Precision of Growth Estimates and Sufficient Sample Size: Can Solar Radiation Level Change These Factors?

Solar radiation levels (SRL) in suboptimal or super-optimal levels modify biomass accumulation. Moreover, sample size might modify the precision of growth estimators; however, little is known about the joint effects of these factors on the precision of growth estimators in nonlinear models. The aim of this study was to determine whether SRL and sample size could change the precision of the growth models. To this, three SRL (100, 70 and 50% of available solar radiation) were established in escarole (Cichorium endivia L. var. latifolia). In each SRL, the Schumacher's nonlinear model was fitted in 100 sample sizes to investigate if the increase in sample size and reduction of SRL could reduce the errors of estimates. Reduced SRL (70 and 50%) improved the precision of the model. The sufficient sample size for estimating growth parameters with lesser error increased when SLR was higher; however, 264 plants were sufficient to estimate growth parameters with best fits to this crop. We proved the increase in sample size jointly with the attenuation of solar radiation are effective methods to providing growth estimates with a lesser error. The method for estimating the sufficient sample size proposed here might be extended for several studies where nonlinear models are used to obtain growth estimates. By using these simple methods, both researchers and farmers might have a competitive advantage in planning their experiments or cropping systems, mainly in sites or seasons where light-sensitive crops need to be cultivated.