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Rev. Biol. Trop. (Int. J. Trop. Biol.) • Vol. 69(1): 218-230, March 2021

Pod production, and dasometric variables,

of the tree Senna spectabilis (Fabaceae) in a tropical dry forest

Jesús H. Duarte-Vargas

, Omar Melo

, Jairo Mora-Delgado

, Román Castañeda-Serrano

& Henry Váquiro

1. Departamento de Producción Pecuaria, Universidad del Tolima, Ibagué, Colombia; jhduarte@ut.edu.co;

jrmora@ut.edu.co; rcastaneda@ut.edu.co

2. Departamento de Ciencias Forestales, Universidad del Tolima, Ibagué, Colombia; omelo@ut.edu.co

3. Departamento de Producción y Sanidad Vegetal, Universidad del Tolima, Ibagué, Colombia; havaquiro@ut.edu.co

Received 04-VII-2020. Corrected 13-XI-2020. Accepted 18-XI-2020.

ABSTRACT. Introduction: Senna spectabilis is a multipurpose pantropical tree, used in agroforestry systems.

Objective: To determine pod production (Pp) and their relationship with dasometric variables in S. spectabilis

in the tropical dry forest. Methods: From August 2016 to February 2017, thirty trees in production stage were

randomly selected. The random selection was formed of the more isolated trees from the total dispersion. The

trees were monitored at the beginning and end of the study period, to determine dasometric measurements such

as total height (Th), height to the first branch (Hb), crown height (Ch), Stem diameter (at 0.2 m height from the

ground) (Db), crown diameter (Cd), and crown volume (Cv) measured. Pods were harvested by the researcher

with cutting and height cutting tongs when their color began to change. Pearson correlations and univariate and

multivariate regression analyses were performed between the dasometric variables and pod production. The

potential number of trees/ha (NPa) was calculated by determining the occlusion percentage (Op) and the shadow

area/tree (Ca); to estimate the production potential of fruits/ha, the production of fruits/tree was multiplied by

(NPa). Results: Th was 6.16 ± 1.23 m, Hb 2.75 ± 0.52 m, Ch 3.41 ± 0.98 m, Db 20.43 ± 4.80 cm, Cd 7.46 ± 1.20

m and Cv 108.43 ± 61.38 m

/tree. There was a significant positive correlation between Hb, Cd, Db, with Pp of

0.592**, 0.592**, and 0.446* respectively. Pp was 32.73 ± 16.13 kg/tree and the dry matter production (MSP)

was 17.84 ± 8.80 kg/tree. The result of the multivariate regression indicated that the second-order polynomial

model presented best goodness of fit. Op was 73.4 7.92 %, the cup area was 49.3 m

/tree, Ca was 36.2 m

/tree,

and NPa was 83 trees. Conclusions: The production of fresh pods/ tree in the S. spectabilis presents a potential

in its availability as feed for ruminant or seed production. The potential production of pods in silvopastoral with

S. spectabilis could be 2.72 t/ ha, and 1.64 t/ ha of dry pods, this shows the importance of trees and of pods

production and nutritional contribution obtained for dry ecosystems.

Key words: pods; morphometry; models of predict; scattered trees; silvopastoral.

Duarte-Vargas, J.H., Omar Melo, Mora-Delgado, J., Castañeda-Serrano, R., & Váquiro,

H. (2021). Pod production, and dasometric variables, of the tree Senna spectabilis

(Fabaceae) in a tropical dry forest. Revista de Biología Tropical, 69(1), 218-230.

DOI 10.15517/rbt.v69i1.42792

ISSN Printed: 0034-7744 ISSN digital: 2215-2075

Ruminants in tropical and subtropical

countries satisfy most of their dietary needs

with native grasses and crop residues, which

are of low quality (Tikam et al., 2015). In order

to overcome the lack of nutrients during the dry

season, some producers supplement their ani-

mals with foliage and pods of woody species.

The scattered trees in the prairies improve

the profitability of livestock farms because

they offer economic benefits such as wood,

poles, and high-quality nutritional supplements

such as forage and pods (Camero, Ibrahim,

& Kass, 2001; Manning, Fischer, & Lin-

denmayer, 2006). Besides, the possibility of

DOI 10.15517/rbt.v69i1.42792

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receiving payments for environmental services,

they have great potential to increase livestock

production. This is due to the contribution of

the animal´s welfare; it favors the habitat of

some species while improving the connectivity

between wooded landscapes (Cadavid-Florez,

Laborde, & Maclean, 2020).

