Depth, Weight, and Volume of Tomato Roots (Solanum lycopersicon) cv. Piedro in Greenhouse Conditions

This research was done to determine the distribution of the root system of tomatoes as a way to perform more accurate agrotechnical conditions. It was conducted in San Pedro Pinampiro Canton, province of Imbadura, Ecuador, between July 10, 2015, and the second fortnight of January 2016. Monoliths were used to determine root distribution, considering the diameter, length, mass, and volume of roots between 0.10 and 0.40 m. The largest root volume was found in the 0-10 m deep profile

Depth, Weight, and Volume of Tomato Roots (Solanum lycopersicon) cv. Piedro in Greenhouse Conditions

This research was done to determine the distribution of the root system of tomatoes as a way to perform more accurate agrotechnical conditions. It was conducted in San Pedro Pinampiro Canton, province of Imbadura, Ecuador, between July 10, 2015, and the second fortnight of January 2016. Monoliths were used to determine root distribution, considering the diameter, length, mass, and volume of roots between 0.10 and 0.40 m. The largest root volume was found in the 0-10 m deep profile

Profundidad, peso y volumen del sistema radical del tomate (Solanum lycopersicon) cv. Piedro en condiciones de invernadero

Con el objetivo de determinar la distribución del sistema radical del tomate, para que facilite con mayor exactitud las aplicaciones de las labores agrotécnicas. La investigación se desarrolló en el Cantón San Pedro de Pimampiro, provincia de Imbabura, Ecuador durante comprendido entre el 10 de julio del año 2015 y la segunda quincena de enero del 2016, utilizaron monolitos para evaluar la distribución de las raíces teniendo en cuenta el diámetro, longitud , masa y volumen de raíces entre 0,10 y 0,40 m. El mayor volumen de raíces se encuentra a la profundidad de 0-10 m

Growth Dynamic of Sugarcane Cultivars C97-366 and C99-374 for Forage Production

Context: Plant growth analysis is a valuable tool to detect biomass formation and accumulation. The determination of growth indexes enables plants to adapt to different edaphoclimatic conditions, and to select the most promising responses among them. Aim: To characterize the growth dynamic of sugarcane cultivars C97-366 and C99-374, with forage purposes. Methods: A randomized experimental block design with three replicas was used. The following growth indicators were evaluated: foliage surface, foliage surface index, crop growth rate, and net monthly assimilation rate, at 181 days (February) and 342 days (July), after planting. Correlation analyses were made to determine the best model fit for every indicator evaluated in the two cultivars, as well as the analysis of variance of regressions. Results: Cultivar C97-366 was fit to a linear model for the foliage surface index, crop growth rate, and net assimilation rate; the foliage surface was fit to a polynomial model. Cultivar C99-374 was fit to a polynomial model for the foliage surface index, crop growth rate, and net assimilation rate; the foliage surface index was fit to a linear model. Conclusions: Cultivars C97-366 and C99-374 showed genetic and morphological characteristics that lead to efficient physiological processes that determine proper biomass production

Dinámica del crecimiento en los cultivares de caña de azúcar C97-366 y C99-374, con fines forrajeros

Context: The analysis of plant growth, is a tool of great value to know the formation and accumulation of biomass. The determination of growth indexes makes it possible to identify plant adaptations to different soil and climate conditions, and within these responses select the most promising. Objective: In order to characterizing the growth dynamics in sugarcane cultivars C97-366 and C99-374, for forage purposes. Methods: A random block design with three replicas was used. Growth indicators were evaluated: leaf area; leaf area index; crop growth rate and net assimilation rate on a monthly basis, from 181 days (February) to 342 days (July) after planting. Correlations were made to determine the best fit model for each of the indicators evaluated in the two cultivars, as well as analysis of variance of the regressions. Results: The cultivar C97-366 was adjusted to a linear model for the indicators leaf area index; crop growth rate and net assimilation rate; and for the leaf area to a polynomial model. The C99-374 was adjusted to a polynomial model for the growth indicators Foliar Area; Crop Growth Rate and Net assimilation rate and for the leaf area index to a linear model. Conclusions: The cultivars C97-366 and C99-374 possess genetic and morphological characteristics that allow performing in an efficient way the physiological processes that determine a good biomass production.Contexto: El análisis de crecimiento vegetal, es una herramienta de gran valor para conocer la formación y acumulación de biomasa. La determinación de índices de crecimiento posibilita identificar las adaptaciones en las plantas a diferentes condiciones edafoclimáticas, y dentro de estas respuestas seleccionar las más promisorias. Objetivo: Con el objetivo de caracterizar la dinámica del crecimiento en los cultivares de caña de azúcar C97-366 y C99-374, con fines forrajeros. Métodos: Se utilizó un diseño de bloques al azar con tres réplicas. Se evaluaron los indicadores de crecimiento: área foliar; índice de área foliar; tasa de crecimiento del cultivo y tasa de asimilación neta de forma mensual, desde los 181 días (febrero) y hasta los 342 días (julio) posteriores a la plantación. Se realizaron correlaciones para determinar el modelo de mejor ajuste para cada uno de los indicadores evaluados en los dos cultivares, así como análisis de varianza de las regresiones. Resultados: El cultivar C97-366 se ajustó a un modelo lineal para los indicadores índice de área foliar; tasa de crecimiento del cultivo y tasa de asimilación neta y para el área foliar a un modelo polinomial. El C99-374 se ajustó a un modelo polinomial para los indicadores de crecimiento área foliar; tasa de crecimiento del cultivo y tasa de asimilación neta y para el índice de área foliar a un modelo lineal. Conclusiones: Los cultivares C97-366 y C99-374 poseen características genéticas y morfológicas que permiten realizar de una forma eficiente los procesos fisiológicos que determinan una buena producción de biomasa