Jameel M. Al-Khayri^1,*, Salha M. Alshamrani², Adel A. Rezk¹, Wael F. Shehata¹, Mustafa I. Almaghasla³, Tarek A. Shalaby^3,4, Ahmed M. Saad⁵, Fatmah A. Safhi⁶, Muhammad N. Sattar⁷, Arafat A. Abdel Latef⁸, Mahmoud Z. Sitohy⁵, Abdallah A. Hassanin^9,*

Phyton-International Journal of Experimental Botany, Vol.92, No.5, pp. 1493-1512, 2023, DOI:10.32604/phyton.2023.027375

Abstract Appropriate knowledge of the parental cultivars is a pre-requisite for a successful breeding program. This study characterized fruit yield, quality attributes, and molecular variations of ten tomato cultivars during three consecutive generations under greenhouse conditions. Peto 86, Castle Rock, and Red Star cultivars showed the highest fruit yield (kg/plant), total phenolic compounds (TPC), and sap acidity. Principal component analysis categorized the evaluated fruit yield into three groups based on their quality attributes. A robust positive correlation appeared among traits inside each group. A positive correlation was likewise noticed between the first and the second groups. However, a negative correlation was… More >

Liming Yang¹, Yongping Gao², Qun Sun³

CMES-Computer Modeling in Engineering & Sciences, Vol.104, No.6, pp. 493-506, 2015, DOI:10.3970/cmes.2015.104.493

Abstract Minimax probability machine (MPM) has been recently proposed and shown its advantage in pattern recognition. In this paper, we present a new minimax probabilistic approach (MPA),which can provide an explicit lower bound on prediction accuracy. Applying the Chebyshev-Cantelli inequality, the MPA is posed as a second order cone program formulation and solved effectively. Following that, this method is exploited directly to recognize the purity of hybrid seeds using near-infrared spectroscopic data. Experimental results in different spectral regions show that the proposed MPA is competitive with the existing minimax probability machine and support vector machine in generalization, while requires less computational… More >