Search results for "YIELD"
showing 10 items of 1338 documents
"Table 35" of "Multiplicity dependence of K*(892)$^{0}$ and $\phi$(1020) production in pp collisions at $\sqrt{s}$ = 13 TeV"
2020
$\phi$ transverse momentum spectrum ratio to INEL>0 - V0M multiplicity class VII
"Table 37" of "Multiplicity dependence of K*(892)$^{0}$ and $\phi$(1020) production in pp collisions at $\sqrt{s}$ = 13 TeV"
2020
$\phi$ transverse momentum spectrum ratio to INEL>0 - V0M multiplicity class IX
"Table 34" of "Multiplicity dependence of K*(892)$^{0}$ and $\phi$(1020) production in pp collisions at $\sqrt{s}$ = 13 TeV"
2020
$\phi$ transverse momentum spectrum ratio to INEL>0 - V0M multiplicity class VI
"Table 33" of "Multiplicity dependence of K*(892)$^{0}$ and $\phi$(1020) production in pp collisions at $\sqrt{s}$ = 13 TeV"
2020
$\phi$ transverse momentum spectrum ratio to INEL>0 - V0M multiplicity class V
"Table 38" of "Multiplicity dependence of K*(892)$^{0}$ and $\phi$(1020) production in pp collisions at $\sqrt{s}$ = 13 TeV"
2020
$\phi$ transverse momentum spectrum ratio to INEL>0 - V0M multiplicity class X
"Table 31" of "Multiplicity dependence of K*(892)$^{0}$ and $\phi$(1020) production in pp collisions at $\sqrt{s}$ = 13 TeV"
2020
$\phi$ transverse momentum spectrum ratio to INEL>0 - V0M multiplicity class III
"Table 32" of "Multiplicity dependence of K*(892)$^{0}$ and $\phi$(1020) production in pp collisions at $\sqrt{s}$ = 13 TeV"
2020
$\phi$ transverse momentum spectrum ratio to INEL>0 - V0M multiplicity class IV
Use of Botanicals to Suppress Different Stages of the Life Cycle of Fusarium graminearum
2019
Fusarium head blight (FHB) is one of the most important cereal diseases worldwide, causing yield losses and contamination of harvested products with mycotoxins. Fusarium graminearum is one of the most common FHB-causing species in wheat and barley cropping systems. We assessed the ability of different botanical extracts to suppress essential stages of the fungal life cycle using three strains of F. graminearum (FG0410, FG2113, and FG1145). The botanicals included aqueous extracts from white mustard (Sinapis alba) seed flour (Pure Yellow Mustard [PYM] and Tillecur [Ti]) as well as milled Chinese galls (CG). At 2% concentration (wt/vol), PYM and Ti completely inhibited growth of mycelium of …
Fine-scale spatial genetic structure analysis of the black truffle T uber aestivum and its link to aroma variability
2015
Truffles are symbiotic fungi in high demand by food connoisseurs. Improving yield and product quality requires a better understanding of truffle genetics and aroma biosynthesis. One aim here was to investigate the diversity and fine-scale spatial genetic structure of the Burgundy truffle Tuber aestivum. The second aim was to assess how genetic structuring along with fruiting body maturation and geographical origin influenced single constituents of truffle aroma. A total of 39 Burgundy truffles collected in two orchards were characterized in terms of aroma profile (SPME-GC/MS) and genotype (microsatellites). A moderate genetic differentiation was observed between the populations of the two o…
2020
AbstractForecasting crop yields is becoming increasingly important under the current context in which food security needs to be ensured despite the challenges brought by climate change, an expanding world population accompanied by rising incomes, increasing soil erosion, and decreasing water resources. Temperature, radiation, water availability and other environmental conditions influence crop growth, development, and final grain yield in a complex nonlinear manner. Machine learning (ML) techniques, and deep learning (DL) methods in particular, can account for such nonlinear relations between yield and its covariates. However, they typically lack transparency and interpretability, since the…