The growth of world population and increase of the demand for food pose important challenges for agriculture, where production will have to increase in 60% by 2050. For this, it would be necessary to use areas in the process of degradation and desertification, with the scoop to produce more, using fewer natural resources (water and soil), and using tolerant and adaptable varieties to the changing climate. Therefore, the objective of agriculture must consider productivity, rural development, environment and social justice (Morales-Velazco et al. 2016).
Productivity of livestock systems has tended to decline, as a consequence of the implementation of inappropriate systems and the use of low fertility soils, in which naturalized or non-adapted species were planted, generating little productivity (Tapasco et al. 2015).
On the other hand, it has been estimated that around half of pastures are degraded to some degree, caused by several reasons, or combinations of them, such as introduction of forage species, not adapted to the region, poor pasture management, soil compaction, erosion and fertility reduction, among other aspects that further reduce livestock productivity in the region (Arango et al. 2016).
In Latin America, it is considered that it is not economical to feed cattle with concentrates and it is decided, as a practical way to increase food production for ruminants, the planting of new species of pasture and forage with greater adaptability and productive potential. This can be obtained by improving the species used for this purpose, and from those that often have high quality and are not used in animal feed (Ramírez et al. 2017).
Hence, the introduction of new species and varieties of higher yield and quality such as Megathyrsus maximus, in several regions of Ecuador, is necessary to improve the low production and quality of naturalized pastures, abundant in livestock production systems. However, its productive potential, chemical composition, digestibility and energy contribution are not known, as well as its adaptability in different climatic areas. Therefore, the objective of the current study was to evaluate the effect of climatic area on indicators of yield and quality of three varieties of Megathyrsus maximus.
Materiales y Métodos
Location. The current research was carried out in Orlando Varela farms, located at kilometer one of El Empalme-Balzar road, left side, Democracia sector, El Empalme canton and El Mamey, located at El Ají sector, Parroquia del Guayas, Guayas province, Ecuador. They are located at 01° 06´ S and 79° 29 W, at 73 m.o.s.l. and 01 ° 00´ S and 79° 30 W, at 75 m.o.s.l., respectively. The study was carried out in the period between July- September (dry season), 2015.
Agrometeorological conditions. The climate is classified as humid subtropical (García 2004). In Guayas, mean precipitation was 2,436.9 mm/year (117.2 mm during the experimental period), mean temperature was 23.87 ° and relative humidity was 79 %. In El Empalme, mean precipitation was 2,229.60 mm/year (245.6 mm during the experimental period), 25.80 °C of mean temperature and 86 % of relative humidity. Soil of both areas is inceptisol (Soil Survey Staff 2003) and its chemical composition appears in table 1.
Indicator | Guayas | El Empalme |
---|---|---|
5.47 | 5.83 | |
|
1.50 | 3.16 |
|
5.1 | 2.78 |
|
0.54 | 0.16 |
|
1.50 | 1.20 |
|
0.80 | 0.23 |
24.00 | 22.00 | |
56.00 | 58.00 | |
20.00 | 20.00 |
Treatment and experimental design. A random block design was used, with factorial arrangement (3x2): three varieties of Megathyrsus maximus (Común, Tanzania and Tobiatá) and two areas (Guayas and El Empalme) and five replicates.
Procedure. The experimental plots (5x5 = 25m2) were sown with Megathyrsus maximus cv. Común, Tanzania and Tobiatá in February 2015, at 50 cm between furrows and 20 cm between plants. Plants had an establishment period until July, when the uniformity cut was performed. From there, samplings were carried every 42 days of regrowth, removing 50 cm of border effect and all the material in the harvest area was cut at 10 cm above ground level. Biomass production, total dry matter yield, of leaves and stems were evaluated, as well as number of leaves and stems (per cutting), leaf length and width and leaf-stem relationship (Herrera 2006). Then, two kilograms (two samples) were taken per each treatment and per replicate for subsequent analysis in the laboratory.
Irrigation was only used for facilitating germination and establishment, and no fertilization or chemical treatment was used to remove weeds. At the beginning of the experiment, the population of varieties in the plots was 97 %.
