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https://doi.org/10.37815/rte.v34n4.978

Artículos originales=

 

Caracterización morfológica del cacao nacional “Theobroma cacao L.” del cantón Naranjal, Ecuador

Morphological characterization of the national cocoa "Theobroma cacao L." of Naranjal, Ecuador<= span lang=3DEN-US style=3D'font-size:10.0pt;mso-ansi-language:EN-US'>=

 

Carlos Amador Sacoto1 h= ttps://orcid.org/0000-0002-5534-5474,

Arturo Alvarado Barzallo<= span style=3D'mso-bookmark:_Hlk61880979'>1=   https://orcid.org/0000-0002-9806-9684, Simón Ezequiel Farah Asang1 https://orcid.org/0000-0003-3245-2936, Juan Javier Martillo Garcia1 https://orcid.org/0000-0002-0182-666X

 

1Universidad Agra= ria del Ecuador, Guayaquil, Ecuador

camador@uagraria.edu.ec, aealvarado@uagraria.edu.ec, sfarah@uagraria.edu.ec, jmartillo@uagraria.edu.ec 

 

Enviado:         2022/09/22

Aceptado:       2022/12/10

Publicado:      2022/12/30                         

Resumen

La investigación se realiza en una zona del cantón Naranjal y para e= ste estudio participan 10 fincas aleatoriamente seleccionadas. Estas fincas se dedican a la producción del cacao nacional o fino de aroma. Adicionalmente,= en estos lugares, se desarrollan las observaciones y mediciones destinadas a c= aracterizar morfológicamente este cultivo de cacao originado a partir de variedades de = los tipos Forastero y Trinitario. Para su análisis se aplicaron parámetros de estadística descriptiva a un grupo de variables morfológicas como: peso, la= rgo y ancho del fruto, rugosidad, grosor y coloración del pericarpio, y número = de semillas por fruto. Se tomaron 10 mazorcas. Y de cada mazorca se describier= on 5 semillas, de estas se tomaron determinaciones de variables como peso, largo ancho y espesor de la semilla, peso de la pulpa y testa. A más de ello, se escogieron 10 flores al azar de cada planta para medir sus estructuras. Lue= go de analizar cada una de estas variables de forma individual, se aplicó un análisis de regresión múltiple, para obtener información del grado de participación de las variables. Finalmente, se obtuvo variables de coloraci= ón de peso, forma y rugosidad del fruto para separar las plantas evaluadas por características fenotípicas similares, las que se sometieron a un ANDEVA pa= ra evidenciar cuál de los grupos tenía mayor variabilidad estadística. Se enco= ntró una mayor participación del tipo forastero y menor del trinitario. Se const= ató que los caracteres de mayor importancia se encuentran en el fruto. <= /p>

 

Sumario: Introducc= ión, Materiales y Métodos, Resultados y Discusión y Conclusiones.

 

Como citar: Amador, C= ., Alvarado, A., Farah, S. & Martillo, J. (2022). Caracterización morfológica d= el cacao nacional “Theobroma cacao L.” del cantón Naranjal, Ecuador. R= evista Tecnológica - Espol, 34(4), 80-97. http://www.rte.espol.edu.ec/index.php/tecnologica/article/view/9= 78


<= i>Palabras clave: cacao nacional, caracterización morfológica, fruto, semilla, cultivar.

Abstract

This investigation was carried= out in Naranjal in ten randomly selected farms.  These farms produce national or fine-aroma cocoa. Observations and measurements were made to morphologically characterize the Forastero and Trinitario cocoa. Descriptive statistics parameters were applied to a group= of morphological variables such as weight, length, and width of the fruit, rou= ghness, thickness and coloration of the pericarp, and number of seeds per fruit, of each of the plants that make up the sample, according to which ten ears were taken and from each ear, five seeds were described taking determinations of variables such as weight, length, width and thickness of the seed, weight of the pulp, and taste. Likewise, ten random flowers were taken from each plan= t to measure their structures. After the analysis of each of these variables individually, a multiple regression analysis was applied to obtain informat= ion on the degree of participation of the variables. Then, the variables of coloration, weight, shape, and roughness of the fruit were obtained to sepa= rate the evaluated plants for similar phenotypic characteristics, that were late= r subjected to an ANOVA to show which of the groups had greater statistical variability= . A greater participation of the Foreign type and less of the Trinitarian type = was found. Also, it was found that the most important characters for the characterization are found in the fruit.

 

Keywords: national cocoa, morphological characterization, fruit, seed, cultivate.

 

Introducción

Ecuador se caracteriza por poseer un cacao fino de aro= ma con características organolépticas y sabor agradable lo que le permite ser reco= nocido en el ámbito mundial por la calidad que presentan sus productos derivados. = El sector cacaotero nacional representa a un segmento económico importantes pa= ra el país.

 

La baja productividad de las plantas de cacao nacional provoca que muchos agricultores se vean obligados a sembrar nuevas variedad= es más productivas como los clones de ccn-51, que presentan mayor resistencia a plaga= s o enfermedades o híbridos que se puedan adaptar con más facilidad a las condiciones climáticas y edáficas del lugar. Más del 70% de la producción mundial de cacao fino y de aroma se encuentra en Ecuador, convirtiéndolo en= el mayor productor de este fruto (Mosquera, B. 2015).

 <= /span>

Las principales áreas del país donde se cultiva cacao = de tipo Nacional son: Naranjal, Tenguel, Balao Chico y Naranjito (provincia del Guayas); ciertas áreas cacaoteras de las provincias de la Sierra (Bolívar y Cotopaxi); y, en la cuenca del Amazonas, donde se han reportado áreas de ca= cao Nacional en estado silvestre (Quiroz 1997). Existe en Ecuador una gran vari= edad de materiales genéticos, de los cuales se pueden mencionar: EET 95 EET 96, = EET 103 y EET 576. Estas variedades se las puede identificar mediante características taxonómicas y ubicarlas dentro del grupo de cacao Nacional “arriba” (Romero C, et al 2010).

 

Los frutos de cacao son una drupa bastante grande, los= que están sujetos por un pedúnculo que se origina del pedicelo de la flor. Los frutos tienen cinco lóculos, cada lóculo posee dos partes formadas cada una= por dos lomos y un surco interno. Su forma varía y esto ha dado lugar a que se pueda realizar una clasificación de distintos genotipos (Enríquez, 2004).

 

Las semillas son de forma oblonga, tienen un recubrimi= ento o cutícula que protege a los cotiledones; y en la parte exterior está el muci= lago o hilio que es la parte dulce mucilaginosa la cual permite la fermentación = de la semilla, además se puede diferenciar algunos genotipos de cacao por su s= abor (Enríquez, 2004).

Las poblaciones de cacao provenientes de la Amazonía se denominan forastero. Los tipos criollos y forasteros son considerados como = dos subespecies distintas y se pensó que eran originarias de Centro y Sur Améri= ca, respectivamente. Un tercer grupo se identifica como trinitario y es descrito como híbrido entre criollo y forastero. Las utilizaciones de marcadores moleculares sobre estos individuos han podido dar respuestas sobre la domesticación y más específicamente sobre la deriva genética (Motomayor, 2002).

