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Cuban Journal of Agricultural Science

Print version ISSN 0864-0408On-line version ISSN 2079-3480

Cuban J. Agric. Sci. vol.54 no.3 Mayabeque Sept.-Dec. 2020  Epub Sep 01, 2020


Pasture Science

Chemical composition, secondary and primary metabolites of Tithonia diversifolia related to climate

1Instituto de Ciencia Animal, Apdo 24 San José de las Lajas, Mayabeque, Cuba

2Universidad de Granma, Bayamo, Cuba


To establish the relationship between chemical composition, secondary metabolites, primary metabolites and digestibility of organic matter, dry matter, protein, NDF and ADF of Tithonia diversifolia and climatic factors, the correlation study was carried out. The indicators were: A) chemical composition: ADF, NDF, lignin, cellulose, hemicellulose, cellular content, OM, ash, N, Si, Ca, P and Mg; B) secondary metabolites: total tannins, total phenols, total condensed tannins, fiber-bound condensed tannins, free condensed tannins, alkaloids, saponins, triterpenes, steroids and flavonoids, and C) primary metabolites: glucose, fructose, sucrose, N, verbascose, stachyose and raffinose. Correlation coefficients (r) between climatic factors and chemical composition were variable and the highest values ​​were obtained for cellulose, total rainfall and number of days with rain (-0.69 and -0.73, respectively). For secondary metabolites, total condensed tannins and free condensed tannins stood out with temperatures and indicators of rain (values of r between 0.62 and 0.85) and for the primary metabolites, verbascose and stachyose were better with temperatures (r higher than 0.78). In vitro digestibility of DM correlated (r between -0.63 and -0.91) with temperatures, rainfall and their distribution. Similar performance was registered for digestibility of organic matter and the r varied between -0.69 and -0.90. Digestibilities of CP, ADF and NDF only correlated with rainfall and their distribution (r between -0.74 and -0.87). Data showed the specific and variable effect of climate elements in the studied indicators, which is useful for the efficient management of this plant under climate change conditions. It is recommended to consider these results to counteract the negative effect that secondary metabolites of Tithonia diversifolia can cause in ruminant feeding systems, apply mathematical modeling to predict the performance of these substances with climatic factors and other aspects of this plant management, as well as extend this type of research to other plants of interest to livestock.

Key words: antinutritional factors; chemical composition; digestibility; temperature; rain

Since the 90s of last century, it has been argued that cattle rearing in tropical countries has to be profitable and competitive, based on the minimum use of imported inputs, friendly to environment and use of local resources (Roggero et al. 1996). This geographical area has the greatest plant biodiversity, but animal feeding systems are mainly based on the use of few plant species.

The use of shrubs in livestock systems has gained great importance in recent years due to its nutritional, productive and environmental contribution (Schultze-Kraft et al. 2018) and Tithonia diversifolia (Hemsl.) A. Gray stood out due to its genetic diversity (Del Val et al. 2017), wide adaptation to different environmental conditions (Ruiz et al. 2010), high variability in morphological indicators (Rivera et al. 2018), high biomass production (Ruiz et al. 2017) and better chemical composition (Londoño et al. 2019) than most of the grasses used in the tropics.

In addition to the previously mentioned benefits, this plant contains secondary metabolites (Verdecia 2014) that, due to its chemical characteristics, give it added value since its extracts can be used as insecticide and herbicide, among other properties (Miranda et al. 2015 and Ejelonu et al. 2017).

Plants (pastures, forages and shrubs, among others) used as food, in tropical areas, show marked seasonal yield, which responds to the existence of two well-defined climatic seasons (rainy and dry periods). Tithonia does not escape this effect and its lower yield has been evidenced in dry season (Ruiz et al. 2016, 2017; Verdecia et al. 2018 and Paumier et al. 2020).

Considering the above, the objective of this study was to determine the relationship between chemical composition and secondary metabolites of Tithonia diversifolia with some climatic factors.

