Validation of submaximal prediction equations for the 1 repetition maximum bench press test on a group of collegiate football players

The purpose of the study was to determine the accuracy of 11 prediction equations in estimating the 1 repetition maximum (1RM) bench press from repetitions completed by collegiate football players (N = 69) using 225 lb. The demographic variables race, age, height, weight, fat-free weight, and percent body fat were measured to determine whether these variables increased the accuracy of the prediction equations; race was the most frequently selected variable in the regression analyses. The validity of the prediction equations was dependent upon the number of repetitions performed, i.e., validity was higher when fewer repetitions were completed. Explained variability of 1RM was slightly higher for all 11 equations when demographic variables were included. A new prediction equation was also developed using the number of repetitions performed and the demographic variables height and fat-free weight

Validation of Submaximal Prediction Equations for the 1 Repetition Maximum Bench Press Test on a Group of Collegiate Football Players

The purpose of the study was to determine the accuracy of 11 prediction equations in estimating the 1 repetition maximum (1RM) bench press from repetitions completed by collegiate football players (N = 69) using 225 lb. The demographic variables race, age, height, weight, fat-free weight, and percent body fat were measured to determine whether these variables increased the accuracy of the prediction equations; race was the most frequently selected variable in the regression analyses. The validity of the prediction equations was dependent upon the number of repetitions performed, i.e., validity was higher when fewer repetitions were completed. Explained variability of 1RM was slightly higher for all 11 equations when demographic variables were included. A new prediction equation was also developed using the number of repetitions performed and the demographic variables height and fat-free weight

Exploitation of Rhizosphere Microbiome Services

The rhizosphere is a soil hot spot where, due to a tight plant-bacteria interaction, plants recruit a beneficial microbiome, enhancing its density and activity. Rhizosphere microbial communities have the potential to provide several services, and their management and \u201cengineering\u201d can be exploited to set up agro-environmental biotechnologies. In this chapter, after a brief overview of the array of services that we can obtain from rhizosphere beneficial microbiome, two case studies are presented: i) the exploitation of plant growth promoting bacteria to increase plant tolerance to drought, potentially able to improve crop plants yields in arid and semi-arid lands, ii) the exploitation of plant biostimulation effect over degrading microbial populations in the rhizosphere, sustaining phyto-rhyzo-remediation approaches in PCB contaminated soils. In each case study the experimental settings, the in vitro and in vivo tests, the result evaluation and modelling are reported, together with a discussion of the critical issues