 

Los cacaos criollos se caracterizan por ser arboles relativamente bajos y menos robustos respecto a otras variedades. Su copa es redonda con hojas pequeñas de forma ovalada, de color verde y rojizas en es= tado inmaduro tornándose amarillas y anaranjadas cuando están maduras, las almen= dras son de color blanco marfil (Perez, 1996).

 

El cacao forastero es un tipo de cacao mucho más resis= tente, y por tal razón, abarca el 90% de la producción cacaotera mundial. Su princ= ipal característica es su fuerte amargor, alta astringencia y falta de aroma. Las mazorcas son verdes en estado inmaduro, tornándose amarillas en estado de madurez (Quiroz, 2009)= .

 <= /span>

El cacao trinitario proviene de la hibridación entre l= os grupos criollo y forastero. La mayoría de las variedades conocidas que se cultivan comercialmente en el mundo, se han seleccionado a partir de este g= rupo (Enríquez, 2004). Fueron seleccionados en trinidad y de ahí su nombre. Sus características botánicas son intermedias entre el criollo y forastero. Los tipos existentes se denominan de acuerdo con los nombres proporcionados en = los centros de investigación de donde fueron seleccionados (Arguello, 2001).

 

El Cacao Nacional se clasifica botánicamente como el t= ipo forastero, puesto que tiene algunas características fenotípicas de este. Po= see un sabor y aroma característico del cacao criollo, muy apreciados en las industrias de todo el mundo. Tradicionalmente se conoce al cacao ecuatoriano como Cacao Arriba, debido a que se cultivaba en la zona superior del río Gu= ayas (río arriba), denominación que se convirtió en sinónimo de buen sabor y aro= ma floral de jazmín, rosas y lilas (MAG/IICA, 2001).

 

Existen varios tipos de caracterización entre las que = se pueden mencionar:

 

      =   Caracterización morfológica

      =   Caracterización molecular

      =   Caracterización física

      =   Caracterización fisiológica

 

Caracterización Morfológica. Un descriptor es un atrib= uto cuya expresión es fácil de medir de la forma, estructura o comportamiento de una accesión. Sirve para discriminar entre fenotipos. Los descriptores son altamente heredables, pueden ser detectados a simple vista y se expresan de igual forma en todos los ambientes (Franco e Hidalgo, 2003).  Los órganos más importantes para la descripción morfológica son aquellos que están menos influenciados por el ambiente. Los más importantes son: la flor y el fruto (Enríquez, 2004). Han sido empleados para caracterizar el germoplasma de las colecciones en diferentes centros de investigación tales como el CATIE, el ICGT y el ICGD, entre otros (End et. al., 2010).

 

Pound (1933), señala que a= lgunas características de la flor y la semilla son de suma importancia en la caracterización de clones de cacao, lo cual es confirmado por Dejean (1984) y Ostendorf= (1965). Enríquez y Soria (1967), proponen una lista de 11 caracteres para la evalua= ción de las flores, que fueron usados por Engels (1983) y B= artley (2000.). Para la caracterización morfológica Williams y Damania (1981) recomiendan 35 frutos.  Las características de las almendras: ancho, largo, espesor, peso húmedo sin te= sta, peso seco sin testa, porcentaje de testa y pulpa, están entre los mejores descriptores para caracterizar una población, usando una muestra de 12 a 20 mazorcas (Braudeau, 2000).

 

Esta investigación pretende realizar un estudio de caracterización del cultivo de cacao con visión a proporcionar información referente a las diferentes características físicas y morfológicas del culti= vo de cacao presentes en el cantón Naranjal de la provincia del Guayas.

 

Materiales y Mét= odos

Esta investigación se realizó= en diez fincas distribuidas en diferentes parroquias del cantón Naranjal, provincia= del Guayas, con las coordenadas UTM: X 653706,31m; Y 9704447,94m, latitud: 02° = 40' 23,34" S y longitud: 79° 37' 2,35" W con un comportamiento climatológico dado por temperatura máxima: 31.5 °C, temperatura mínima: 19.8 °C, temperatura media: 25.7 °C, humedad Relativa: 95%, altitud: 25 msnm.

 <= /o:p>

El cantón Na= ranjal cuenta con alrededor de 1500 hectáreas cultivadas de cacao nacional, dentro= de la zona cacaotera tipo nacional se encuentran pequeñas plantaciones de superficie que van de entre 5 a 10 hectáreas (Municipalidad de Naranjal 201= 0). Las fincas de Cacao Nacional pertenecen por lo general a pequeños productores que van de entre una a diez hectáreas, no cuentan con infraestructuras óptimas de tecnología productiva, sistemas de riego ni métodos especializados de fertilización, muchas de estas son producidas de manera silvestre, en donde solo se realizan prácticas de limpieza una vez al año, generando un bajo ni= vel en producción y rendimiento de estas fincas.

 

Se realizó un muestreo no probabilístico, seleccionando 10 fincas distribuidas en la zona= . En cada finca se estableció un reconocimiento de variedades existentes dentro = de la plantación, luego se seleccionó los 10 mejores arboles al azar, resisten= tes a plagas y enfermedades, altamente productivos, color de mazorcas característicos, olor, tamaño, forma de las mazorcas, entre otras para la evaluación de las diferentes variables de caracterización (Águila et. al., 2012).

 <= /o:p>

Las variables empleadas para el proceso de caracterización de frutos, flores y árbol fuer= on las siguientes: largo del fruto, ancho del fruto, peso de la cáscara, espes= or de la cáscara en el lomo, espesor de la cáscara en el surco, número de semi= llas por fruto, peso de semillas por fruto, largo de semillas, ancho de semillas, espesor de semillas, forma del fruto, constricción basal.

 <= /o:p>

En Flores: l= argo del sépalo, ancho del sépalo, largo de la lígula, ancho de la lígula, largo del estaminodio, largo del ovario, ancho del ovario, forma de la lígula, largo = del pedúnculo. Para realizar la caracterización de las flores se tomaron 5 flor= es por planta de las diez plantas seleccionadas de las 10 fincas evaluadas.=

 

El largo del estaminoide y del estilo. Se los realizó con la ayuda de una hoja milimetra= da.

 <= /o:p>

La forma de = la lígula y largo del pedúnculo. La medición se logró con la ayuda de una hoja milimetrada. La forma de lígula se basa en la multiplicación del largo de la lígula por ancho de la lígula.

Además, tamb= ién se tomaron las siguientes características como variables morfológicas del árbo= l: altura del árbol, vigor del árbol, índice de mazorcas, coloración de frutos, rugosidad de pericarpio, forma del ápice (Ayestas, 2013).

 <= /o:p>

Altura del á= rbol (m). Se tomó una altura promedio de todas las plantas en cada lote provisto para el ensayo, expresado en metros. Y se lo tomó por inspección visual.

 <= /o:p>

Vigor del Ár= bol. Para el vigor se tomó en cuenta la siguiente tabla realizada por el INIAP e= n el 2007 y citada por Mario Águila en el 2012.

 <= /o:p>

1 =3D 20% En= deble (Frágil)

2 =3D 40 % V= igor bajo

3=3D 60% Vig= or medio

4=3D 80 % Vi= goroso

5=3D 100% Mu= y vigoroso (Águila et. al., 2012)

 <= /o:p>

Índice de Ma= zorca. Se tomó en cuenta la cantidad de mazorcas sanas encontradas durante todo el tiempo que se realizó este trabajo de tesis.