Determination of chemical composition. Samples, after collected, were dried in a forced air circulation oven at 65 °C. Then, they were ground to a particle size of 1mm and stored in amber flasks until their analysis in the lab. There, DM, CP, ash, OM, P and Ca, according to AOAC (2016), were determined, as well as NDF, ADF, ADL, cellulose (Cel), hemicellulose (Hcel) and cellular content (CC) according to Goering and Van Soest (1970), dry matter digestibility was quantified by Aumont et al. (1995) and metabolizable energy and net lactation were established according to Cáceres and González (2000). All analyzes were performed in duplicate and per replication.
Statistical analysis. Analysis of variance was performed according to the experimental design and mean values were compared using Duncan (1955) multiple range test. Kolmogorov-Smirnov test (Massey 1951) was used for determining normal distribution of data and Bartlett (1937) test for the variances.
Results
Variety x area interaction (P <0.05) was found for all yield indicators. The highest yield of total dry matter, of leaves and stems (2.17, 1.25 and 0.92 t/ha, respectively) was obtained with Tanzania variety in El Empalme. Biomass production showed a similar performance with 6.97 t/ha (table 2).
Areas | Varieties | SE1 ± | P | ||
---|---|---|---|---|---|
Común | Tanzania | Tobiatá | |||
0.89c | 2.17a | 1.37b | 0.40 | 0.04 | |
0.57e | 1.41b | 0.75d | |||
3.13d | 6.97a | 4.56b | 0.76 | 0.01 | |
2.33e | 4.52c | 3.30d | |||
0.55d | 1.25a | 0.76c | 0.20 | 0.0001 | |
0.31f | 0.84b | 0.42e | |||
0.34c | 0.92a | 0.61b | 0.19 | 0.041 | |
0.26d | 0.57b | 0.42c |
abcde Values with different letters differ at P<0.05 (Duncan 1955)
1SE, standard error of variety x area interaction
In the case of morphological performance (table 3), they showed variety x area interaction (P <0.05). The best results in height, number of leaves and number of stems were for Tanzania variety in El Empalme area with 1.22 m; 409.5 and 65.25, respectively.
Areas | Varieties | SE1 ± | P | ||
---|---|---|---|---|---|
Común | Tanzania | Tobiatá | |||
0.95b | 1.22a | 0.99b | 0.10 | 0.040 | |
0.84c | 0.97b | 0.86c | |||
161.55c | 409.50a | 267.80b | 8.20 | 0.0001 | |
52.33e | 70.08d | 69.50d | |||
26.95c | 65.25a | 51.45b | 4.91 | 0.001 | |
25.08e | 44.00c | 37.50d |
abcde Values with different letters differ at P<0.05 (Duncan 1955)
1SE, standard error of variety x area interaction
For the leaf growth indicators (table 4), there was no variety x area interaction and only differences (P <0.003) were presented for varieties in leaf width and the highest value was 0.36m for Tanzania.
Indicators, m | Varieties | Areas | |||||||
---|---|---|---|---|---|---|---|---|---|
Común | Tanzania | Tobiatá | SE± | P | El Empalme | Guayas | SE± | P | |
0.58 | 0.66 | 0.63 | 0.03 | 0.85 | 0.63 | 0.61 | 0.29 | 0.576 | |
0.27b | 0.36a | 0.31ab | 0.002 | 0.003 | 0.031 | 0.032 | 0.001 | 0.854 |
ab Values with different letters differ at P<0.05 (Duncan 1955)
1SE, mean standard error
There was no variety x area interaction for crude protein content (figure 1) and the highest content was obtained in Tanzania variety in Guayas (12.52%, P <0.0001).
There was no variety x area interaction for cell wall and its components and there was no effect of either variety or area. However, the highest value of ADL (3.82%, P<0.004) was obtained in Guayas area (table 5)
Indicators, % | Varieties | P | Areas | P | |||||
---|---|---|---|---|---|---|---|---|---|
Común | Tanzania | Tobiatá | SE± | El Empalme | Guayas | SE± | |||
52.96 | 53.20 | 53.26 | 2.38 | 0.995 | 52.13 | 54.15 | 1.94 | 0.464 | |
27.45 | 27.30 | 28.91 | 1.07 | 0.506 | 26.88 | 28.89 | 0.87 | 0.108 | |
3.62 | 3.17 | 3.56 | 0.24 | 0.394 | 3.02b | 3.82a | 0.20 | 0.004 | |
23.64 | 24.13 | 25.35 | 0.83 | 0.399 | 23.86 | 25.02 | 0.68 | 0.234 | |
25.50 | 25.91 | 24.35 | 1.39 | 0.717 | 25.25 | 25.26 | 1.13 | 0.995 | |
47.05 | 45.32 | 46.74 | 2.62 | 0.885 | 46.89 | 45.85 | 2.14 | 0.732 |
ab Values with different letters differ at P<0.05 (Duncan 1955)
SE±, mean standard error
There was significant variety x area interaction for ash, Ca and P content. The highest value (14.62%) of the ash was registered for Tobiatá variety in Guayas. In this same area, the highest value of Ca was recorded by Tanzania and Tobiatá varieties, while the same happened for P content of Común and Tobiatá varieties. However, Común variety in El Empalme area presented the highest percentage of organic matter (table 6).
