Efficiency of using indexes method in the comprehensive assessment of the genetic collection in the winter hexaploid triticale

The paper presents the comparative assessment results of 53 collection samples of winter hexaploid triticale of various ecological and geographical origin using traditional statistical methods and methods of complex indices (Jk), perspectivity indices (Jp), ecological plasticity (Jsp), Finno-Scandinavian (FSJ), Mexican (Mi), and adaptive potential. By the traditional statistical method, high-yield varieties with high values of individual elements of plant productivity were identified: (k-3717) Kaskad, (k-4071) Ramzay, (k-3969) Trizub, (k-3924) Popsuevskaya, (k-3900) Prometey, (k-4095) Shalanda, (k-4097) Buket. The following varieties were identified by the method of complex indices: (k-3909) Topaz, (k-3717) Kaskad, (k-3931) Skif, (k-4071) Ramzay, (k-3969) Trizub, (k-4074) Valentin-90, (k-4078) Bordo, (k-3924), Popsuevskaya, (k-3968) Interes, (k-3901) Mars, (k-3900) Prometey, (k-4003) Disko, (k-3999) Anvo, (k-3701) Fidelio, (k-4095) Shalanda, (k-4097) Buket. According to the indices’ complex that determine the prospects of the variety, the grain-forming ability of its ear, resistance to lodging, high adaptive potential, the following varieties were identified: (k-3909) Topaz, (k-3717) Kaskad, (k-4020) Zavet, (k-3932) Skolot, (k-4071) Ramzay, (k-4074) Valentin-90, (k-4076) Knyaz, (k-3924), Popsuevskaya, (k-3968) Interes, (k-3966) Ajax, (3965) Pshenichne, (k-3900) Prometey, (k-4003) Disko, (k-4005) Korvetta, (k-3999) Anvo, (k-3701) Fidelio, (k-4095) Shalanda, (k-4097) Buket, (k-3562) Antey, (k-3582) Patriot. The study results allow to speak about the usage efficiency of the indices method for a comprehensive winter triticale assessment.

ANN-Based Wheat Chlorophyll Density Estimation Using Canopy Hyperspectral Vegetation Indices

Canopy leaf Chlorophyll Density is a key index for evaluating crop potential photosynthetic efficiency and nutritional stress. Leaf Chlorophyll Density estimate using canopy hyperspectral vegetation indices provides a rapid and non-destructive method to evaluate yield predictions. A systematic comparison of two approaches to estimate Chlorophyll Density using 6 spectral vegetation indices (VIs) was presented in this study. In this study, the traditional statistical method based on power regression analyses was compared to the emerging computationally powerful techniques based on artificial neural network (ANN). The regression models of TCARI 、SAVI 、MSAVI and RDVIgreen were found to be more suitable for predicting Chlorophyll Density when only traditional statistical method was used especially TCARI and RDVI. ANN method was more appropriate to develop prediction models. The comparisons between these two methods were based on analysis of the statistic parameters. Results obtained using Root Mean Square Error (RMSE) for ANNs were significantly lower than the traditional method. From this analysis it is concluded that the neural network is more robust to train and estimate crop Chlorophyll Density from remote sensing data.

The analysis of fracture profiles of soil using fractal geometry

The fracture profiles of three soils (taken from Dexter and Horn 1988) are analysed according to their fractal dimensions D. D, which is a measure of how the 'apparent' length of a fracture path increases with decreasing ruler size, is found to be a good quantifier of the tortuousity of fracture paths. The fractal analysis is compared with a more traditional statistical method of analysing fracture profiles. It is shown that the latter method, unlike fractal analysis, can omit a significant proportion of a tortuous fracture path and therefore leads to an underestimate of any roughness parameter.