 <= /o:p>

Peso de Mazo= rcas (g). Se tomó, con la ayuda de una báscula electrónica, el peso que presenta= una mazorca en el momento de la cosecha y se lo expresó en gramos.

 <= /o:p>

Forma del áp= ice, se utilizó una escala arbitraria con valores de: 1.-Puntiagudo, 2.-Agudo, 3.-O= btuso, 4.- Redondeado, 5.- Pezón, 6.- Dentado.

 <= /o:p>

Diámetro del= Fruto (cm). Se tomó en cuenta el diámetro medio de entre todos los frutos de las muestras dentro de cada lote y se realizó con la ayuda de un calibrador de Vernier la medición y se la expresó en centímetros.

 <= /o:p>

Número de Se= millas. Se tomó en cuenta la cantidad de semillas obtenidas en cada una de las mazo= rcas que presentaron los árboles evaluados, teniendo una media por cada árbol.

 <= /o:p>

Coloración d= e los Frutos. Se realizó el análisis de caracterización mediante la coloración de= los frutos y se tomó en cuenta los árboles que tengan la misma coloración y características fisiológicas de los frutos de la misma pigmentación. Esto se realizó mediante la inspección visual directa. Para la identificación de ca= da tipo de coloración se tomó la siguiente codificación o escala arbitraria: 1= =3D amarillo; 2=3D rojo; 3=3D anaranjado; 4=3D morado; 5=3D café.

 <= /o:p>

Forma del fr= uto. Se empleó la escala arbitraria empleada donde: 1=3DAngole= ta, 2=3DCundeamor, 3=3DAmelonado, 4=3DCalabacín.

 <= /o:p>

Largo del Fr= uto (cm). Se consideró el largo de la mazorca, promediando entre todos los frut= os obtenidos en una planta, se midió con la ayuda de un calibrador de Vernier expresado en centímetros.

 <= /o:p>

Rugosidad de= l fruto. Se evaluó empleando una escala arbitraria donde: 1=3DRugoso, 2=3DSemi-Rugos= o, 3=3DLiso, 4.- Medianamente liso.

 <= /o:p>

Constricción= basal. Se aplicó una escala arbitraria donde: 1=3DAusente, 2=3DEscasa, 3=3DInterme= dia, 4=3D Bien marcada, 5.- Muy ancha.

Forma del áp= ice. Se usó una escala arbitraria donde: 1=3Dpuntiagudo, 2=3Dagudo, 3=3Dobtuso, 4= =3Dredondeado, 5=3Dpezón, 6=3Ddentado.

 <= /o:p>

Forma de la = lígula. Se basa en la multiplicación del largo por el ancho de la lígula.

 <= /o:p>

Peso de la C= áscara (g). Se basó en el peso que presentó la cascara de la mazorca al momento de= la cosecha, se realizó con la ayuda de una báscula electrónica expresada.

 <= /o:p>

Peso de Semi= llas Húmedas (g). Se tomó en cuenta cinco semillas por mazorca específicamente e= n la parte media de cada mazorca, el peso se realizó con la ayuda de una báscula electrónica expresado en gramos.

 <= /o:p>

Se aplicaron= a las variables estudiadas, los cálculos de estadígrafos descriptivos como: media, intervalo de confianza, rango, máximos y mínimos. Se utilizaron los coeficientes de regresión múltiple para determinar el nivel de dependencia = del peso del fruto con el resto de las variables asociadas a él. Esto también se aplicó a la dependencia del largo del pétalo a las otras variables asociada= s a la flor.

 <= /o:p>

Resultados y Discusión

Caract= erización de Árboles

La  REF _Ref121678575 \h = Tabla = 1 muestra los valores de las variables altura del árbol, vigor= del árbol e índice de mazorcas. La altura de árbol presentó una media de 7.27 m= y un intervalo de confianza de 0.35 m, un valor máximo de 7.61m y un mínimo de 6.93m. El valor medido en una escala arbitraria del 1(bajo), al 5 (muy alto) obtuvo una media de 2.97, un intervalo de confianza de 0.19, alcanzó como v= alor mínimo 2.78 y un valor máximo de 3.15, es decir, los árboles descritos presentan un vigor medio. Por su parte, el índice de mazorcas alcanzó una m= edia de 15.24, un intervalo de confianza de 0.78, con valor mínimo 14.46 y valor máximo 16.03, para un rango de entre 14 y 16 mazorcas por árbol entre las fincas evaluadas.

 

Tabla 1=

Estadí= grafos descriptivos de Altura del Árbol, Vigor del Árbol e Índice de Mazorcas=

PARÁMETRO

ALTURA DEL ÁRBOL

VIGOR DEL ÁRBOL

ÍNDICE DE MAZORCAS

Media

7,27

2,96

15,24

Interv. de confianza=

0,34

0,18

0,78

Mínimo<= /span>

6,92

2,78

14,45

Máximo<= /span>

7,61

3,15

16,03

Promedios máximos y mínimos con un intervalo de confianza del 0.05

Fuente: Alvarado B. Arturo, 2015.

 

Caract= erización de Frutos y Semillas

Los resultad= os obtenidos en la forma del ápice (según la escala nominal aplicada) se muest= ran en la Tabla 2, con una media de 2.93, con valor máximo de 3.011, y un míni= mo 2.84 lo que indica que la forma del ápice se encuentra entre agudos y obtus= os. De igual forma en la misma tabla se exponen los valores concernientes a la rugosidad del fruto donde se utilizó la escala arbitraria siguiente: 1.- Rugoso, 2.-Semi-Rugoso, 3.- Liso, 4.- Medianamente liso. La Tabla = 2 presentó el promedio de 1.61, valor máximo 1.78 y valor míni= mo 1.44 respectivamente es decir el fruto presenta en el rango rugoso.<= /p>

 <= /o:p>

 <= /o:p>

Tabla 2=

Estadí= grafos descriptivos de las variables forma del ápice y rugosidad del fruto

ANÁLISIS

FORMA DEL ÁPICE<= /p>

RUGOSIDAD DEL FRUTO

Media

2,92

1,61

Interv de confianza

0,08

0,16

Mínimo

2,84

1,44

Máximo

3,01

1,77

Promedios máximos y mínimos con un intervalo de confianza del 0.05

Fuente: Alvarado B. Arturo, 2105.

 

Una comparac= ión de los parámetros estadísticos descriptivos de las variables anteriores se mue= stra en la Tabla 3.

 

Tabla 3=

Estadí= grafos Descriptivos de las Características del Árbol y el Fruto

V= ARIABLES

P= ROMEDIO

D= ESVIACIÓN ESTÁNDAR

R= ANGO

I= NTERVALO DE CONFIANZA

C= OEFICIENGTE DE VARIACIÓN

Altura del árbol

7,27

1,69

6.00

0,34

23.25 %=

Vigor del árbol

2,96

0,91

3.00

0,18

30.74 %=

Índice de mazorcas

15,24

3,86

3,87

0,78

25.33 %=

Forma del Ápice

2,92

1,23

6.00

0,25

42.12 %=

Rugosidad del fruto<= /o:p>

1,61

0,82

2.00

0,16

50.93 %=

Fuente:= Alvarad= o B. Arturo, 2015.