Areas | Varieties | SE1 ± | P | ||
---|---|---|---|---|---|
Común | Tanzania | Tobiatá | |||
11.89d | 11.83d | 12.25c | 0.52 | 0.001 | |
12.97c | 13.94b | 14.62a | |||
0.46c | 0.49c | 0.48c | 0.02 | 0.001 | |
0.62b | 0.66a | 0.65a | |||
0.019d | 0.017d | 0.020c | 0.002 | 0.0001 | |
0.030ab | 0.029b | 0.032a | |||
88.11a | 88.17a | 87.75b | 0.52 | 0.001 | |
87.03b | 86.07c | 85.38d |
abcde Values with different letters differ at P<0.05 (Duncan 1955)
1SE, standard error of variety x area interaction
Table 7 shows variety x area interaction in leaf/stem, NDF/N and ADF/N relationships. The best results were presented by Guayas area with 2.32 and 4.40 for leaf/stem and ADF/N relations, respectively, in Tanzania, while Común variety had 8.68 for NDF/N in El Empalme.
Areas | Varieties | SE1 ± | P | ||
---|---|---|---|---|---|
Común | Tanzania | Tobiatá | |||
5.18a | 2.08b | 1.77c | 0.68 | 0.005 | |
1.75c | 2.32b | 1.95c | |||
8.68c | 8.75c | 8.79c | 2.34 | 0.0001 | |
33.58a | 29.20b | 33.13a | |||
4.42d | 4.40d | 4.64d | 1.09 | 0.0001 | |
17.70b | 15.18c | 18.10a |
abcd Values with different letters differ at P<0.05 (Duncan 1955)
1SE, standard error of variety x area interaction
For energy intake and digestibility (table 8), there was no significant variety x area interaction. There were only significant differences (P <0.0001) for the effect of area on OMD, ME and LNE, which showed the best results for Guayas area with values of 48.09%, 8.87 and 3.78 MJ / kg, respectively.
Indicators | Varieties | Areas | |||||||
---|---|---|---|---|---|---|---|---|---|
Común | Tanzania | Tobiatá | SE± | P | El Empalme | Guayas | SE± | P | |
47.19 | 47.08 | 47.05 | 1.04 | 0.995 | 47.55 | 46.66 | 0.85 | 0.464 | |
46.10 | 45.70 | 45.79 | 0.98 | 0.957 | 43.63b | 48.09a | 0.80 | 0.0001 | |
6.56 | 6.50 | 6.51 | 0.15 | 0.955 | 6.18b | 6.87a | 0.12 | 0.0001 | |
3.56 | 3.52 | 3.53 | 0.10 | 0.956 | 3.29b | 3.78a | 0.08 | 0.0001 |
ab Values with different letters differ at P<0.05 (Duncan 1955)
SE±, mean standard error
Discussion
These are difficult times for livestock in tropical areas and the activity largely depends on forage supply, while, in turn, this is a function of soil and water, among other factors. Farmers are the most affected by this fact because forests were degraded first, then, forage and now, soils. This circle of social, environmental and economic degradation is a complex phenomenon on a global scale recognized by the United Nations, known as desertification. This process is based on reduction or loss of biological or economic productivity of terrestrial bio-productive system that includes soil, vegetation, other biota components and ecological and hydrological processes, especially in ecosystems of dry areas, due to the way of using land and the combination of processes resulting from human activities and climatic factors (Tapasco et al. 2015 and Arango et al. 2016).