S. spectabilis (DC.) H.S. Irwin & Barneby,

is an important source of food for livestock

and wildlife, mainly during the dry season. The

forage nutritive value of the leaves and pods of

these trees is generally higher than herbaceous

plants, specifically in reference to legumes

(Guariguata & Ostertag, 2001; Harvey, Vil-

lanueva, & Esquivel, 2011). The benefit of

maintaining this type of tree in grasslands is

evidenced by the traditional use of silvopasto-

ral systems in several parts of the world (Har-

tel, Réti, & Craioveanu, 2017).

Given the implementation of the S. specta-

bilis tree in silvopastoral systems in Colombia,

the academy has been motivated to carry out

research works to find out its potential. It is

a pantropical tree (Lacerda et al., 2018) and

has been introduced as an ornamental tree to

different parts of Africa including Angola,

Burundi, South Africa, and Eastern Africa

(Jothy et al., 2012).

S. spectabilis has been commonly used in

traditional medicine for many years. Informa-

tion in the biomedical literature has indicated

the presence of chemical components of medi-

cal importance, with antibacterial, anti-biofilm,

antifungal, and antioxidant properties (Chuke-

atirote, Hanpattanakit, Kaprom, & Tovaranon-

te, 2007; Torey, Sasidharam, Yeng, & Latha,

2010; Jothy et al., 2012). It is a rapid growth,

drought tolerant, termite attack resistant tree

that is also able to grow in standard conditions

(Namirembe, Brook, & Ong, 2009). It is used

for firewood (Tabuti, Dhillion, & Lye, 2003)

and widely for landscaping, due to the great

beauty of its yellow flowers. Also, it has a great

potential for degraded area restoration (Silva et

al., 2010). S. spectabilis is a tree of the Fabace-

ae family (subfamily Caesalpiniaceae) (Pivatto

et al., 2005). It is commonly used in semi-arid

regions, where it is known as “cañafístula” or

“cassia,” as a forage for sheep and goats (San-

tos, Araújo, Nascimento, & Lima, 2013).

The nutritional value of S. spectabilis

forage has a high potential for livestock agro-

forestry technologies in the humid lowlands of

West and Central Africa (Larbi et al., 2005).

The protein, mineral, and fat content of S.

spectabilis are high in comparison to other

forage species that are native to the Brazilian

Caatinga. For this reason, the plant represents a

valuable nutritional resource during periods of

drought (Almeida et al., 2011).

A study incorporated S. spectabilis tree

pods as a supplement in the diet of ruminants

(Bonilla-Trujillo, Pardo-Guzman, & Castañe-

da-Serrano, 2018), which looked at the in

vivo and in vitro digestibility and ruminal

degradability in sheep hair fed with Angleton

(Dichanthium spp.) hay-based diets. S. specta-

bilis pods were used at 0.6, 1.2, and 1.8 % of

body weight and concluded that the pods have

an attractive nutritional value. It was proposed

as a promising alternative for the ruminant

supplementation in the tropical regions of the

world. However, the lack of knowledge about

the production of pods restricts its use and

therefore, its diversification.

This tree annually produces large quanti-

ties of viable seeds; one kilogram corresponds

to approximately 27 600 seeds. Researchers

obtained galactomannans with a yield of 31.6 %

in dry weight and suggest that the seeds can be

considered as a potential source of galactoman-

nans for the industry (Fernandes, Nakashima,

& Serra, 2004). Galactomannans are widely

used in the pharmaceutical industry to control

water activity, to stabilize aqueous solutions

and dispersions, and for their high thickening

power (Buckeridge, Dietrich, & de Lima, 2000;

Prajapati et al., 2013; Soares et al., 2015).

The knowledge of the tree architecture and

dasometric measurements represents a contri-

bution to defining criteria for harvesting and

management (Beltrán-Galindo, Romero-Man-

zanares, Luna-Cavazos, & García-Moya, 2017)

and the design of agroforestry or silvicultural

systems. The architecture of the tree canopy

has significant impacts on the microclimate

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of the crop and is influenced by competition

for light, water absorption and transpiration,

dispersion of pollen; acquisition and location

of carbon (Boudreau, 2013). This architecture

also influences biophysical processes, such as

photosynthesis and evapotranspiration (Van

der Zande, Hoet, Jonckheere, Aart, & Coopin,

2006; Rosell et al., 2009). An accurate descrip-

tion of the tree architecture leads to a better

understanding of how the shape is controlled

by each function (Lau et al., 2018).