 <= /o:p>

En la Tabla = 4 se encuentran reflejados los valores de las variables del fr= uto: peso, largo y ancho.

 <= /o:p>

Tabla 4=

Estadí= grafos Descriptivos del largo del fruto y ancho del fruto=

ANÁLISIS

PESO DEL FRUTO=

LARGO DEL FRUTO

ANCHO DEL FRUTO

Media

588,06 g

17,04

8,55

Interv. de Confianza

38,10 gr

0,58

0,18

Mínimo

549,96 gr

16,46

8,37

Máximo

626,16 gr

17,62

8,73

Promedios máximos y mínimos con un intervalo de confianza del 0.05

Fuente: Alvarado B. Arturo

 

El peso del fruto presentó un promedio de 588,06 g, el valor máximo = para esta variable alcanzó 549,96 g 7 valor mínimo y 626,16 g. En cuanto al largo del fruto (Tabla = 4), este presentó una media de 17.04 cm, con un valor mínimo un 16.46 cm y máximo de 17.62 cm= . Para el ancho del fruto la misma tabla muestra una media de 8.55 cm, con va= lor mínimo 8.37cm y valor máximo 8.73cm respectivamente.

 

La  REF _Ref121679960 \h = Tabla = 5 indica el peso de la cáscara con un valor promedio 480.81 g, valor mínimo 446.56 g y valor máximo 515.03 g respectivamente. También la <= /span>Tabla = 6, muestra el espesor de la cáscara en el lomo con una media de 1.29 cm, un mínimo de 1.21 cm y un valor máximo 1.35 cm respectivamente. Igualmente, y en la misma tabla se observa el espesor de la cáscara en el s= urco con promedio de 0.96 cm, un valor mínimo de 0.91cm y un valor máximo un 1.0= 3 cm respectivamente.

 =

Tabla 5=

Estadí= grafos Descriptivos del Peso y Espesor de la Cascara en el Lomo y en el Surco=

ESTADÍRAFOS

PESO DE=

LA CASCARA

ESPESOR DE LA<= /span>

CASCARA EN EL LOMO

ESPESOR DE LA<= /span>

CASCARA EN EL SURCO<= /o:p>

Media

480,80

1,285

0,965

Interv. De confianza

34,22

0,068

0,059

Mínimo

446,56

1,21

0,91

Máximo

515,03

1,35

1,03

Promedios máximos y mínimos con un intervalo de confianza del 0.05

Fuente: Alvarado B. Arturo, 2015.

 

Como indica la Tabla 6 08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200= 650066003100320031003600380030003500360035000000 el número de semillas presentó una media de 30.86 semillas por fruto, un valor mínimo de 29.57, un máximo de 32.16 semillas por fruto. También la <= /span>Tabla 6 08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200= 650066003100320031003600380030003500360035000000 indica el peso = de semillas por fruto que alcanzó una media de 107.24 g por fruto, un valor mí= nimo de 100.02 g y un valor máximo de 114.46 g de semillas por fruto .

 

Tabla 6=

Estadí= grafos Descriptivos del Número y Peso de Semillas por Fruto

ANÁLISIS

NÚMERO DE SEMILLAS

PESO DE SEMILLAS POR FRUTO

Media

30,86

107,24

Interv. De confianza

1,29

7,23

Mínimo

29,57

100,02

Máximo

32,16

114,46

Promedios máximos y mínimos con un intervalo de confianza del 0.05

Fuente: Alvarado B. Arturo, 2015.

 

A partir de la medición de 5 semillas sin pulpa= y testa de cada mazorca, como indica la Tabla 7 08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200= 650066003100320031003600380031003500300033000000 , el largo de semillas presentó una media de 2.013 cm, un valor mínimo 1.933 cm = y un valor máximo 2.093 cm respectivamente. De la misma forma la <= !--[if supportFields]> REF _Ref121681503 \h Tabla 7 08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200= 650066003100320031003600380031003500300033000000 expresa que el ancho de semillas presentó una media de 1.06 cm, con valores mínimo y máximo 1.1 cm respectivamente. En la misma tabla el espesor de semillas alcanzó una media de 0.79 cm, con valores mínimo y máximo de 0.44 = cm y 1.14 cm.

 

Tabla 7=

Estadí= grafos Descriptivos del Número y Peso de Semillas por Fruto

ESTADÍGRAFO

LARGO DE SEMILLAS

ANCHO DE SEMILLAS

ESPESOR DE SEMILLAS<= /o:p>

Media

2,013

1,061

0,785

Interv. De confianza

0,077

0,040

0,358

Mínimo

1,93

1,02

0,44

Máximo

2,09

1,1

1,14

Promedios máximos y mínimos con un intervalo de confianza del 0.05

Fuente: Alvarado B. Arturo, 2015

 

Para la forma del fruto, empleando una escala nominal arbitraria, se obtuvo un mínimo de 1.583, máximo de 1.935, indicando que las formas del fruto predominante están entre la A= ngoleta y Cundeamor en las 10 fincas evaluadas, como indica la Tabla 8. En cuanto a la constricción basal, empleando una escala similar, arrojó el valor de 1.855 como el valor mínimo y 2.085 para el valor máximo, es decir,= la constricción basal predominante entre las mazorcas evaluadas es escasa. Com= o se indica también en la Tabla 8.

 

Tabla 8= =

Estadí= grafos Descriptivos de la Forma del Fruto y Constricción Basal

ESTADÍGRAFO=

FORMA DEL FRUTO<= o:p>

CONSTRICCIÓN BAS= AL

Media

1,76

1,96

Interv. De confianza

0,17

0,11

Mínimo

1,585

1,855

Máximo

1,935

2,085

Promedios máximos y mínimos con un intervalo de confianza del 0.05

Fuente: Alvarado B. Artur= o, 2015.

 

Un resumen de los estadígrafos descriptivos = de las características del fruto y las semillas se presenta en la Tabla 9.

 

Tabla 9= =

Valore= s de los Estadígrafos de las Características Morfológicas en Frutos y Semillas

VARIABLES

PROMEDIO

DESVIACIÓN ESTÁNDAR

RANGO

INTERVALO DE CONFIANZA

Peso del fruto (PF) gr.<= /b>

588,065

189,478

905,188

38,101

Largo del fruto (LF) cm.=

17.044

2,933

18,298

0,589

Ancho del fruto cm.<= /span>

8,554

0,934

5,012

0,187

Peso de la cascara

480,807

170,220

827,427

34,229

Esp. cascara en lomo=

1,285

0,340

1,15

0,068

Espesor del surco (ES).<= /b>

0,965

0,297

1,13

0,059

Núm. de semillas/fruto

30,858

6,421

30,256

1,291

Peso semillas/fruto gr

107,236

35,938

222,853

7,226

Largo de semillas cm.

2,013

0,387

3,056

0,077

Ancho de semillas cm.

1,061

0,200

1,619

0,040

Espesor semillas cm<= /span>

0,785

1,780

17,638

0,358

Forma del fruto

1,764

0,871

3

0,175

Constricción basal

1,968

0,573

2

0,115

Fuente: Alvarado B. Artur= o, 2015.

