Abstract The algarrobo blanco tree (Prosopis alba ), a tree species used in afforestation in semi-arid zones in Argentina, requires greater knowledge of its growth phases in the nursery to adjust irrigation, fertilization, and plant production time programs, in order to produce quality plants that ensure better responses in the field. For this, in this study, different durations in the hardening phase and their influence on the morphological attributes of quality in Prosopis alba Griseb plants were evaluated. The recorded variables were diameter at neck height (DAC), total height (Ht), root dry weight (PSR) and aerial dry weight (PSA); and the morphological indices: Dickson's index (ICD), aerial and root dry weight ratio (PSA/PSR) and slenderness index (IE). To determine the effects of the treatments tested, longitudinal measurements were made on the DAC and Ht evaluated by repeated means analysis of the mixed linear model’s module. The other parameters were evaluated by analysis of variance in the measurement 105 days after sowing. The results indicated that the treatment with duration of 60 days in the hardening phase presented the morphological parameters with the best quality. It is concluded that a longer duration in the hardening phase generated better morphological attributes, mainly 60% to 140% more root biomass and in the ICD a value 90% to 140% higher with respect to the other treatments.

Resumen El algarrobo blanco (Prosopis alba), especie arbórea utilizada en forestaciones en zonas semiáridas en Argentina, requiere de un mayor conocimiento de sus fases de crecimiento en vivero para ajustar programas de riego, fertilización y época de producción de plantas, con el fin de producir plantas de calidad que aseguren mejores respuestas en campo. Para ello, en este estudio se evaluaron diferentes duraciones en la fase de endurecimiento y su influencia sobre los atributos morfológicos de calidad en plantas de Prosopis alba Griseb. Las variables registradas fueron: diámetro a la altura de cuello (DAC), altura total (Ht), peso seco radical (PSR) y aéreo (PSA); y los índices morfológicos: índice de Dickson (ICD), relación entre peso seco aéreo y radical (PSA/PSR) e índice de esbeltez (IE). Para determinar los efectos de los tratamientos ensayados, se efectuaron mediciones longitudinales en las variables DAC y Ht evaluadas mediante análisis de medias repetidas del módulo de modelos lineales mixtos. Los demás parámetros fueron evaluados mediante análisis de varianza en la medición a los 105 días de la siembra. Los resultados indicaron que el tratamiento con una duración de 60 días en la fase de endurecimiento presentó los mejores parámetros morfológicos de calidad. Se concluye que una mayor duración en la fase de endurecimiento generó mejores atributos morfológicos, principalmente 60% a 140% más de biomasa radicular y en el ICD un valor 90% a 140% más alto con respecto a los demás tratamientos.

ABSTRACT The classification of sites through curves of Site Index allows to predict the yield of the planted forests at a certain age of the stand and to plan cultural treatments. The goal of this research was to compare linear and non-linear models of fixed effects vs. mixed non-linear models to estimate the site index in plantations of Prosopis alba var Griseb in the irrigated area of the province of Santiago del Estero, Argentina using the guide curve method. The data used comes from temporary plots, permanent plots and growth data from the stem analysis of selected individuals based on their greater growth in height within the sampled areas. The registered variable for the evaluation of the site was the dominant Height (HD), defined as the average height of the 100 thickest trees per hectare. Considering that the source of data from repeated measurements on the same subject implies the presence of correlation and/or heteroscedasticity, it was proposed to evaluate statistical models that allow to properly representing the structure of the variance-covariance matrix, improving the accuracy in the adjustment. From the analysis of the results, it appears that the models non-linear mixed models have had better performance in the adjustment of the Site Index than linear and non-linear models of fixed effects. The most accurate model (smallest AIC and BIC) in the site index estimation was the mixed non-linear regression model of “Gompertz”, with structure of composite symmetry correlation and exponential heteroscedasticity.