Materials and Methods

Data obtained by Verdecia (2014) was used. This data came from an experiment with Tithonia diversifolia of two years of established in plots of 0.5 ha in a completely randomized design and five replications, in a brown soil with carbonate (Hernández et al. 1999). It showed 6.2 of pH, P2O5, K2O and N contents of 2.4, 33.4 and 3.0 mg/100g of soil, respectively, and 3.6% of organic matter. Mean temperature and annual rainfall of the experimental period were 25.6 ºC and 1,083 mm, respectively, while historical values were, in the same order, 25.2 ºC and 1000 mm. No irrigation or fertilization was used.

Samples were taken from 10 random plants per replicate (240 samples in total), cut at 15 cm above soil level and were composed of leaves, petioles and stems smaller than 2.0 cm. The material was homogenized, dried in a circulating air oven at 65ºC for 72 h until constant weight and ground until reaching a particle size of 1 mm. An amount of 600 samples were analyzed in the two experimental years.

DM, N, ash, OM, P, Ca and Mg (AOAC 2000) were determined, as well as NDF, ADF, lignin, cellulose, hemicellulose, cellular content and silica (Goering and Van Soest 1970), phenols and total tannins (Makkar 2003), total condensed, free condensed and fiber-bound condensed tannins (Porter et al. 1985), flavonoids (Boham and Kocipai-Abyazan 1944), saponins (Obdoni and Ochuko 2001), triterpenes (Fernand He 2006), steroids (Galindo et al. 1989) and alkaloids (Muzquiz et al. 1994). There were also determinations of in vitro digestibilities of DM, CP, ADF and NDF (Ankom 2000) and of OM (Aumont et al. 1995) and sugars by gas-liquid chromatography. In addition, maximum, minimum and mean temperatures were quantified, as well as total rain and number of days with rain between samplings.

Correlation coefficients (Visauta 2007) were established between secondary metabolites (total phenols, total tannins, fiber-bound condensed tannins, free condensed tannins, alkaloids, saponins, triterpenes, flavonoids and steroids), as well as chemical composition (NDF, ADF, lignin, cellulose, hemicellulose, cellular content, organic matter, ash, nitrogen, Si, Ca, P and Mg); digestibilities of OM, DM, CP, ADF, NDF, and sugars (verbascose, stachyose, raffinose, glucose, fructose and sucrose) of Tithonia diversifolia with some climatic factors (maximum, minimum and mean temperatures, number of days with rain and total rain).


The correlation between climate factors and chemical composition was variable (table 1). The highest coefficients (r) were obtained for P, with the maximum temperature (0.64) and mean temperature (0.63), OM and ash with the minimum temperature (0.62 and -0.62, respectively), cellulose with the maximum temperature, total rainfall and number of days with rains (-0.62, -0.69 and -0.73, in the same order) and nitrogen (N) with rains and their distribution (-0.81 and -0.82, respectively). For the rest of the chemical composition indicators, correlations were low or not significant.

Table 1 Correlation coefficients (r) between chemical composition and climate factors 

Dependent variables, % Independent variables
Temperature, ºC Rain, mm
Maximum Minimum Mean Total # of days
NDF -0.15NS -0.45* -0.33 NS 0.31 NS 0.35 NS
ADF -0.29 NS -0.48* -0.42 NS 0.32 NS 0.39 NS
Lignin 0.15 NS -0.18 NS -0.04 NS 0.49* 0.56*
Cellulose -0.62** -0.29 NS -0.46* -0.69** -0.73**
Hemicellulose 0.31 NS -0.22 NS 0.15 NS 0.07 NS 0.04 NS
Cell content 0.14 NS 0.45* 0.33 NS -0.31 NS -0.36 NS
Organic matter 0.47* 0.62** 0.55* 0.53* 0.55*
Ashes -0.48* -0.62** -0.56* -0.54* -0.56*
Si -0.10 NS -0.19 NS -0.19 NS 0.20 NS 0.29 NS
Ca 0.50* -0.60** -0.58** -0.29 NS -0.17 NS
P 0.64** 0.49* 0.63** 0.18 NS 0.25 NS
Mg -0.29 NS -0.35 NS -0.30 NS -0.14 NS -0.008 NS
N -0.45* -0.23 NS -0.33 NS -0.81*** -0.82***