 

Se realizó el análisis de regresión intentan= do cuantificar la posible dependencia entre el peso de los frutos con las demás variables de caracterización del fruto y las semillas, los resultados se observan mediante la fórmula siguiente:

 

Y (fruto)=3D I+= x1+x2+x3+……….+x12

 

Donde:

 

Y  =3D  Peso del fruto=

I   =3D  Intersección

X1=3D  Largo del fruto

X2=3D  Ancho del fruto

X3=3D  Peso de la cascara<= /span>

X4=3D  Espesor<= span style=3D'mso-bookmark:_Toc38966068'> de la cascara en el lomo

X5=3D  Espesor de la cascara en el surco=

X6=3D  Número de semillas

X7=3D  Peso total de semillas por fru= to

X8=3D  Largo de semillas

X9=3D  Ancho de semillas

X10=3D<= /span> Espesor de semillas

X11=3D<= /span> Forma del fruto

X12=3D<= /span> Constricción basal

 

Y(fruto)=3D0.39= 7+0.0023x1-0.0004x2+0.999x3-0.136x4+0.074x5-0.0013x6+0.999x7+0.280x8= -0.572x9+0.002x10-0.015x11-0.066x12.

 <= /span>

La Tabla 10 indica, los coeficientes de regresión de las diferentes variables en el peso del fruto, mostrando al peso de la cáscara y el peso total de semillas por fruto los valores positivos y significativos (8.942 y 2.090 respectivamente) con un margen de probabilidad menor al 0.05.

 <= /span>

Tabla 10=

Coefic= ientes de la Regresión de Variables sobre el peso del fruto

VARIABLES

COEFICIENTES

PROBABILIDAD

Intercepción<= /p>

0,397

0,210

Largo del fruto (LF) cm.=

0,002

0,878

Ancho del fruto (AF) cm.=

-0,001

0,992

Peso de la cáscara (PC) gr.

0,999

8,94E-218 *

Espesor de la cáscara en el lomo cm.<= /o:p>

-0,136

0,567

Espesor del surco (ES).<= /b>

0,074

0,775

Número de semillas por fruto (NSP).

-0,001

0,745

Peso total de semillas/fruto (PS) gr.=

0,999

2,09E-172 *

Largo de semillas (LS) cm.

0,280

0,368

Ancho de semillas (AS) cm.

-0,572

0,340

Espesor de semillas (ES) cm.

0,002

0,865

Forma del fruto (LF/AF).=

-0,015

0,589

Constricción basal (CB).=

-0,066

0,126

Datos de probabilidad y significancia al 0.0= 5

Fuente: Alvarado B. Arturo 2015

 

Caract= erización de Flores

Tabla 11=

Estadí= grafos Descriptivos de los sépalos

ESTADÍGRAFO

LARGO DE SÉPALO

ANCHO DE SÉPALO<= o:p>

Media

0,873

0,201

Interv. de confianza

0,014

0,002

Mínimo

0,859

0,199

Máximo

0,886

0,204

Promedios máximos y mínimos con un intervalo de confianza del 0.05

Fuente: Alvarado B. Arturo, 2015.

 

La Tabla 11 detalla los valores promedios de las variables largo y ancho de sépalos con medias de 0.87 cm, y como valor máximo de ancho de sépalo un promedio de 0.= 203 cm. En cuanto al largo y ancho de la lígula la medición se la realizó con la ayuda de una hoja milimetrada y se obtuvieron= los valores que muestra la Tabla 12 donde se observan medias de 0.67 y 0.213 cm respectivamente.

 

Tabla 12=

Estadí= grafos Descriptivos del largo y ancho de la lígula

ESTADÍGRAFOS

LARGO DE LA LÍGU= LA

ANCHO DE LA LÍGU= LA

Media=

0,671=

0,213=

Interv. de confianza

0,008=

0,007=

Mínimo

0,664=

0,205=

Máximo

0,680=

0,221=

 

Promedios máximos y mínimos con un intervalo= de confianza del 0.05

Fuente: Alvarado B. Artur= o, 2015.

 

El largo del estaminoide y del estilo obtuvi= eron medias de 0.58 y 0.28 cm respectivamente como aparecen en la = Tabla 13.

 

Tabla 13=

Estadí= grafos Descriptivos del Largo del Estaminoide y del Estilo

ESTADÍGRAFOS

LARGO DEL ESTAMINOIDE

LARGO DEL ESTILO

Media

0,580

0,280

Interv. de confianza

0,018

0,006

Mínimo

0,561

0,274

Máximo

0,598

0,286

Promedios máximos y mínimos con un intervalo de confianza del 0.05

Fuente: Alvarado B. Arturo, 2015.

 

Tabla 14=

Estadí= grafos Descriptivos del Largo y Ancho del Ovario

ESTADÍGRAFOS

LARGO DEL OVARIO

ANCHO DEL OVARIO

Media

0,208

0,185

Interv. de confianza

0,001

0,004

Mínimo

0,206

0,180

Máximo

0,209

0,189

Promedios máximos y mínimos con un intervalo= de confianza del 0.05

Fuente: Alvarado B. Arturo, 2015.

 

La Tabla 14 refleja promedios para el largo y ancho del ovario de 0.21 y 0.185 cm respectivamente. La Tabla 15 expresa la forma de la lígula, (basada en la multiplicación del largo de la lígula por ancho de la lígula) y el largo del pedúnculo. El largo del pedún= culo (2.01 cm promedio) y la forma de lígula (3.19) se muestran en la Tabla 15.

 

 

 

Tabla 15=

Estadí= grafos Descriptivos de la Forma de la Lígula y Largo del Pedúnculo

ESTADÍGRAFOS<= /p>

FORMA DE LA LÍGULA

LARGO DEL PEDÚNCULO<= /span>

Media

3,191

2,013

Interv. de confianza

0,109

0,068

Mínimo

3,082

1,944

Máximo

3,300

2,082

Promedios máximos y mínimos con un intervalo de confianza del 0.05

Fuente: Alvarado B. Arturo, 2015.

 

En la Tabla 16 se muestran las variables descriptivas: promedios, desviaciones estándar e intervalos de confianza generales de todas las variables morfológicas especificadas en las flores.

 

Tabla 16=

Estadí= grafos Descriptivos de las Características Morfológicas en Flores

VARIABLES

PROMEDIO

DESV. ESTÁNDAR

RANGO

INTERV. DE CONFIANZA

COEFICIENTE DE VARIACION

Largo del sépalo

0,873

0,067

0,425

0,014

7.67

Ancho de sépalo

0,201

0,012

0,070

0,002

5.97

Largo de la lígula

0,672

0,040

0,230

0,008

5.95

Ancho de la lígula

0,213

0,037

0,343

0,007

17.37

Largo del estaminoide

0,580

0,092

0,588

0,019

15.86

Largo del estilo

0,280

0,029

0,130

0,006

10.36

Largo del Ovario

0,208

0,009

0,045

0,002

4.33

Ancho del Ovario

0,185

0,022

0,214

0,004

11.89

Forma de la lígula

3,192

0,542

3,901

0,109

0.02

Largo del pedúnculo

2,013

0,342

4,116

0,069

0.02

 Fuente: Alvarado B. Arturo, 2015.=

 

Los valores de estas variables florales fueron sometidos a un anális= is de regresión donde se tomó como variable de referencia o variable independi= ente el largo del sépalo (y). Las significaciones estadísticas de estos coeficie= ntes de regresión aparecen en la Tabla 17, siendo significativos: ancho de sépalo, largo del ovario, forma de la lígula y lar= go del pedúnculo.