Therefore, this research aimed to deter-

mine the production of pods and the architec-

ture of the tree in the tropical dry forest, to

contribute with tools that serve as a basis for

management programs, and above all to con-

tribute knowledge to generate alternatives of

integral use of S. spectabilis into cattle farms.

MATERIALS AND METHODS

Location and climatic conditions: The

present study was carried out in La Comarca

farm located in Alvarado, Tolima, Colombia,

(74°58’14.6” WO & 74°58’14.6” W) under

the following conditions: 460 m.a.s.l., annual

average temperature 27.7 ºC, annual average

precipitation 1 601 mm, relative humidity 67

%, and is related to tropical dry forest weather

according to Sánchez-Azofeifa et al., (2005).

Edaphic conditions: A chemical analysis

of the soil was carried out to complement the

information about the edaphic conditions at

the study site, with the analysis made between

0 and 20 cm depth. The data of the chemical

analysis, texture and bulk density is then pre-

sented. A chemical and soil texture analysis

of the La Comarca farm was carried out by

LASEREX laboratory of University of Tolima,

finding: pH 5.9, organic matter 2 %, texture

(27.2 % clay, 18 % silt, 54.8 % sand), humid-

ity 15.2 %, and apparent density 1.49 g/cm

(Instituto Colombiano de Normas Técnicas y

Certificación, 2014; 2018).

Sampling: The trees were sampled in

eight transects of 300 m × 4 m each, randomly

plotted. Thirty trees free of visual defects,

pests, and diseases were selected. All trees

were georeferenced and labelled with their

numbering directed towards the North cardi-

nal point. The trees that were more isolated

from the total dispersed trees were chosen (to

avoid inter and intraspecific competition). The

selected trees height was measured and it was

found that 53.3 % were less than 6 m tall, and

were characterized by having had at least four

harvests. While the trees greater than or equal

to 6 meters were characterized by having more

than four harvests, this was the criterion used to

analyses the two ranges of height; h < 6 m (N =

16) and h ≥ 6 m (N = 14).

Samples of leaves, flowers, and fruits were

taken to the TOLI herbarium of the University

of Tolima, for classification, and it was verified

that they corresponded to the Senna spectabilis,

number 29061 in the collection book.

Dasometric variables: Total (Th) and first

tree branch (Hb) height were measured with a

graduated telescopic rod expressed in meters.

Crown height (Ch) was determined by the dif-

ference between Th and Hb Equation 1.

Stem diameter (at 0.2 m height from the

ground): this measurement was made because

the individuals of the species showed a main

shaft bifurcation at a low height, using a dia-

metric tape.

Crown diameter (Cd) in m: four crown

radii were measured in relation to the cardinal

points at 90 °, with a tape measure, the radii

were taken from the center of the tree to the

outer edge of it, measured in vertical projec-

tions. Therefore, the cup diameter was set at

twice the average of the four measured radii.

Crown volume (Cv) in m

: to estimate this,

the shape of the tree’s crown was taken into

account, which corresponds to a spherical cap,

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therefore the corresponding equation was used

Equation 2.

Where and Ch = crown height, r = crown

radius, R = radius in which the spherical cap

is circumscribed.

The dasometric measurements were made

at the beginning and at the end of the evalua-

tion period; the measurements were then avera-

ged for the evaluations.

Pod production (Pp): The pods that were

within reach of the researcher were harvested

with cutting tongs and the others with height

cutting tongs. The pods were harvested when

they presented a 50% color change (green to

brown). In addition, the fallen pods were also

collected and transported to be weighed and the

total mass of the pods in kg of each sampled

tree was obtained (the pods are harvested once

a year, phenologically one harvest of pods

per year is presented between the months of

November to February according to Duarte-

Vargas et al. (in press), an electronic weighing

scale of 50 kg capacity with an accuracy of 5 g,

was used for weighing.

Dried pod production (DPp): For the

determination of dried pods/tree, five samples

of pod production were exposed to the sun on

a cement surface to dry for a week and then

weighed. With this procedure it was possible to

determine the average yield by multiplying the

production of pods per tree, thus obtaining the

production of dried pods tree

-1

Dry matter production of pod/tree

(DMPp):

To determine the dry matter of the pods, five

dry matters analyzes of the dried pods were

performed and the value averaged. The dry

matter of the pods per tree was calculated by

multiplying dried pod production by the dry

matter percentage.

Tree occlusion percentage (Op): Vertical

digital photographs were taken of the trees

under study from the bottom up of the canopy

in the early hours of the morning, to avoid sun-

light interference. The images were analyzed

software free (Gap light analyzer), which was

designed to examine hemispheric photographs.