*P<0.05 **P<0.01

NS: not significant

The highest correlations (table 2) were found: between total phenols, total condensed tannins, fiber-bound condensed tannins and free condensed tannins with maximum temperature (between 0.67 and 0.89) and mean temperature (between 0.63 and 0.85); for total condensed tannins and free condensed tannins with the minimum temperature (0.77 and 0.76, respectively) and these same compounds with total rain (0.72 and 0.79, respectively) and with number of days with rain (0.64 and 0.77, respectively). For the rest of the secondary metabolites, correlations were low or not significant.

Table 2 Correlation coefficients (r) between secondary metabolites and climate factors 

Dependent variables Independent variables
Temperature, ºC Rain, mm
Maximum Minimum Mean Total # of days
Total tannins 0.40 NS 0.29 NS 0.34 NS 0.51* 0.58*
Total phenols 0.67** 0.57* 0.63** 0.48* 0.52*
Total condensed tannins 0.88*** 0.77*** 0.85*** 0.72*** 0.64**
Fiber-bound condensed tannins 0.63** 0.56* 0.63** 0.45* 0.33 NS
Free condensed tannins 0.89*** 0.76*** 0.84*** 0.79*** 0.77***
Flavonoids 0.20 NS -0.28 NS -0.16 NS 0.46* 0.50*
Alkaloids -0.10 NS -0.33 NS -0.19 NS 0.45* 0.42 NS
Saponins -0.26 NS -0.45* -0.38 NS 0.31 NS 0.34 NS
Triterpenes 0.06 NS -0.27 NS -0.13 NS 0.42 NS 0.47*
Steroids 0.01 NS -0.29 NS -0.16 NS 0.48* 0.52*

*P<0.05 **P<0.01 ***P<0.001

NS: not significant

The highest coefficients between verbascose and stachyose (0.78-0.90) were obtained with temperatures (maximum, minimum and mean). For the rest of sugars, no relationship was found with temperatures, while relationships were low or not significant with rains and their distribution (table 3).

Table 3 Correlation coefficients (r) between sugars and climate factors 

Dependent variables Independent variables
Temperature, ºC Rain, mm
Maximum Minimum Mean Total # of days
Verbascose 0.78*** 0.90*** 0.88*** 0.39 NS 0.39 NS
Stachyose 0.78*** 0.87*** 0.86*** 0.55* 0.46*
Raffinose -0.12 NS 0.03 NS 0.20 NS -0.40 NS -0.53*
Glucose 0.19 NS 0.35 NS 0.31 NS -0.24 NS -0.35 NS
Fructose 0.25 NS 0.32 NS 0.32 NS -0.11 NS -0.20 NS
Sucrose 0.23 NS 0.34 NS 0.32 NS -0.17 NS -0.27 NS

*P<0.05 ***P<0.001

NS: not significant

DM in vitro digestibility (DMIVD) and of organic matter (OMD) were negatively correlated with temperatures, rains and their distribution, while in true digestibility (DV), correlations were significant only with temperatures. The highest correlations between digestibilities of protein (CPD), acid detergent fiber (ADFD) and neutral detergent fiber (NDFD) were obtained with rains and their distribution, although the latter also correlated with minimum temperature (table 4).