 

Y (largo/sépalo)=3D I+x1+x2+x3+……….+x9

 

Donde:

 

Y  =3D  Largo del sépalo

I   = =3D  Intersección

X1=3D  Anch= o del sépalo <= /o:p>

X2=3D  Larg= o de la lígula 

X3=3D  Anch= o de la lígula=

X4=3D  Largo= del estaminoide

X5=3D  Larg= o del estilo

X6=3D  Larg= o del ovario <= /o:p>

X7=3D  Anch= o del ovario <= /o:p>

X8=3D  Form= a de la lígula

X9=3D  Larg= o del pedúnculo

 

Y(largo/sépalo)=3D0.289+1.090x1-0.021x2+= 0.136x3-0.146x4+0.125x5+1.386x6= +0.334x7+0.056x8-0.063x9=

 

Tabla 17=

Variab= les relacionadas con en el Largo del Sépalo

VARIABLES

COEFICIENTE

PROBABILIDAD

Intercepción

0,289

0,128

Ancho de sépalo

1,091

0,017*

Largo de la lígula

-0,021

0,891

Ancho de la lígula

0,136

0,391

Largo del estaminoide

-0,146

0,091

Largo del estilo

0,125

0,498

Largo del Ovario

1,386

0,030*

Ancho del Ovario

0,334

0,174

Forma de la lígula

0,056

0,001*

Largo del pedúnculo

-0,063

7,4E-05*

Datos de probabili= dad y significancia al 0.05

Fuente: Alvarado B. Artur= o, 2015.

 

Variables de acuerdo con el Tipo de Varie= dades o Razas de Cacao.

Los valores medidos u observados de variables en plantas de acuerdo con su variedad muestran los siguientes resultados.

 

La variable número de semillas por fruto es muy similar entre las 4 variedades presentes en el cantón Naranjal siendo el promedio más alto el perteneciente al cacao tipo forastero con un valor de 34.46 semillas por fruto sobre el resto de las variedades ( REF _Ref121684604 \h Tabla = 18).

 =

Tabla 18

Resultados de la Comparación de Medias para el Número de Semillas por Frutos por Variedades

 

N= °

V= ARIEDADES

P= ROMEDIOS

S= ignificancia

1

Forastero

34,46

a

2

Trinitario

32,00

a

3

Nacional

31,68

a

4

Criollo=

30,27

a

 <= /span>

P. GENERAL

32,10

 <= /span>

 <= /span>

C. V.

20,06

 <= /span>

Medias con una letra común = no son significativamente diferentes (p > 0,05)

F= uente: Alvarado B. Arturo, 2015.<= o:p>

 

La Tabla = 19 muestra que la forma predominante de los tipos forastero y trinitario es cundeamor con expresión intermedia entre cundeamo= r y angoleta en los tipos criollo y nacional.<= /span>

 

 

 

Tabla 19

Result= ados de la Comparación de Medias para Forma del Fruto por Variedades<= /span>

N= °

V= ARIEDADES

P= ROMEDIOS

S= ignificancia

1

Forastero

2,38

a

2

Trinitario

2,00

a

3

Nacional

1,74

a

4

Criollo=

1,68

a

 <= /span>

P. GENERAL

1.95

 <= /span>

 <= /span>

C. V.

47,18

 <= /span>

Medias con una letra común no son significativamente diferentes (p > 0,05)=

Fuente: Alvarado B. Arturo, 2015.

 

El color del fruto, según la escala nominal empleada mostró un coeficiente de variación muy elevado (57.27%). La variedad forastera obtuvo una coloración entre anaranjado y morado, el naci= onal mostró coloración entre rojo y anaranjado, mientras que el trinitario prese= ntó coloración rojiza, así mismo el criollo es el que muestra coloración amaril= la (Tabla 20).

 

Tabla 20

Result= ados de la Comparación de Medias para el color del Fruto por Variedades

VARIEDADES<= /o:p>

PROMEDIOS

S= ignificancia

1

Forastero

3,77

a

2

Nacional

2,32

b

3

Trinitario

2,00

bc

4

Criollo

1,14

c

 

P. GENERAL

2.31

 

 

C. V.

57,27

 

Medias con una letra común no son significativamente diferentes (p > 0,05)

Fuente<= span style=3D'mso-bookmark:_Toc38966068'>: Alvarado B. Arturo, 2015.

 

La Tabla = 21 referente a la varia= ble rugosidad del fruto del fruto, de acuerdo con la escala nominal empleada, muestra que la variedad forastera tiene un fenotipo con pericarpio liso, po= r su parte el tipo trinitario ofrece una textura entre semi= -rugoso y liso, la variedad nacional con rugosidad también entre semi-rugoso y liso, mientras tanto el de tipo criollo muestra pericarpio rugoso.

 

Tabla 21

Result= ados de la Comparación de Medias para la textura del Fruto por Variedades=

VARIEDADES<= /o:p>

PROMEDIOS

S= ignificancia

1

Forastero

3,00

a

2

Trinitario

2,50

b

3

Nacional

2,32

b

4

Criollo

1,05

c

 

P. GENERAL

2.22

 

 

C. V.

20,27

 

Medias con una letra común no son significativamente diferentes (p > 0,05)<= /span>

Fuente: Alvarado B. Arturo, 2015.

 

De acuerdo con la <= /span>Tabla 22 referente a la constricción basal, los datos ofrecidos por la escala aplicada indica que l= as variedades tipo trinitario, forastero y nacional presentan una constricción basal entre escasa e intermedia, y la del tipo criollo de una constricción basal entre ausente y escasa.

 

Tabla 22

Result= ados de la Comparación de Medias para la Constricción Basal Fruto por Variedades=

VARIEDADES<= /o:p>

PROMEDIOS

S= ignificancia

1

Trinitario

2,50

a

2

Forastero

2,46

a

3

Nacional

2,37

a

4

Criollo

1,76

b

 

P. GENERAL

2.27

 

 

C. V.

24,08

 

Medias con una letra común no son significativamente diferentes (p > 0,05)<= /span>

Fuente: Alvarado B. Arturo, 2015.

 

En la Tabla = 23 se muestran resultad= os relativos a la forma del ápice, indicando forma obtusa en las variedades de tipo criollo, nacional, trinitario y aguda en el caso del forastero. <= /o:p>

 

Tabla 23

Resultados de la Comparación de Medias para la Forma del Ápice en las diferentes variedades

 

VARIEDADES<= /o:p>

PROMEDIOS

S= ignificancia

1

Criollo

3,05

a

2

Nacional

2,95

a

3

Trinitario

2,75

a

4

Forastero

2,46

a

 

P. GENERAL

2.80

 

 

C. V.

38,41

 

Medias con una letra común no son significativamente diferentes (p > 0,05)<= /span>

Fuente: Alvarado B. Arturo, 2015

 

Los promedios para largo del fruto se presentan en la  REF _Ref121686128 \h Tabla 24, no muestran diferen= cias significativas entre las 4 variedades, siendo el promedio más alto el de la variedad de tipo criollo con un valor de 17.69 (cm). Sobre el resto de variedades.