This tool allowed estimating the percentage of

occlusion through the canopy (Frazer, Canham,

& Lertzman, 1999). The tree canopy area (Ta)

in m

was estimated through Equation 3.

Where: r = average canopy radius, r = Cd/2.

The shadow area (As): Equation 4 was

used to determine:

Where: Op = occlusion percentage.

The number of potential trees/ha

of Senna

spectabilis in a silvopastoril system: To calcu-

late, it is taken into account that, the maximum

shade to not affect the biomass production of

Botrhioclhoa pertusa grass is a bush coverage

of 20 to 40 % (Serrano, 2013), and in tropical

grasses a 30 % shade (Castro, García, Mesqui-

ta, & Couto, 1999; Andrade, Brook, & Ibrahim,

2008), and for the calculation the number of

tree/ha

(Nt), Equation 5 was used:

Where: 3 000 m

= maximum shade in one

hectare, Sa = the shadow area per tree.

Statistical analysis: Using the program

IBM SSPS Statistics version 22, the analysis

of the descriptive statistics, means, standard

deviations, coefficient of variation of each one

of the dimensional variables and pod produc-

tion was carried out. A comparison analysis

of the height ranges: < 6 m (N = 16) and ≥

6 m (N = 14) was carried out for tree daso-

metric measurements with T-test for related

variables, using the Anova N statistic; for

unbalanced designs, with the MatLab R2019b

program. Likewise, the normality of each vari-

able with the Shapiro-Wilk tool was evalu-

ated and based on the result and the Pearson

correlation analysis was made to identify the

correlation. Only statistically significant corre-

lations with a value greater than or equal to 0.4

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were considered. If the value of the index was

between: 0.4-0.5 an average positive correla-

tion, 0.75 a considerable positive correlation,

0.95 a very strong positive correlation, and 1 a

perfect positive correlation.

A univariate regression analysis was per-

formed for each of the variables, the dasometric

measurements, and pod production, where dif-

ferent models (linear, exponential, logarithmic,

polynomial, and potential) were tested and with

the purpose of generating models that would

allow estimating pod production, and also

multivariate regression to evaluate with three

different models. Two models were linear one,

which considered first-order terms; another

linear model with interactions that included

first-order terms and interactions between pairs

of them. A second order polynomial model

was also used, which involved the first and

second order terms of the variables and their

interactions. The stepwise regression method

was applied using the “stepwise” function of

the MatLab R2007b software to univariate and

multivariate regression. The models identified

from the stepwise regression method included

only those terms statistically significant at a

95 % confidence level. The best models were

selected considering the criteria of highest

determination coefficient adjusted R

adj, low-

est mean: the square root of the mean square of

the error (RMSE), Akaike Information Criteria

(AIC) and Bayesian Information Criteria (BIC)

(Kusmana, Hidayat, Tiryana, & Rusdiana,

2018). Additionally, the confidence intervals of

the parameters, the normality in the distribution

of the residues through the Lilliefors test and

the graph of the residuals were evaluated to

rule out heteroscedasticity problems.

RESULTS

Dasometric variables in the tree S. spec-

tabilis: It is observed that the variation coef-

ficients of the tree dasometric variables: total

height of the tree (Th), height to the first

branches (Hb), diameter at the base of the

stem (Db), and crown diameter (Cd) are lower

concerning the variables: crown height (Ch),

crown volume (Cv), pod production (Pp), dry

pod production (Ppd), and dry matter of pod

(PpMS). Table 1 shows the basic statistics of

the eight variables analyzed, H, Ch, Hb, Db,

Dc, Cv, Pp, Ppd, PpMS.

It is observed that S. spectabilis has a

crown height around 36.5 times the diameter at

the base of the stem. Maintaining a large crown

requires more energy to move nutrients and

water throughout the length and width of the

crown, but it has the advantage of receiving and

intercepting a greater amount of light (King &

Clark, 2011). It is important to note that crown

diameter is greater than height of the tree by

21.1 %. Also, height average tree is constituted

by a 55.4 % of crown length, these characteris-

tics enable a biophysical design useful for the

production of pods since the crown volume in

the tree is high and it favors the interception of

light, especially in trees ≥ 6 m.

The average pod production/tree per har-

vest was 32.73 kg (± 16.13 SE; N = 30) and the

average dry matter of pod/tree per harvest was

17.84 kg (± 8.8 SE; N = 30). It is also impor-

tant to indicate the potential of the tree when

fertilized. One tree that was excluded from the

study and located next to a stable, absorbed

nutrients from feces and reported a production

of 118.76 kg.