Table 4 Correlation coefficients (r) between digestibilities and climate factors 

Dependent variables Independent variables
Temperature, ºC Rain, mm
Maximum Minimum Mean Total # of days
DMIVD -0.80*** -0.63** -0.74*** -0.91*** -0.89***
TD 0.82*** 0.61** 0.72** 0.56* 0.55*
OMD -0.81*** -0.69** -0.76** -0.90*** -0.88***
CPD -0.53* -0.37 NS -0.46 -0.85*** -0.87***
ADFD -0.34 NS -0.09 NS -0.20 NS -0.74** -0.77**
NDFD -0.34 NS -0.79** -0.19 NS -0.74** -0.76**

*P<0.05 **P<0.01 ***P<0.001

NS: not significant


Most of research on yield and quality of pastures, forages and other crops of interest for livestock are carried out in field experiments and differences in the results have been explained by regrowth age, frequency and cutting height, fertilization, irrigation, management, species and varieties, among other factors. While the aspects of the climate have been treated in a general way through the performance of its indicators in seasonal periods.

It is established science that climate features (temperatures, rainfall, humidity and some others) act in an interrelated manner on yield and quality of pastures. However, in the current research, the hypothesis of studying the individual influence of some climate factors (temperatures, rainfall and their distribution) on chemical composition, secondary metabolites and digestibility of Tithonia diversifolia, was used. For this, climate data corresponding to each growth period were used in which samplings and chemical analyzes of studied indicators, during two years, were carried out. In this way, enough data was obtained to establish accurate correlations. Furthermore, it was considered significant when the correlation coefficient reached a value superior to 0.60 and a significance higher than P <0.05.

References indicate the benefits of the chemical composition of Tithonia, characterized by high protein values, moderate contents of fiber elements and acceptable mineral content, which vary depending on agronomic management (variety, frequency and cutting height, fertilization, regrowth age and some other aspects) to which the plant is subjected. However, information shows high variability of values of chemical composition indicators with management (Verdecia et al. 2011, Rivera et al. 2018 and Londoño et al. 2019).

Correlation coefficients between indicators of chemical composition and climate factors were, in general, low and with high variability, except cellulose, OM and P (table 1). Negative correlation found between cellulose and maximum temperature could be possibly related to the fact that maximum temperatures were higher than optimum temperature for plant growth and had a negative influence on it. However, correlations with rain and its distribution were negative and significant, indicating the possible alteration of the synthesis of this compound. This confirms the findings of Nava et al. (2019), when they studied the effect of rain on this crop.

Negative and highly significant correlations of N with rain and its distribution could be related to the dilution effect suffered by N, as well as the probable decrease in the absorption capacity, by the root, of this element due to the existence of a humidity gradient in the soil that does not favor the referred process (Taiz and Zeiger 2010).

Variability in the mineral composition of Tithonia has been reported depending on the management, including the climate, to which it is subjected (Verdecia 2014 and Guatusmal-Gelpud 2020). In the case of minerals (Si, Ca and Mg), no adjustments were found or they were low with climate factors, which could indicate some independence from climate factors, aspects that need future research. Nevertheless, the highest correlations only corresponded to P with the maximum and mean temperatures. The above could indicate that the absorption of this element is favored with the increase of maximum and mean temperatures.

Rivera et al. (2018), in their article, compiled information on secondary metabolites of Tithonia and pointed out the diversity of chemical compounds that make them up, as well as the variety of effects they produce in the animal. In this way, saponins have antibacterial activity and intervene in the decrease o removal of protozoa from the rumen. Flavonoids have antimicrobial properties and terpenoids can reduce the peptidolytic activity of ruminal bacteria and effectively inhibit the growth of ruminal bacteria involved in ammonia production. This variety of chemical compounds that flavonoids, alkaloids, saponins, triterpenes, and steroids are constituted by, could be responsible for the variable relationships between these secondary metabolites and climate factors, with a low correlation coefficient in the current research. For this reason, future experiments are needed to deepen in this response, as well as its effect on animals.

In relation to tannins, these are high molecular weight polyphenolic compounds with different properties, there are several classifications and these compounds can inhibit enzymes (cellulases and pectinases), produce alterations in cell walls, reduction of CH4 emissions and affect the transport of carbohydrates and amino acids, among other functions (Makkar et al. 1988, Makkar 2003 and Rivera et al. 2018).