 

Tabla 24

Valores Promedio del largo del fruto por variedades

VARIEDADES<= /o:p>

PROMEDIOS

SIGNIFICANCIA

1

Criollo

17,69

a

2

Forastero

16,38

a

3

Trinitario

16,25

a

4

Nacional

15,93

a

 

P. GENERAL

17.10

 

 

C. V.

16,63

 

Medias con una letra común no son significativamente diferentes (p > 0,05)

Fuente:= Alvarado B. Arturo, 2015

 

Los promedios del ancho del fruto aparecen en la Tabla 25, sin diferencias significativas entre las variedades, logrando el promedio mayor la variedad= de tipo trinitario con 8.59cm.

 

 

Tabla 25

Valores Promedio de Ancho del Fruto por variedades

VARIEDADES<= /o:p>

PROMEDIOS

SIGNIFICANCIA

1

Trinitario

8,99

a

2

Criollo

8,59

a

3

Forastero

8,52

a

4

Nacional

8,47

a

 

P. GENERAL

8.64

 

 

C. V.

10,89

 

Medias con una letra común no son significativamente diferentes (p > 0,05)<= /span>

Fuente: Alvarado B. Arturo, 2015

&= nbsp;

Discus= ión

Peña (= 2003) indica que para realizar una caracterización morfológica no se deben tomar = en cuenta las características físicas del árbol en si como las antes mencionad= as ya que pueden existir diferencias en esta variable de acuerdo con la zona y manejo del cultivo, índice de sombreamiento, et= c. En este estudio los coeficientes de variación fueron variables, por ejemplo, resultaron del 10,89% para el ancho de semillas; y 20,26% para el número de semillas/fruto en variables no codificadas a escala; de 20,27% en la rugosi= dad del fruto; y 57,21% variables codificadas mediante escalas utilizadas de fo= rma arbitraria.

 

Pesant= es (2014), indicó que al caracterizar cacao de tipo nacional en la Estación Experimental Litoral Sur del INIAP, los valores para el coeficiente de variación resultaron de 6.30% para el largo de semillas y 26.28% para el pe= so total de semillas por fruto, otros autores señalan valores entre 9.22% y 33.85%. Pesantes (2014) señaló que las variables más importantes para reali= zar un trabajo de caracterización en frutos son el peso del fruto y el número de semillas por fruto teniendo como promedios del peso del fruto 611.97 y la m= edia para número de semillas por futo 32.69, valores que se asemejan al presente trabajo de investigación.

 <= /o:p>

Conclusiones

Las variedades encontradas entre las fincas evaluadas = son la variedad de tipo forastero con un 13.68%, criollo con un 62.11%, nacional c= on un 20% y trinitario con un 4.21%.

 

Los caracteres de mayor importancia para la caracteriz= ación se encuentran en el fruto entre los cuales se tienen en cuenta la forma del fruto, coloración del fruto forma del ápice, constricción basal, rugosidad = del fruto, peso del fruto, largo del fruto, ancho del fruto, número de semillas= por fruto, peso de lascara. Mientras que en la flor se tiene como característic= as importantes el largo del estilo, largo del sépalo, largo de la lígula, largo del ovario, ancho del ovario, y numero de óvulos por ovario lo cual tiene relación con el número de semillas por fruto.

 

En este trabajo de caracterización no se ha tomado en = cuenta el aspecto fisiológico, físico y molecular de las plantaciones de cacao, lo cual podría generar información específica para producir nuevos materiales genéticos.

 

Referencias

Águila L, Alfonso M., Jimen= ez C. y Mesías M., 2012. Caracterización morfológica y sensorial del cacao nacional (teobroma cacao) a nivel de fincas en el cantón las naves, provinc= ia bolívar. Tesis De Grado. Repositorio Universidad Estatal de Bolivar. Enlace del recurso http://dspace.ueb.edu.ec/handle/123456789/1031. Rights openAccess

Arguello M., 2001. Tipos de Cacao. Tesis, Agroedit, Cuenca.

Ayestas, E., et al. 2013. Caracterización de árb= oles promisorios de cacao en fincas orgánicas de Waslala, Nicaragua. Agroforesteria en las Americas: 1-8.

Bartley B.G= .D., 2000. An Explanation of the Meaning of the Term and its relationship to the= lntroductions from Ecuador. B.G.D.

Braudeau, J. 2000. «El cacao. Colección Agricultura Trop= ical.» Barcelona ES. (Editorial Blume.): 304 p.

Dejean, M. (1984). Floración del cacao. Boletín inform= ativo del Cacao, San José, CR, 1(3), 1-3.

End MJ, Day= mond AJ, Hadley P, editors. 2010. Technical guidelines for the safe movement of cacao germplasm (Revised from the FAO/IPGRI Technical Guidelines No. 20). Global Cacao Genetic Resources Network (CacaoNet), Bioversity International, Montpellier, France. ISBN 978-92-9043-871-7

Enríquez, G., 2004. Cacao orgánico: Guía para productores ecuatorianos. Instituto Nacional de Investigaciones Agropecuari= as, Quito: Quito Ediciones, segunda edición, 360p.

Enríquez, G., & Soria, V. (1967). Selección y estudio de los caracteres útiles de la flor para la identificación y descripción de cultivares de cacao. Cacao, (Costa rica) 12(1): 8-16.

Franco, T. L. e Hidalgo, R. (eds.). 2003. Anális= is Estadístico de Datos de Caracterización Morfológica de Recursos Fitogenétic= os. Boletín técnico no. 8, Instituto Internacional de Recursos Fitogenéticos (IPGRI), Cali, Colombia. 89 p.

MAG/IICA. 2001. Identificación de mercados y tecnología para productos agrícolas tradicionales de exportación. Quito, Ecuador. 45 p.

Mosquera, B. 2015. Importancia económica del cac= ao orgánico (Theobroma cacao) en el Ecuador. Tesis de pregrado. Universidad de Babahoyo. http://dspace.utb.edu.ec/bitstream/handle/49000/9226/E-UTB-FACIAG= -ING%20AGRON-000302.pdf?sequence=3D1&isAllowed=3Dy

Motomayor J.C., Risterucci A.M., López P.A., Ortiz C.F., Moreno A.Lanaud C. 2002. Cacao domestication I: The origin of the cacao cultivated by the Mayas. Heredity 89, 380–386.

Municipalidad de Naranjal, 2010. Estadísticas Agropecuarias. Naranjal. Guayas, Ecuador.

Ostendorf, F. W. (1965). Identifying characters f= or cacao clones crop. Reuniao do Comite Técnico Interamericano do Cacau, VI Salvador, Bahía, Br= asil, 89-110.

Peña Monserrate, G.R. (2003). Caracterización morfológica de 57 accesiones de cacao (Theobroma cacao L.) tipo nacional del banco de germoplasma de la Estación Experimental Tropical Pichilingue. (Tes= is de Ingeniería). Universidad Técnica de Manabí, Facultad de Ingeniería Agronómica, Escuela de Agronomía, = Manabí,.Ecuador.

