Ferdowsi University of MashhadJournal Of Agroecology2008-771310320181222Effect of Fertilizer Type and Intercropping of Trigonella (Trigonella foenum-graecum) and Psyllium (Plantago psyllium) on Growth Index of Psyllium using Factor analysisEffect of Fertilizer Type and Intercropping of Trigonella (Trigonella foenum-graecum) and Psyllium (Plantago psyllium) on Growth Index of Psyllium using Factor analysis8058223660610.22067/jag.v10i3.60474FASoheilaGhasemi MahamShahrekord UniversitySeyfollahFallahShahrekord UniversityAmirDadrasiVali-e-asrJournal Article20161121Introduction
In the cultivation of medicinal plants, employing practices that can increase the essential materials is of necessary issues. Intercropping can improve the ecological diversity and stability in agro-ecosystems, increase the yield and reduce the use of chemical compounds. In addition, application of integrated fertilizers on agricultural soils may affect ecosystem sustainability, directly or indirectly, through changing the amount of chemical fertilizers application. Integrated fertilizers not only increase the yield, but also prevent environmental pollution. Accurate assessment of plant growth changes in various agricultural land management cannot be achieved by measuring an individual simple parameter. For this reason, simultaneous determination of several growth indicators can be a suitable method for monitoring the changes of plant growth in different conditions. The use of multivariate analysis is a beneficial approach in agronomic studies, since the method can easily assess the measured indices and more clearly interpret the results. Principal Components Analysis (PCA) or Factor Analysis (FA) are among of multivariate analysis methods in which reducing the number of primary studied variables is their initial aim. The purpose of this research was to evaluate the changes of psyllium growth indices in different fertilizer treatments and different combinations of intercropping using multivariate analysis and selection of the most sensitive growth indicator.
Materials and Methods
In order to evaluate the effects of different fertilizer types and intercropping ratios on the quantitative and qualitative yield of psyllium, the study was setup as 3×4 full factorial arrangement based on a randomized complete block design with three replications for each treatment over a period of 120 days. The treatments were intercropping ratio (monoculture of psyllium, trigonella: psyllium (2:1), fenugreek: psyllium (1:1), fenugreek: psyllium (1:2)) as the main plot factors and fertilizer types (cow manure, integrated fertilizer and chemical fertilizer) as the sub-plot factors. In intercropping treatments, the amount of fertilizer consumption corresponded to their intercropping ratio. Finally, 20 plants were randomly collected from each plot and were transferred to the laboratory. Data obtained from the study were analyzed using multivariate analysis (Factor Analysis, FA).
Results and Discussion
Extracted factors were rotated by Quartimax rotation to set most of the factor loadings on the first factor. Factor analysis led to the selection of four factors with eigenvalue greater than 1. The eigenvalue of fifth factor was 0.981, so it was not considered in the analysis and interpretation of data. The first, second, third and fourth factors were accounted for 31.1, 22, 18.3 and 8.3% of the variability of the data, respectively. These three factors explained 79.7% of the original variability, totally (i.e., variance). Consequently, four factors were retained to represent the original variability of the dataset. The first factor had 5 highly weighted variables with positive loadings for mucilage yield, the percentage of mucilage and inflation factor and negative loadings for other variables. The first factor, which included most of the qualitative and quantitative indicators as input variables, clearly separated fertilizer treatments. Number of branches, during spike and the weight of one thousand seeds loaded heavily on the second factor with a positive loading for all properties. The second factor noticeably discriminated intercropping treatments. The effect of fertilizer treatments depended extremely on intercropping ratio, due to positive interaction between fertilizer type and leguminous symbiosis. However, the positive impact of fertilizer treatments was only related to appropriate intercropping ratio (1:2), probably due to suitable space for psyllium growth.