In the analysis of the height range of the

trees regarding to the measurements of the

tree dasometric variables, statistically highly

significant differences were found (P < 0.01).

In regard to the height of trees, crown height,

height to the first branch, crown diameter, and

crown volume where the range of trees ≥ 6 m

(N = 14), is superior to the range of trees < 6 m

(N = 16). While for the variable diameter at the

base of the stem, pod production, dry pod pro-

duction, and dry matter pod production there

were no statistically significant differences (P

> 0.05) between the ranges studied.

The performance of weight of harvested

pod to weight of dry pod in S. spectabilis was

60.6 %, and the dry matter of the pods per tree

was an average of 0.9.

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Correlation between the dimensional

variables and the pod production: Table 2

presents the correlation study between the eval-

uated dasometric variables and pod produc-

tion, where it is observed that diameter at the

base of the stem, height to the first branch,

and crown diameter have average positive

correlation with pod production. The variable

crown volume has a positive correlation from

strong to very strong with height and crown

volume. The crown diameter has an average

to strong positive correlation with diameter

at the base of the stem. The variables crown

volume and height were the ones with the most

positive correlations.

The average positive correlation between

crown diameter with the diameter at the base

of the stem and the considerable to very strong

positive correlation between the total height of

the tree with crown height and crown volume,

indicate that they grow as the diameter at the

base of the stem and height increase, respec-

tively (Table 2). It is observed that as the tree

increases in height the crown height increases

and at the same time the crown volume increas-

es. As the crown height increases, the crown

diameter increases, and as the crown diameter

increases, the pod production increases.

The mean positive correlation to consid-

erable correlation between crown diameter

TABLE 1

Dasometric variables of the tree S. spectabilis in tropical dry forest (Colombia)

Variable Height range Average Standard deviation Minimum Maximum

Total height of the tree (m) Average 6.16 1.23 3.87 8.35

< 6 m 5.21b 0.56 3.87 5.81

6 m 7.27a 0.75 6.02 8.35

Crown height (m)

Average 3.41 0.98 1.64 5.43

< 6 m 2.72b 0.53 1.64 3.47

6 m 4.21a 0.74 3.04 5.43

Height to the first branch (m)

Average 2.75 0.52 1.99 4.16

< 6 m 2.49b 0.30 1.99 3.05

6 m 3.06a 0.55 2.21 4.16

Diameter at the base of the stem (cm)

Average 20.43 4.80 10.6 31.1

< 6 m 20.18a 5.38 10.6 28.15

6 m 21.43a 4.13 15.0 31.1

Crown diameter (m) Average 7.46 1.20 4.57 9.39

< 6 m 7.12a 1.20 4.57 8.93

6 m 7.92b 1.09 6.01 9.39

Crown volume (m)

Average 108.43 61.38 17.63 271.11

< 6 m 70.05b 28.59 17.63 118.56

6 m 153.98a 57.67 85.83 271.11

Pod production (kg)

Average 32.73 16.13 9.17 68.55

< 6 m 27.63a 14.72 9.17 68.55

6 m 39.00a 15.48 17.93 61.74

Dry pod production (kg)

Average 19.82 9.77 6.03 45.04

< 6 m 16.73a 8.92 6.03 45.04

6 m 23.62a 9.38 11.78 40.56

Dry matter of pod (kg)

Average 17.84 8.80 5.42 40.53

< 6 m 15.06a 8.03 5.42 40.53

6 m 21.26a 8.44 10.60 36.50

Different letters within the column for each variable indicate statistically significant differences, where * Significant

correlation at level 0.05, ** Significant correlation at level 0.01.

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with the diameter at the base of the stem and

positive considerable correlation to very strong

correlation between the total height of the tree

with crown height and crown volume, indicate

that they grow as the diameter at the base of the

stem and height increase respectively (Table

2). It is observed that as the tree increases in

height, the crown height increases and at the

same time the crown volume increases; as the

crown height increases, the crown diameter

increases, and as the crown diameter increases,

the pod production increases.

Models to predict pods production: The

best results of the univariate regression analysis

between tree and pod production used the daso-

metric variable measurements. The findings

indicate that the univariate models do not offer

a good estimation of pod production. This is

due to the largest R

adj being 0.327, between

crown diameter and pod production in a loga-

rithmic model and the measurement of height

to the first branches does not allow an estimate

of pod production.

The multivariate analysis with the stepped

regression method allowed the generation of

the linear model (equation 12), linear with

interactions model (equation 13), and poly-

nomial of second order model (equation 14).