Pérez, A. 1996. Variedades de Cacao y sus Características. Cali, Colombia: Ed. Lucas.

Pesantez, A. 2014. Caracterización morfológica y= de rendimiento    de 26 clones de caca= o (theobroma cacao l.) considerando características de 6= genotipos identificados en la zona de Yaguachi provincia del Guayas.2014tesis de ingeniero agrónomo. Guayaquil. Tesis de pregrado Repositorio Universidad Agraria del Ecuador. https://cia.uagraria.edu.ec/index.php

Pound, F. (1933) Criterios y Métodos de Selección en = Cacao. Segundo Informe Anual de Investigaciones sobre Cacao, 27-29.

Quiróz J.G. 1997. Recolección de Genotipos y Estableci= miento de un Banco de Germoplasma de Cacao Nacional. Estación Experimental Tropica= l PichilingueINIAP Boletín Técnico 75.

Quiroz, J. 2009. La producción de cacao, program= a de capacitación a facilitadores y agricultores en la cadena de cacao. Quito Ecuador: Consorcio Camaren.

Romero C, et al 2010. Identificación varietal de plantas de cacao. Tecnológica ESPOL, 2: 5.=

Williams, J= .T.; Damania, A.B. 1981. IPGRI. (International Plant Genet= ic Resources Institute), Industrial Crops: Cacao, Coconut, Pepper, Sugarcane a= nd Tea. 50 p.

 =

Anexos

Anexo 1: Ubicación de las fincas productoras de cacao del canton Naranjal

Fuente: Google earth

 =

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An actor-network perspective on Bitcoin sp= litsTechnological Forecasting & Social Change<= /b:JournalName>201910Elsev= ier Inc.148doi.org/10.1016/j.tech= fore.2019.1197436Mor19JournalArticle{D4ECDB8= 4-D68A-4A11-8DCE-A97B0CBACD82}Virtual Currencies in Moder= n Societies: Challenges and Opportunities2019MoraHigini= oPujol LópezFranc= iscoA.Mendoza T= elloJulioCésar= MoralesMarioR.Politics= and Technology in the Post-Truth Era171-185doi:10.1108/978-1-78756-983-6201910127Ruo19JournalArticl= e{7133703A-698D-4E64-BA75-23B2EB9D53CD}RuozhouLiu<= /b:First>ShanfengWanZilibZhangXuejunZhaoIs the introduction of futures res= ponsible for the crash of Bitcoin?Finance Research= Letters20197Elsevier Inc.doi.org/10.1016/j.frl.2019.08.0079Duc18JournalArticle{D8C4AD1E-00DD-4174-AD12-A7E5= EEA7A216}Duchenn= eJamesBlockchain and Smart Contracts: Complementing Climate Finance= , Legislative Frameworks, and Renewable Energy ProjectsTransforming Climate Finance and Green Investment with Blockchains2018303-317Els= evier Inc.https://doi.org/10.1016/B978-0-12-814447-3.0= 0022-741Tah18<= /b:Tag>JournalArticle{3626D445-20F2-4F= 35-BEEC-B80D29A3B047}Tahar HammiMohamedHammiBadisBel= lotPatrickSerhrouc= hniAhmedBubbles of Trust: A descentralized blockchain-based authent= ication system for IoTComputers & Security2018126-142Esl= evier Inc.78doi.org/10.1016/j.cos= e.2018.06.00412You19JournalArticle{1F0820C8-= DFC1-40A5-B454-C588C1DDB847}Young LeeJeiA decentralized token economy: How blockcha= in and cryptocurrency can revolutionize businessKe= lley School of Business, Indiana University2019773-784Elsevier Inc.62doi.org/10.1016/j.bushor.2019.08.00316Che17JournalArticle{9969D752-C425-4279-A234-F602F63434F= C}On Security Analysis of Proof-of-Elapsed-Time (PoET)2017282-297<= b:NameList>ChenLin= XuLeiShahNolanGao<= /b:Last>ZhiminLuYangShiWeid= ong10.1007/9= 78-3-319-69084-1_1943= Dis20InternetSite{251DF= 0DA-4770-4DD0-BA17-6EB1830F9E3F}DistrictOx Education Port= alhttps://education.district0x.io/general-topics/ethereum-= scaling/what-is-casper/DistrictOx = Education Portal2020enero1144But19JournalArticle{E15C7771-D498-4A90= -A732-5C47E4987A9F}ButerinVitalikG= riffithVirgilCasper the Friendly Finality Gadget2= 019arXiv:1710.09437v445Din18JournalArticle{744F9D50-6CAF-44A7-97F1-2DB5DFBFCC09}Untan= gling Blockchain: A Data Processing View of Blockchain Systems2018julio01DinhTienTuan AnhLiuR= uiZhangMeihuiChenGangChinBengIEEE Transactions on Knowledg= e and Data Engineering1366-1385307doi: 10.1109/TKDE.2017.278122732Gil17JournalArticle{3B9471CB-074C-448D-A287-6E= E6D2DA8E21}Algorand: Scaling byzantine agreements for cry= ptocurrencies.2017GiladYossiHemoRotemMicaliSilvioVla= chosGeorgiosZeldov= ichNickolai<= /b:Author>In Proceedings of the 26th Symposium on Operating = Systems52-68ACMdoi.org/10.1145/3132747.313275746= Alg19InternetSite{219F6B12-84E7-4D62-B3B0-D594D2B24FBE}Algo= rand2019Algoran= dhttps://www.algorand.com/what-w= e-do/technology/algorand-protocol2020enero1247Han18JournalArticle{2B1AAB3D-42D4-4EC8-924B-167E5= C5A668A}Dfinity technology overview series, consensus sys= tem2018arXiv:1805.04548v1 HankeTimoMovahediMahnushWilliamDominic48Dan16JournalArticle{5D9F8FF9-546A-4B66-838D-1E2AEA955BD1}DanezisGeorgeMeiklejohnSarahCentrally Banked Crypt= ocurrencies2016dx.doi.org/10.14722/ndss.2= 016.2318749Luu= 16JournalArticle{C6662B04-D002= -4B97-B745-9552B7430001}= LuuLoiNara= yananVisweshZheng<= /b:Last>ChaodongBawejaKunalGilbertSethSaxenaP= rateekA se= cure sharding protocol for open blockchainsIn Proc= eedings of the 2016 ACM SIGSAC Conference on Computer and Communications Se= curity201617-30ACMdx.doi.org/10.1145/2976749.297838950Zam18JournalArticle{5C16A509-11FE-42EF-AC64-72C01E4850= 8F}ZamaniMahdiMovahediMahnushRaykovaMarianaR= apidChain: Scaling Blockchain via Full ShardingIn = Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communication= s 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6

Carlos Amador Sacoto, Arturo Alvarado Barzallo, Simón Farah Asang, Juan = Javier Martillo

5

Caracterización morfológi= ca del cacao nacional “Theobroma cacao L.” del cantón Naranjal, Ecuador

 

Escuela Superior Politécn= ica del Litoral, ESPOL

 

Revista Tecnológica Espol= – RTE Vol. 34, N° 4 (Diciembre, 2022) / e-ISSN 1390-3659