Conclusion
Factor analysis was used successfully in discriminating the effects of fertilizer type and intercropping on psyllium growth indicators. As a result, psyllium qualitative and quantitative properties were positively affected by the first and second factors. The first and second factors were clearly affected by fertilizer type and intercropping ratio, respectively. Therefore, these factors can be used for improving psyllium growth and increasing its quality. Moreover, application of integrated fertilizer not only increase intercropping efficiency, but also reduce environmental pollution.Introduction
In the cultivation of medicinal plants, employing practices that can increase the essential materials is of necessary issues. Intercropping can improve the ecological diversity and stability in agro-ecosystems, increase the yield and reduce the use of chemical compounds. In addition, application of integrated fertilizers on agricultural soils may affect ecosystem sustainability, directly or indirectly, through changing the amount of chemical fertilizers application. Integrated fertilizers not only increase the yield, but also prevent environmental pollution. Accurate assessment of plant growth changes in various agricultural land management cannot be achieved by measuring an individual simple parameter. For this reason, simultaneous determination of several growth indicators can be a suitable method for monitoring the changes of plant growth in different conditions. The use of multivariate analysis is a beneficial approach in agronomic studies, since the method can easily assess the measured indices and more clearly interpret the results. Principal Components Analysis (PCA) or Factor Analysis (FA) are among of multivariate analysis methods in which reducing the number of primary studied variables is their initial aim. The purpose of this research was to evaluate the changes of psyllium growth indices in different fertilizer treatments and different combinations of intercropping using multivariate analysis and selection of the most sensitive growth indicator.
Materials and Methods
In order to evaluate the effects of different fertilizer types and intercropping ratios on the quantitative and qualitative yield of psyllium, the study was setup as 3×4 full factorial arrangement based on a randomized complete block design with three replications for each treatment over a period of 120 days. The treatments were intercropping ratio (monoculture of psyllium, trigonella: psyllium (2:1), fenugreek: psyllium (1:1), fenugreek: psyllium (1:2)) as the main plot factors and fertilizer types (cow manure, integrated fertilizer and chemical fertilizer) as the sub-plot factors. In intercropping treatments, the amount of fertilizer consumption corresponded to their intercropping ratio. Finally, 20 plants were randomly collected from each plot and were transferred to the laboratory. Data obtained from the study were analyzed using multivariate analysis (Factor Analysis, FA).
Results and Discussion
Extracted factors were rotated by Quartimax rotation to set most of the factor loadings on the first factor. Factor analysis led to the selection of four factors with eigenvalue greater than 1. The eigenvalue of fifth factor was 0.981, so it was not considered in the analysis and interpretation of data. The first, second, third and fourth factors were accounted for 31.1, 22, 18.3 and 8.3% of the variability of the data, respectively. These three factors explained 79.7% of the original variability, totally (i.e., variance). Consequently, four factors were retained to represent the original variability of the dataset. The first factor had 5 highly weighted variables with positive loadings for mucilage yield, the percentage of mucilage and inflation factor and negative loadings for other variables. The first factor, which included most of the qualitative and quantitative indicators as input variables, clearly separated fertilizer treatments. Number of branches, during spike and the weight of one thousand seeds loaded heavily on the second factor with a positive loading for all properties. The second factor noticeably discriminated intercropping treatments. The effect of fertilizer treatments depended extremely on intercropping ratio, due to positive interaction between fertilizer type and leguminous symbiosis. However, the positive impact of fertilizer treatments was only related to appropriate intercropping ratio (1:2), probably due to suitable space for psyllium growth.
Conclusion
Factor analysis was used successfully in discriminating the effects of fertilizer type and intercropping on psyllium growth indicators. As a result, psyllium qualitative and quantitative properties were positively affected by the first and second factors. The first and second factors were clearly affected by fertilizer type and intercropping ratio, respectively. Therefore, these factors can be used for improving psyllium growth and increasing its quality. Moreover, application of integrated fertilizer not only increase intercropping efficiency, but also reduce environmental pollution.https://agry.um.ac.ir/article_36606_d483632f6b9571b26717d4119a6e2d5c.pdf