The chemical determination of these compounds requires specific analytical procedure, generally expensive, which is why their qualitative determination is frequently used (Lezcano et al. 2012 and Sandoval-Pelcastre et al. 2020). However, like all qualitative analytical procedure, it depends on several factors (age and part of the sampled plant, concentration of the compound in the material and sensitivity of the reagent to be used) so the result may be variable and not reflect the true composition of the sample.

In Tithonia diversifolia, Gallego-Castro et al. (2017) found variations in the content of phenolic compounds when they studied different sowing systems. Scull et al. (2008) found differences in the phenolic content of among leaves, stems and the whole plant, and Verdecia et al. (2011) determined the effect of regrowth age and season in several phenolic compounds.

In the present research, the best correlations were obtained in total condensed tannins and free condensed tannins with temperatures (maximum, minimum and average) and rains and their distribution, which evidences the positive effect of climate factors on concentration of these chemical compounds of Tithonia. Therefore, it would be of interest to know what would be the limit value of temperatures and rainfall that would promote appropriate values of these compounds that do not negatively influence on physiology and nutrition of animals that consume this plant.

In relation to sugars, information is limited and has been based on the qualitative determination of reducing sugars. In the current research, the best correlations were found in verbascose and stachyose with temperatures (maximum, minimum and mean). These sugars are composed by galactose, glucose and fructose molecules in proportions 2:1:1 and 3:1:1 for stachyose and verbascose, respectively. However, there was no correlation between glucose and fructose with climate factors, which attracted attention, since these substances are the basis for the synthesis of verbascose and stachyose, classified as oligosaccharide and tetrasaccharide, respectively. In addition, these compounds, when consumed, can produce flatulence and have a negative effect on animal nutrition. Therefore, all these aspects require future research.

Digestibility indicates the efficiency of use of an indicator (DM, OM, CP, NDF and ADF, among others) by the animal, and it has been reported that it depends on pasture management, as well as internal factors such as content of fiber compounds, lignin and silica, among other aspects (Valenciaga et al. 2009a b). On the other hand, La O et al. (2012), when studying different digestibilities (DM, OM, ADF, NDF) of various ecotypes of Tithonia diversifolia, found variability of values among ecotypes. As these compounds of the plant vary according to the climatic season, it is expected that digestibility will also fluctuate and, therefore, climate factors can be considered to indirectly influence on digestibility.

In the references consulted, no article similar to the present study was found and it was interesting to find the negative and significant influence between maximum, minimum and mean temperatures (correlation coefficient between -0.63 and -0.81) and the DMIVD and OMD, but rains and their distribution also showed negative and highly significant correlation coefficients (between -0.88 and -0.91). Nevertheless, for CPD, NDFD and ADFD, the highest negative and significant correlations were obtained with rainfall and its distribution. These elements could serve as an alert to carry out the efficient management of this species during rainy period, characterized by high temperatures and precipitations.

Results of the current study, considering that climate elements (temperatures, rainfall and its distribution) act individually and/or interrelated, evidenced the specific and variable response of climate factors in the studied indicators, which is useful for the efficient management of this plant under climate change conditions. Furthermore, it is necessary to consider the need for future studies to counteract the probable negative effect that secondary metabolites of Tithonia diversifolia may cause in ruminant feeding systems. It is also necessary to apply mathematical modeling to predict the performance of these substances with climate factors and include other indicators such as duration and intensity of light, as well as consider these results when designing the efficient management of this plant and extend this type of research to other plants of interest for livestock.


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Received: February 25, 2020; Accepted: June 05, 2020


Declaración de conflicto de intereses: Los autores declaran no presentar conflicto de intereses

Contribución de los autores: Los autores declaran presentar contribución igualitaria en la concepción de la investigación, obtención y procesamiento de los datos y redacción del documento

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