Table 3 shows the results of the goodness of

fit and the results of the residue normality test.

The linear model presented a mean positive

regression; the linear model with interactions

and the second-order polynomial model

showed a positive regression from consider-

able too strong with pod production. Although

the pod production presents a high coefficient

of variation, with multivariate models, it is pos-

sible to generate a better prediction of the pod

production regarding the univariate analysis.

In Fig. 1, it can be seen that the linear model

with interactions and second-order polyno-

mial model have a better distribution between

the observed and estimated data. The random

distribution of the data and residues indicates

that there is homoscedasticity. The result of the

analysis multivariate regression indicated that

the second-order polynomial model presented

the best goodness of fit.

Tree occlusion percentage in S. spectabilis

was 73.4 7.92 % (CV = 10.8 %), the cup area

was 49.3 m

tree

-1

, the shadow area was 36.2

tree

-1

, the number of trees for ha

-1

was 83

trees, the potential production of pods in a

silvopastoral arrangement with S. spectabilis

could be 2.72 t ha

-1

of pods, and 1.64 t ha

-1

dried pods.

DISCUSSION

The specific allometric equations are

convenient because tree species can differ

greatly in tree architecture (Ketterings, Coe,

Van Noordwijk, Ambagau, & Palm, 2001). In

general, bifurcation patterns, branching, and

irregular and relatively complex crown shapes

TABLE 2

Pearson correlation matrix for and between measures of S. spectabilis tree dasometric variables and pod production

Variables

Total height

of the tree

Crown

height

Height to

the first branch

Crown

diameter

Crown

volume

Total height of the tree 1 0.000 0.000 - 0.031 0.000

Crown height 0.914** 1 0.001 0.043 0.001 0.000

Height to the first branch 0.635** 0.586** 1 - - 0.000

Diameter at the base of the stem - 0.372* - 1 0.000 0.004

Crown diameter 0.395* 0.586** - 0.714** 1 0.000

Crown volume 0.804** 0.942** 0.752** 0.530** 0.752** 1

Pod production - - 0.592** 0.446* 0.592** -

Above the diagonal the values of p are presented. Below the diagonal, the correlation values are presented, where *

Significant correlation at level 0.05, ** Significant correlation at level 0.01.

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TABLE 3

Results of the indicators for the selection of the best model, normality test of residuals and models

Models Value

adj RMSE AIC BIC

C Value C Value C Value C Total

Linear 0.51 3 11.53 3 1730.5 1 858.9 2 9

Linear with interactions 0.65 2 9.80 2 1737.5 3 861.7 3 10

Second-order polynomial 0.83 1 6.80 1 1735.6 2 856.2 1 5

Linear

Linear with interactions:

Second-order polynomial:

Lilliefors 95 % test, where: R

adj = adjusted correlation coefficient, RMSE = the square root of the mean square of the error,

AIC statisticians = Akaike information criterion, BIC = Bayesian information criterion, C = sum of the indicators. Where:

= Diameter at the base of the stem, X

= Crown height, X

= Crown diameter, X

= Crown volume, X

= Total height of

the tree, X

= height to the first branch. The model with the best fit according to the sum of the R

adj, RMSE, AIC and BIC

statistics was the second-order polynomial.

Fig. 1. Distribution of the observed and estimated data with A. linear, B. linear models with interactions and C. second-order

polynomial for estimation in the production of pods in S. spectabilis.

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make it difficult to adjust correlative models

between components, even in the same species.

The architecture of the trees is the result

of the influence of ontogenetic and morpho-

genetic factors that affects all levels of orga-

nization of the organism, in each stage of its

development and throughout its life period

(Barthélémy & Caraglio, 2007). Forest param-

eters, such as the location of the tree, the height

of the tree, the number of trees, the diameter of

the crown, and the tree species, are essential for

the quantitative analysis of the forests (Chen,

Baldocchi, Gong, & Kelly, 2006; Koch, Hey-

der, & Weinacker, 2006).

The height of the trees of S. spectabilis

reported in this study was higher than those

reported in Minas Gerais with an average of

5.9 m at 155 months from seed (12.91 years)

(Ferreira, Bothelo, Dadive, & Faria, 2007).