Ramírez et al. (2017) stated that climate elements interact and have a marked effect on growth and development of grass species and varieties in the different months of the year, causing a seasonal imbalance in yields, which provokes food deficits mainly during dry period. In addition, soils destined for pasture cultivation mostly have low fertility and poor drainage, which, together with climate, exert negative effects on productivity and persistence of forage plants. These aspects have been considered for the introduction of improved species with better adaptation to different livestock ecosystems with superior potentialities from a productive and quality point of view.
Herrera et al. (2018) pointed out that plant species exist, reproduce and endure in certain edaphoclimatic contexts, which can be considered as tolerance to these conditions. This is evident in the present study, in which rainfall distribution has an important influence on productivity of Megathyrsus maximus varieties, because areas in El Empalme had 128 mm of precipitations and 1.93 ºC, superior to those in Guayas region, obtaining a difference between regions of 0.76, 0.41, 0.57 and 2.45 t/ha for yield of total dry matter, of leaves, stems and biomass, respectively. In addition, plants also presented higher growth, number of leaves and stems.
This performance is due to the fact that, according to De Lucena-Costa et al. (2018) and Avellaneda-Cáceres et al. (2019), growth and productivity of pastures is influenced by the existing climatic conditions, mainly by annual rains distribution, which, together with other environmental and management factors, impact on pastures and forages do not fully reflect its productive potential. This performance was evidenced in studies by Oyedeji et al. (2016) in Nigeria, who reported yields, under monoculture conditions, of Común variety of 0.53, 0.40 and 0.65, 0.52 t/ha, for the yield of dry matter and of green biomass during dry and rainy periods, respectively, and 200 and 300 mm of precipitations, as well as average temperatures of 34 and 33 ºC, respectively. These results are similar to those obtained in the current study, although with different climate and soil conditions.
Studies of Velasco et al. (2018) demonstrated that biomass production per season was proportional to the recorded precipitation. The highest accumulation of leaf biomass in summer coincides with the best climatic conditions. In the central region of Chiapas state, Mexico, during winter and without record of precipitation, pasture growth decreased, together with the decrease of temperature. In this regard, it should be considered that water stress reduces photosynthesis rate, causes leaf death, and induces plants to seek strategies, like leaf fall.
Seasonal growth of morphological components of plants (tables 3 and 4) are directly related to edaphoclimatic conditions and management practices. Leaf and stem proportion, as well as their growth, are generated by genotype-environment interaction, which results in forage yield. Knowledge of this influence allows to identify availability and, consequently, adopt management strategies (Ramírez et al. 2017 and Velasco et al. 2018).
Differences in the performance of these indicators in the current study regarding interactions (variety x areas) in height, number of leaves and stems (table 3), and their non-existence in leaf length and width (table 4), agrees with reports of Fortes et al. (2016), when evaluating cv. Mombaza and Tanzania during dry period under Cuban western conditions (53 mm of precipitations, 21 and 27 °C of mean and maximum temperatures, respectively). This result could favor biomass production in the plant, since it could correspond to a greater leaf area that favors the capture of light energy and transformation into chemical energy and biomass.
With the development of science, it has been demonstrated that not only climate factors influence plant productivity. Factors such as soil characteristics, fertilization, water availability, sowing and management season, among others, have an important role in the production of plant systems. Pastures are a clear example of this fact (Herrera 2015).
For chemical composition variation, there was only variety x area interaction for CP (figure 1). Cell wall components (NDF, ADF, ADL, CEL and HCEL) did not present differences (table 5). These results agree with Tapasco et al. (2015), Arango et al. (2016) and Morales-Velasco et al. (2016), who stated that when comparing nutritional value of forages, variability is small among cultivars and varieties of the same genus, but their quality is affected by rainfall and temperature variations. Hence, the use of improved pastures with adaptability to different ecosystem conditions and with little difference in their chemical composition are elements that must be considered for selecting varieties.
Álvarez (2019) explained that excess and deficit of precipitation can cause stress in different crops. Excess water causes anoxia in the roots, affecting their aerobic respiration, absorption of minerals and water. If this is prolonged in non-tolerant species, carbon assimilation and translocation decrease, producing metabolic changes that activate anaerobic respiration, which implies less energy efficiency and bio-productivity in plants. While, water stress due to water deficit decreases cell wall concentration in leaves and stems of forage, although variably in its structural components (cellulose, hemicellulose and lignin) and polyphenols, the latter attributed to the need of the plant to maintain high carbohydrate values in soluble forms during osmotic adjustments.
