Water and saline stresses are the main factors affecting agricultural production in semiarid regions. The tolerance of forage cactus to water and salt deficit makes it a promising solution, in particular Nopalea cochenillifera. The growth curves for species facing these conditions can provide useful information supporting the cultivation and management of natural populations and carry significant biological importance as growth rate assessment contributes to maintaining species viability. The objective of this study was to estimate the plant height and linear dimensions (length, width, and thickness) of N. cochenillifera Giant Sweet clone growing under water and saline stress. The experiment design was completely randomized, comprising a 4 × 4 factorial, with four water and four salinity levels; there were four replications. In order to estimate plant height in N. cochenillifera Giant Sweet clone as a function of the accumulated thermal sum, generalized additive models for location, scale, and shape (GAMLSS) were used to determine water level, saline level, length, width, and thickness. We constructed models using four distributions: the Weibull, Gumbel, Logistic, and Box-Cox power exponential distributions. The models were evaluated using global deviation and the generalized Akaike criterion. The Box–Cox power exponential proved to be the most effective in estimating N. cochenillifera height. This model enabled information relevant to practical environmental management to be obtained, as it precisely defined the optimum salt application and the required amount of replacement water, together with the cladode width for each plant growth stage using the accumulated thermal sum.
Determination of photosynthetic area of a plant, leaf or cladode is a fundamental tool in study of transpiration intensity, specific leaf area and leaf area index. The objective of this study was to evaluate Nopalea cochenillifera (L.) Salm-Dyck). cladode area, in a non- destructive way, using digital images and test its relation with the variables: product of length and maximum width and real cladode area through regression models. The design used randomized blocks with three replicates and using the N. cochenillifera forage cactus clone, Giant Sweet. To determine the real cladode area of cactus forage, 432 cladodes in different stages of growth were randomly collected (162 primary cladodes, 127 secondary and 143 tertiary cladodes), all free from damage, disease or pest attacks. All cladodes were photographed with a digital camera (Sony Mark, model DSC-P72) generating a sample of 432 1200 x 2500 pixel digital images of N. cochenillifera cladodes. Linear, gamma and power regression models were adjusted to test the relation between the digital cladode area and the explanatory variables real cladode area and product of length by width. Models were evaluated with the following criteria: Coefficient of model determination, Akaike information criterion, sum of squares of residuals and Willmott index. The power model gave the best performance, with explanatory power higher than 99.5%, while the Willmott index exceeded 0.99. Sum of squares of residuals and Akaike information criterion had lower values. The digital cladode area of N. cochenillifera can be explained by the linear dimensions of cladodes in, and independent of, branching order. The digital cladode area (DCA) of N. cochenillifera can be explained as a function of the power model -DCA = LW0.98Sconsidering the product of length by width (LW) with explanatory variable, and by D-CA = RCA1.002considering real cladode area (RCA) with explanatory variable.
Forage cacti can contribute to increases in biomass yields in agricultural areas, improving the use efficiency of local natural resources. Forage cactus stands out as a forage alternative in semi-arid regions due to its high potential of phytomass production and energy value, large water reserve and easy propagation. The objective of this study was discriminate as morphometric characteristics of Nopalea cochenillifera cladodes in relation to Little and Giant Sweet clones. This research was conducted from March 2016 to July 2019. The design used was randomized blocks with five replicates using the forage cactus clones Little and Giant Sweet of Nopalea cochenillifera (L.) Salm-Dyck. The experimental unit was an area of 126.0 m2 (12.6 x 10.0 m). Study sample is composed of 1018 cladodes (581 of Little Sweet clone) and (437 of Giant Sweet clone), randomly collected. Variables evaluated were the cladode length, width, thickness, area weight. T-tests, Pearson correlation coefficients, discriminant analysis and canonical variables analysis were used to evaluate, compare and discriminate the morphometric characteristics of forage cactus clones. The Giant Sweet clone presented the highest means for the variables length, width, area and weight. Fisher's discriminant function verified a 99.41% hit rate to differentiate groups of forage cactus clone. The hit rate for Little Sweet clone was of 98.97%, while for Giant Sweet clone was of 100.00%. With two canonical variables the explanation rate of the morphometric characteristics for the behavior of forage cactus clones is higher than 90%. Morphometric characteristics of cladodes can be used as parameters that help in the identification of Nopalea cochenillifera clones with high discriminatory power.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.