Whereas in Eastern Africa, the characteris-

tics of the tree S. spectabilis was a height of

6.8 ± 0.1 m (Ndoli et al., 2018) and when a

qualitative-quantitative analysis was performed

of shrub-arboreal vegetation of the Caatinga

in Teixeira, Paraiba, Brazil, the report of an

average tree height in S. spectabilis was (11.3

% < 4.05 m; 86.1 % 4.05 ≤ H ≤ 6.16 m, and

2.6 % ≥ 6.15 m) (Leite, 2010). These reports

of different heights may be related to the fertil-

ity of the soils and the specific environmental

conditions of each place. A tree from S. spec-

tabilis at 26 months after planting in Makoika,

Malawi, had a reported height of 3.23-3.42 m

(Maghembe & Prins, 1994). The productivity

of the forest site can be derived from the height

and age of the dominant trees controlled by

the environmental conditions (Corral, Álva-

rez, Ruiz, & Gadow, 2004), especially cli-

matic and phytogeomorphic variables (Dorner,

Lertzman, & Fall, 2002).

Reports on other members of the genus

Senna shows the different characteristics

between the species. In selected plantations

in Colombia with a rainfall of 1 200 mm and

soils with pH 7.8, Senna siamea were found to

have arboreal spread of 3 by 3 m, an age of 3

years, and a height average of 7.5 m (Francis,

Lowe, & Trabanino, 2000); Senna macranthera

(Collad.) were reported at a height of 5.8 m

by Ferreira et al., (2007). Parolin (2001), also

measured Senna reticulata (Willd.) in flood

areas in the Amazon that reached a height of

12 m. In Campinas, Brazil, other species of

the fabaceae family were also researched. Cen-

trolobium tomentosum had reported heights of

10.18 ± 3.26 m; Holocalyx balansae Micheli

had a height of 10.26 ± 2.6 m and Machaerium

nyctitans (Vell.) Benth had heights of 8.84 ± 2.9

m (Dias, dos Santos, Maës, & Martins, 2017).

The crown diameter in this differs from

those mentioned in Eastern Africa, where the

tree canopy radius was 4.7 ± 0.1m with the

tree´s age given by the owner as 21.9 ± 0.9

years (an estimated crown diameter of 9.4 m)

(Ndoli et al., 2018). Possibly, this result is relat-

ed to the tree´s age, in the case of “La Comarca

farm,” the estimated age of the trees does not

exceed 20 years. Other research reports that

S. reticulata trees of 4-8 m in height have the

densest canopies, with diameters that reach 4-6

m (Parolin, 2001).

In this study, the production of pods of S.

spectabilis was related to crown diameter and

crown volume; while in Acacia pennatula,

found that the production of pods is strongly

related to the diameter of the tree, which at

the same time is correlated with the height and

coverage of the tree (Purata, Greenberg, Barri-

entos, & López-Portillo, 1999). In Astrocaryum

standleyanum a positive association between

spatial variation in pod density and spatial den-

sities of photodetected crowns; spatial densities

of soil stems and stem diameters were found

(Jansen et al., 2008).

A description of the production of pods of

other tree species was made since no reports

were found in the literature of pod production

in S. spectabilis. In Prosopis alba, the control

trees in Argentina produced 32 kg of pods

(Ewens & Flecker, 2010). In Prosopis chilen-

sis, the control trees in Egypt produced 9.8 kg

of pods (Faramawy, 2014).

Trees S. spectabilis with a range of height

equal to or more than 6 m had higher averages

in the dasometric variables of height, crown

height, height to the first branch, and crown

227

Rev. Biol. Trop. (Int. J. Trop. Biol.) • Vol. 69(1): 218-230, March 2021

volume with respect to trees shorter than 6 m.

This is possibly because the taller trees are at a

more developed stage.

It is possible that the low coefficient of

determination of the univariate models is due

to the fact that the variable pod production in S.

spectabilis presents a high coefficient of varia-

tion in tree

-1

pod production. This corresponds

to 49.28 % for the average of all trees, 39.69 %

for trees equal to or taller than 6 m and 55.25

% for trees shorter than 6 m. On the other hand,

a single dasometric measurement could hardly

explain the production of pods, given that

this variable is complex and depends on other

dasometric measurements from the tree. The

quality of the soil, the amount of rainfall, their

distribution, and other factors, are all variables

that affect production.

In trees dispersed in the pastures of Mag-

dalena Medio Tolimense in Colombia, the per-

centage of occlusion was evaluated and it was

found that Anagyris foetida presented an occlu-

sion value of 92 %. Other species established

in the silvopastoral systems of the dry tropics

in the Fabaceae family presented values with

lower occlusion. These species were Senna

spectabilis, Phithecelobium dulce, Pseudosa-

manea guachapele, and Prosopis juliflora, with

73.4 %, 71 %, 64 % and 63 % respectively

(Serrano, 2013).