In this species, Álvarez-Perdomo et al. (2016a b) reported CP values between 6-9%, using fertilization with liquid residues from pigs and associated with legumes, with precipitations of 3,500 mm/year. These results are below those reported in the present study for Tanzania variety (11-12%), while Fortes et al. (2016), under Cuban western conditions, found no significant differences in the chemical composition of Mombaza and Tanzania during two years of study. Likewise, Cruz et al. (2012) reported higher CP percentages for Mombaza with respect to cv. Tanzania, and little variability in terms of cell wall components, with cuts at 90 days, being this a performance similar to that obtained in the current research. These differences in both studies could be due to edaphoclimatic and management differences (cutting age) in the studied regions.
On the other hand, Montenegro et al. (2018) reported 8.61, 73.70 and 33.91% for CP, NDF and ADF, respectively, in Común variety, with precipitations of 500mm and temperatures of 32 °C. Differences related to the current research may be due to the prevailing climatic conditions, fertilization effect, nutrient dilution by rains, increased stem growth, experimental conditions and management.
For ash, minerals and organic matter content (table 6), there was variety x area interaction for all indicators, with the highest results in minerals for the area with lower precipitations. This performance, according to Pereira et al. (2017), is attributed to the effect of climate factors, specifically of rains and temperatures, which propitiate greater growth and development for plants (maturity). It is known that minerals are abundant in young and growing parts of plants, especially in sprouts, young leaves and radical extremes, and their decrease in the region of higher precipitations is related to the dilution effect produced by plant development.
De Lucena-Costa et al. (2019) evaluated Megathyrsus maximus cv. Zuri with precipitations of 865.4 mm, mean temperature of 24.86 ºC, and the use of urea, triple superphosphate and potassium chloride with standards of 90, 50 and 60 kg/ha of N, P2O5 and K2O, respectively. They reported decreases of 0.063, 0.12, 0.15 and 0.67%, for the P, Ca, Mg and K, respectively, with a negative effect on mineral content due to dilutions by rains, increases in growth and higher biomass accumulation. Meanwhile, Ortega-Aguirre et al. (2015) and Montenegro et al. (2018) reported values of ash and organic matter between 12-17 and 84-87%, respectively, for Común, Tanzania and Mombaza varieties, which evidences that the percentages found in the present research are within the range of those reported in the scientific literature for this species.
Regarding quality indicators (leaf/stem and fiber fraction/nitrogen relationships), they presented significant differences (table 7). These results coincide with those reported by Verdecia et al. (2012a b) and Méndez-Martínez et al. (2019) in Mombaza, Tanzania, Común and Tobiatá varieties. These authors also argued that this performance is due to anatomical characteristics of each variety, since these cultivars had the highest proportion of leaves available for animal intake and make them promising for cattle feeding.
Digestibility variability and energy supply due to the effect of climatic area (table 8) was reported by Valles-De la Mora et al. (2016), who, after evaluating the effect of seasonality on Megathyrsus maximus cv. Tanzania quality throughout the year, established three periods (March-June, 200 mm and 30 ºC; August-November, 400 mm 32 ºC and January-April, 80 mm and 28 ºC). The best results were for the January-April interval with the lowest rainfall and mean temperature, with digestibility of 73.8% and a difference of 14.1 percentage units with respect to the period of superior precipitations, while the best energy contribution was found during the period of greater precipitations, between August and November, with 6.03 MJ/kg.
Digestibility and energy values are within the range reported in the literature. However, it is worth noting that, despite differences in precipitations between both areas, DMD showed little variation. Ortega-Aguirre et al. (2015) and Avellaneda-Cáceres et al. (2019), when studying five varieties of Megathyrsus maximus (Común, Tanzania, Dwarf, Mombaza and Tobiatá), found no significant differences when evaluating the effect of variety on digestibility, reporting DMD above 47%. These authors considered that the causes of this performance are the constitutive similarity of the different cell components of the plant depending on the variety. These results are similar to those obtained in the current study, in which fiber components did not show differences between areas and variety.
Conclusions
The effect of climate area on forage quality and yield was demonstrated in the current research, where better performances of productivity and morphological development were obtained in the areas of greater rainfall (Empalme), while quality was better for that of less precipitation (Guayas). Although there were no differences for leaf growth, cell wall components, digestibility and energy contribution, its adaptability and potential in different ecosystems is confirmed.