It can be seen from Figure 2B that each fig leaf extract had the ability of scavenging ABTS free radicals, which was similar to that of DPPH free radicals. The changing trend of sample scavenging ability was the same as that of sample concentration. The ethyl acetate extract had the stronges...
The accumulated metabolites of figs before and after the entry of pollinators were compared with the KEGG database, leading to the identification of 215 KEGG pathways. The top twenty metabolic pathways are presented based on the screening criteria ofp-value < 0.05. Notably, the enriched metabolic...
Identification of panicle and leaf blast resistance genes in Jiangnanwan by QTL mapping method.doi:10.1371/journal.pone.0169417.g004Wang RuisenFang NengyanGuan ChanghongHe Wan-wanBao YongmeiZhang HongshengPLOS ONE
IFOA-GRNN algorithm flow chart. Step 1. Randomly initialize the position of the fruit fly InitX_axis, InitY_axis. (10) Step 2. Calculate the distance from the origin of the fruit fly Di and the judgment value Si of taste concentration, which is the spreading parameter σ in the GRNN ...
Dietrich (INHS, Champaign, IL) for confirming identification of Auchenorrhyncha species (except Delphacidae). This research was made possible by a grant to LMHB via the Coastal Waters Consortium from The Gulf of Mexico Research Initiative. Data are publicly available through the Gulf of Mexico ...
Identification of insect-host plant associations using DNA extracted from rolled-leaf beetle gut contents.Carlos, GarcíaRobledoDavid, L. EricksonCharles, L. StainesTerry, L. ErwinW., John Kress
PREPARATION AND IDENTIFICATION OF FE (III) NANOOXIDE USING FIG LEAF (FICUS LYRATA) EXTRACT AND STUDY OF ITS EFFECT ON THE PHOTOSYNTHESIS OF POLY (VINYL ALCOHOL)Jiad, Sami AssafAli, Hameedd KhalidBiochemical & Cellular Archives
Identification accuracy with the additional color characteristics of leaf sheath.Lisu, ChenLin, LinGuangzhe, CaiYuanyuan, SunTao, HuangKe, WangJinsong, Deng
and this method can be used for both the continuous and categorical variables. We found that the C4.5 classifier achieved the highest accuracy among these methods for the land cover identification. The classifier was developed on the basis of the decision tree learning, which is a heuristic, one...
The maximum depth of the tree is 5; the number of iterations is 250; the weight sum of the minimum leaf nodes is 5; the random sampling proportion is 0.7; in the selection of the maximum height of the tree, because the height of the tree is too small, the model is too simple, ...