An interesting aspect of the introduction

of S. spectabilis as a scattered tree species is

that by supplying the pods to cattle, the seeds

are sown in fertile feces and the seedlings are

not consumed by the animals. This allows dif-

fusion of the trees in the silvopastoral system,

a supplementary source of pod production, and

shade for the animals in the warm environments

of the tropics, an increase in seed availability

for nurseries, and the generation of a potential

source of galactomannans for the industry.

The production of fresh pods per tree in the

S. spectabilis presents a potential in its avail-

ability as feed for ruminant or seed production.

The potential production of pods in sil-

vopastoral with S. spectabilis could be 2.72 t/

ha, and 1.64 t/ha of dry pods, this shows the

importance of trees and of pods production

and nutritional contribution obtained for

dry ecosystems.

Ethical statement: authors declare that

they all agree with this publication and made

significant contributions; that there is no con-

flict of interest of any kind; and that we fol-

lowed all pertinent ethical and legal procedures

and requirements. All financial sources are

fully and clearly stated in the acknowledge-

ments section. A signed document has been

filed in the journal archives.

ACKNOWLEDGMENTS

Our research is supported by the project:

Innovación y gestión técnico científica para el

desarrollo de la cadena ovino caprina del Tol-

ima “INNOVIS” of Gobernación del Tolima,

project registered in the Office of Research and

Scientific Development of the Universidad del

Tolima with the code [730115]. To the Engineer

Mario Vanegas for facilitating the property.

RESUMEN

Producción de vainas, y variables dasométricas,

del árbol Senna spectabilis (Fabaceae) en un bosque

seco tropical. Introducción: Senna spectabilis es un

árbol pantropical multipropósito, utilizado en sistemas

agroforestales. Objetivo: Determinar la producción de

vainas (Pv) y la relación con las variables dasométricas

en S. spectabilis en el bosque seco tropical. El número

potencial de árboles/ha (NPa) fue calculado determinando

el porcentaje de oclusión (Po) y el área de sombra/árbol

(As); para calcular la producción potencial de frutos/ha,

la producción de frutos/árbol fue multiplicada por (NPa).

Métodos: Desde agosto del 2016 hasta febrero de 2017,

treinta árboles en etapa de producción fueron selecciona-

dos al azar, los más aislados del total de árboles dispersos

fueron seleccionados, y fueron monitoreados al inicio y al

final del período de estudio, para determinar las mediciones

dasométricas como la altura total (At), altura a la primera

rama (Apr), altura de la copa (Ac), diámetro del tallo (a 0.2

m altura desde el suelo) (Dt), diámetro de la copa (Dc) y

volumen de copa (Vc). Las vainas se cosecharon cuando

su color comenzó a cambiar. Se realizaron correlaciones

de Pearson y análisis de regresión univariada y multi-

variada entre las variables dasométricas y la producción

de vainas. El número potencial de árboles/ha (NPa) se

calculó determinando el porcentaje de oclusión (Po) y el

área de sombra/árbol (Asa); para estimar el potencial de

228

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producción de las vainas/ha, la producción de vainas/árbol

se multiplicó por NPa. Resultados: la At fue de 6.16 ±

1.23 m, Apr 2.75 ± 0.52 m, Ac 3.41 ± 0.98 m, Db 20.43 ±

4.80 cm, Dc 7.46 ± 1.20 m y Vc 108.43 ± 61.38 m

/árbol.

Existió una correlación positiva significativa entre Apr, Dc,

Db, Pv de 0.592**, 0.592 ** y 0.446 * respectivamente.

La Pv fue de 32.73 ± 16.13 kg y la producción de materia

seca (PMS) fue de 17.84 ± 8.80 kg/árbol. El resultado de

la regresión multivariada indicó que el modelo polinomial

de segundo orden presentó la mejor bondad de ajuste. El

Po de los árboles fue de 73.4 % ± 7.92 %, el área de copa

fue de 49.3 m

/árbol, el Asa fue de 36.2 m

/árbol, el NPa

fue de 83 árboles. Conclusiones: La producción de vainas

frescas/árbol en el S. spectabilis presenta un potencial en

la disponibilidad de alimento para los rumiantes o la pro-

ducción de semillas. El potencial de producción de vainas

en u arreglos silvopastoriles podría ser de 2.72 t/ha, y 1.64

t/ha de vainas secas, esto muestra la importancia del árbol

de producción de vainas y la contribución nutricional para

los ecosistemas secos.

Palabras clave: vainas, morfometría; modelos de predic-

ción; árboles dispersos; silvopastoril.

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