9, as Hydromorphic Gley Nodular Ferruginous Petroferric. As results of the soil sampling of the experimental area, some properties that characterize its fertility are shown (Table 1).

Table 1 Some properties of the arable layer (0-20 cm) that characterize the fertility of the soil where the experiments were developed 

pH H2O Ca++ Mg+ Na++ K+ P2O5 MO
cmol kg-1 soi l Mg 100 g-1 of soil %
6.49 7.01 3.13 0.16 0.23 20.47 2.72

The main characteristics of the cultivars under study are presented in Table 2 3, which were sowed by direct seeding at a distance (manual), of 0.70 m between rows and 0.07 m between plants, with a standard of 54 kg ha-1 of seeds. The phytotechnical work was carried out as recommended in the Technical Manual of Soybean Cultivation 10. An experimental randomized block design was used with four treatments (the cultivars) and three replications. The experimental plots had an area of 30 m2.

Table 2 Main characteristics of the cultivars of soybean studied in the experiments 

DVN-5 DVN-6 DT-84 D-2101
Yield (t ha-1) 3.5-3.0 3.5-3,0 2.5-3.0 2.0-3.0
Number of pods/plant 61-51 60-53 23-47 25-55
Number of grain/plant 121-110 100-89 54-110 70-123
Mass 1000 grains (g) 170.0 173.0 170.0 180.0
Sowing time Spring-Summer Spring-Summer Winter-Spring Winter-Summer
Cycle (days) 92-100 95-100 90-92 90-95

Figure 1 shows the maximum, minimum and average daily temperature (T max, T min, T ave), precipitation, global solar radiation (RSG) and relative humidity (Hr), from the period in which the experiments lasted, which were obtained from the Paso Real meteorological station of San Diego, in Los Palacios.

The thermal sum or cumulative day degrees (GDA) was calculated by the following method 11:

GDA= n ((T max. + T min.)/2)  T base

Where in this case was selected as the base temperature at 10 ° C and n the number of days in the period considered.

In each experimental plot at the time of harvest, ten representative plants were taken at random, always respecting the edge area and were determined:

Agricultural yield (t ha-1, adjusted to 14% humidity) (Yld).

Number of pods per plant (Nu pods).

Number of grains per plant (Nu grains).

Mass of 1000 grains (Mass 1000).

To determine the agricultural yield, 8 m2 of the center were harvested in each experimental plot, the plants were threshed and the grains were dried until they reached 14 % humidity. Regarding the number of grains and number of pods, the value of each variable in the ten plants per plot was counted.

The three sowing dates were climatically characterized through a principal components analysis with said variables, dividing the crop cycle into three periods: Ve-R1, pre-flowering stage and beginning of flowering; R1-R5, early reproductive stage in which most of the fruits are established and seeds begin to fill, and the third stage is R5-R7, period of seed filling 12.

The means of the evaluated variables obtained by cultivating and date of sowing, were subjected to analysis of variance (ANOVA), and the significant differences between the means were determined with the Fisher LSD test (p <0.05). Several matrices of data were constructed which were processed by the multivariate technique of Principal Components, by means of the representation of a Biplot. The statistical package InfoStat version 2015 was used 13.

Figure 1 Temperatures (maximum, average, minimum), rainfall, global solar radiation and relative humidity, taken from the Paso Real Agrometeorological Station of San Diego, during the period of the experiments 

RESULTS AND DISCUSSION

The results of the agricultural yield appear in Figure 2, observing a variation between dates of sowing and between cultivars, so it was found that it is difficult to establish a behavior pattern from the role played by the interaction with weather conditions, to the time to define this indicator for a particular cultivar.

On the dates of January and December 2012 the cultivars (DVN-5, DT-84, D-2101) reached the best performance, with statistically significant differences with respect to the sowing of December 2011. The cultivar DVN-6 showed differences in the behavior of this variable between dates, however, DT-84 was the lowest performance on the date of December 2011.

Figure 2 Agricultural yield (t ha-1) at 14 % humidity of soybean cultivars sown in the three dates under study 

This variability of the cultivars in the different sowing dates can be related to the response of these to the behavior of the meteorological variables, which play a fundamental role in the productivity of the crop 14. In this regard, it should be noted that the temperatures on the dates of December and January 2012 (Figure 1), were relatively higher than those of December 2011, so this result corroborates what was stated by some authors, where they affirm that the yield in the cultivation of soybeans are influenced during the whole cycle by temperatures (15.

Also, other studies carried out with the purpose of explaining the variability of yield in soybean cultivation, base their principle on the fact that variations in the yields of this crop may be a consequence of the different availability of radiation 16. This may be the reason why the cultivator DT-84, despite being recommended for the cold season (Table 2), shows the lowest yield values in December 2011, since on this date where the lowest values were recorded of solar radiation (Figure 1). In Cuba, agricultural yields vary significantly between seasons and sowing dates (10). In this sense, works carried out in other crops show that the yield is positively and linearly related to the sowing date, depending on the cultivar and the environment 17.

Also, other studies carried out with the purpose of explaining the variability of yield in soybean cultivation, base their principle on the fact that variations in the yields of this crop may be a consequence of the different availability of radiation 16. This may be the reason why the cultivator DT-84, despite being recommended for the cold season (Table 2), shows the lowest yield values in December 2011, since on this date where the lowest values were recorded of solar radiation (Figure 1). In Cuba, agricultural yields vary significantly between seasons and sowing dates 10. In this sense, works carried out in other crops show that the yield is positively and linearly related to the sowing date, depending on the cultivar and the environment 17.

When analyzing the behavior of the main components of yield (Table 3), it was possible to demonstrate the differences of these variables, both between cultivars and between sowing dates. Regarding the mass of the grains, the cultivars reached the highest values on the date of December 2011 and lower on the dates of January and December 2012 where the best yields are shown. This contradiction that exists between the yield and its components can be given by the compensatory character that certain crops have in increasing the mass of their grains when the number of pods and grains is low 18.

Table 3 Behavior of the main yield components of soybean cultivars in the different sowing dates studied 

December 2011
Cultivars Nu. pods Nu. grains Mass 1000
DVN-5 16.3-26.3 20.2-30.8 192.9-236.1
DVN-6 18.4-28.4 21.0-31.6 151.3-194.5
DT-84 10.2-20.2 11.6-22.2 184.7-227.9
D-2101 20.4-30.4 27.6-38.2 166.1-209.3
Esx. 2.55* 2.68* 11.00*
January 2012
Cultivars Nu. pods Nu. grains Mass 1000
DVN-5 30.6-40.6 35.7-52.1 137.7-152.7
DVN-6 27.8-37.8 21.9-38.3 132.2-147.2
DT-84 18.4-28.4 38.4-54.8 151.9-166.9
D-2101 33.3-43.3 58.4-74.8 150.5-165.5
Esx. 2.57* 4.2* 3.84*
December 2012
Cultivars Nu. pods Nu. granos Mass 1000
DVN-5 25.7-36.5 35.8-58.4 163.9-190.9
DVN-6 17.00-27.8 19.4-42.0 147.2-174.2
DT-84 24.7-35.5 39.5-62.1 130.8-157.8
D-2101 35.9-46.7 68.8-91.4 118.3-145.3
Esx. 2.73* 5.79* 6.9*

Confidence interval calculated to 95 % of probability using the mean and having into account the experimental error of variance analysis

With respect to the number of grains, the cultivars reached the best responses in the sowing date where the highest value of yield were achieved for this reason this component should have a main role in the determination of agricultural yield. Some studied has showed that a wide range of agroeconomic conditions, the number of grains is the best component that explain the yield variations 19. On the other hand, when analyzing the cultivars independently, it is possible to highlight that in the three sowing dates the cultivar D-2101 reached the best response of this variable and it coincided with the highest value of yield reached in edaphoclimatic conditions where these experiments took place. Similar results in other studies in Cuba have been obtained where an excellent behavior of this cultivar during this season 3.

The behavior in the number of pods was similar to the number of grains that is an important element in the formation of yield, although some authors identify it like an indirect component of yield 15. In literature is highlighted the number of pods is the first component to define in the R3-R4 stage. As the number and mass of grains is in correspondence with the fluctuations in the environment from this the importance of making to coincide the stage, in which these components with the best environmental conditions although it will be hard to manage at practice are decided 20.

Besides, soy has the capacity to fix reproductive structures for a long time 21, showing in the study that an eventual decreasing in the number of pods can be balanced partially, for an increasing in the grain mass. It is important if each component could be affected with different intensity for the environment of each development stage.

From the results related to the association of agricultural yield and its components, it was determined that the most influent were the number of grains/plant and the number of pods/plants, in general form to the three sowing dates studied. It is presented in the analysis of main components where the components 1 (CP1) and 2 (CP2) explained 90 % of the total variability (Figure 3).

Mass 1000: mass of 1000 grains (g). Yield: Agricultural yield (t ha-1). Nu. grains: Number of grains per plants. Nu. pods: Number of pods per plants

Figure 3 Association of the agricultural yield of soy cultivars with the obtained variables on the first and second component in the three sowing dates studied 

The mass of the grains had a high angular separation respect to the grain and pod number and yield. It indicates that under these conditions while increase the number of pods and grains decrease mass of the same ones and vice versa, what it is appreciable again the compensatory level among these variables. Other authors studies the positive and significant association of yield and its main components where it could be to appreciate that the number of grains and pods are the components, which are associated to yield 22. This type of analysis was exposed in soy cultivars one more time in studies, of different maturity groups 16. Furthermore, all this offer the possibility of many and different genotypes can reach similar yields in the same environment, and a genotype can have different yields in different environments 5, overall for the influence that can exerted in the behavior of meteorological variables in the phenological stage where each one of the components are decided.

The duration of phenological stages, explain partially the morphological component generation of yield, then when analyzing the association among the different meteorological variables with the duration in days, in each one of the studied stages for the three sowing dates in general, the existent differences among them (Figure 4)

In the phenological Stages Ve-R1 (5-30 days after emergence), the most positive association with the duration in days for solar radiation were reached. It should contribute to the stimulation of plant growing for a greater availability of solar radiation.

About this, some authors express that a higher efficiency of the radiation in this stage, stimulate a greater rate of crop growing that can be appreciated in an increasing in the number of nods and then in the number of pods and yield 23. However, the amount of pods achieved by the cultivars studied in the sowing dates in January and December 2012, coincide with the greater values of solar radiation of this stage.

D days: duration in days (days). GDA: degree accumulate days (0 C). RSG: global solar radiation (MJ.m-2). T min: minimum temperature (0 C). T med: Mean temperature (0 C). T max: maximum temperature (0 C). Hr: relative humedity (%)

Figure 4 Association of the main meteorological variables with the duration in days of the cultivars of soy in each one of the phenological stage studied for the three sowing dates in general 

On the other hand, the clearest association to the duration in days in the phenological stage R1-R5 (30-45 days after emergence), was given by solar radiation and temperatures. This must be related to the fact that on the date of December 2011, a low number of grains was obtained, since the average temperature in this stage (stage where the number of grains was decided), kept values below the 25 0C. It has been suggested in the literature that soybean cultivars may exhibit a different behavior in terms of temperatures, however, some results have shown that, in order to increase the number of grains per unit area, average daily temperatures higher than the average 26 ° C 6,24.

However, other authors state that stress by temperatures at the end of the cultivation critical period (R5) (higher than 30 °C) can modify the stability of the cells of the membranes, which affects several metabolic processes in particular photosynthesis and cellular respiration 25, at the same time that they could generate a decrease in the mass of the grains 6.

About the association of solar radiation with the duration in the days of this stage, some studies highlight, the importance that have the influence of the same during the critical period of crop (R1-R5),

close to the association of solar radiation with the duration in days of this stage. Some studies highlight the importance of the influence of the same during the critical period of the crop becoming a relevant characteristic because the production environment during this stage , conditions the growth rate of the crop, determining the number of grains as the main component of yield 26. The basis of this hypothesis is that solar radiation has a high positive association with the number of grains / m2 (15.

As for phase R5-R7, there was no association with the variables studied, so in this case it is not possible to establish a pattern of behavior. There are contradictions in many studies, since some authors suggest that the rate of development after R5 is more affected by the photoperiod than by changes in temperature and radiation 23. However, other authors state that the prevailing conditions in terms of humidity, temperature and solar radiation are of vital importance in this phase, since cultivars with a high number of grains combine these variables in different ways, determining different physiological strategies that are equally successful 27. . It is also established that temperature generally has a positive influence on the rate of development of the crop, which means that all crops and all stages of development are sensitive to temperature 6. It cannot be ruled out that, based on studies that clarify these aspects, new genotypes can be identified that allow a better analysis of the relationship between phenology and environmental conditions as a variability factor, opening new routes to increase crop yield. soy.

About the association of solar radiation with the duration in days of this stage some studies highlight, the importance that have the influence of the same during the critical period of crop (R1-R5),

CONCLUSIONS

Based on the results, it can be concluded that the highest values of the agricultural yield were found on the date of December 2012, although in a general way the cultivar D-2101 was the one with the best performance in all the sowing dates studied. The number of grains / plant and the number of pods / plant were the components that most influenced the expression of yield. From the meteorological variables studied, they proved to be the most influential in the duration of the stages, the solar radiation in the stage Ve-R1, R1-R5, and the temperatures in the stage R1-R5. Radiation and temperature play an important role in the formation of the yield, due to its influence in the determination of the mass and the number of grains. The duration in days of the phenological stage R5-R7 was not associated to any of the meteorological variables analyzed.

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Received: June 04, 2018; Accepted: December 05, 2018

*Author for correspondence. orojan@inca.edu.cu

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