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Waxy corn starch is widely used in food and papermaking industries due to its unique properties. In this work, the structural and functional properties of starch isolated from waxy corn at different stages of kernel growth were investigated and their relationships were clarified. The results showed that with kernel growth, the surface of starch granules became smooth gradually, and the inner growth rings and the porous structure grew and became clear. Meanwhile, the weight-average molecular mass (Mw), root mean square radius (Rg), and average particle size increased while the amylose content decreased, which should account for the decreased pasting temperature (from 71.37 to 67.44 °C) and increased peak viscosity (1574.2 to 1883.1 cp) and breakdown value observed. Besides, the contents of slowly digestible starch (SDS) and resistant starch (RS) in waxy corn starch decreased significantly (from 44.01% to 40.88% and from 16.73% to 9.80%, respectively, p < 0.05) due to decreases in the double helix content, crystallinity, and structural order, and increases in the semi-crystalline lamellae thickness and the amorphous content. This research provides basic data for the rational utilization of waxy corn starch at different stages of kernel growth.

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Boron (B) and zinc (Zn) are essential micronutrients of plant nutrition programs in orchards for securing the crop quality and yield. Although orchard supplementation with B and Zn is a common practice to overcome deficiencies or maintain their optimal levels, the efficiency of combined B and Zn spraying in relation to European hazelnut (Corylus avellana L.) phenological stage has not been investigated so far. Leaf and kernel mineral and functional traits were studied in cultivar Tonda di Giffoni after B and Zn spraying in four phenological stages. During the 2016/2017 season, 9-year-old trees were sprayed with B (0, 800, and 1,600 mg L-1) and Zn (0, 400, and 800 mg L-1) under three treatments: B0+Zn0, B800+Zn400, and B1600+Zn800 implemented in three spring application programs scheduled from October to December (P1: four times, P2: early two times, and P3: late two times). B and Zn treatments in P1 and P3 led to higher Zn concentration both in leaves and in kernels compared with non-sprayed trees. Stabilized nut production increased 2.5-fold under B800+Zn400 in all three programs. Kernel/nut ratio improved in both B+Zn treatments in P1 and P3, while the percentage of blank nuts was reduced compared with B0+Zn0. Increased radical scavenging activity in B+Zn-treated kernels and leaves was not attributed to the accumulation of phenolics in P3 compared with B0+Zn0, whereas B and Zn spraying reduced the level of lipid peroxidation in both studied organs. According to the results, combined B and Zn should be sprayed at the end of spring (P3) on hazelnut plantations in temperate areas such as Southern Chile, whereas early applications (P2) showed an irregularity in nut production and functional traits in nuts. Moderate and partialized rates of B and Zn and the time of implementation contribute to improving the quantitative and qualitative features crucial for future sustainable hazelnut production.

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Kernel atoms of Au nanoclusters are packed layer-by-layer along the [001] direction with every full (001) monolayer composed of 8 Au atoms (Au8 unit) in nanoclusters with formula of Au8n+4 (TBBT)4n+8 (n is the number of Au8 units; TBBTH=4-tert-butylbenzenelthiol). It is unclear whether the kernel atoms can be stacked in a defective-layer way along the [001] direction during growth of the series of nanoclusters and how the kernel layer number affects properties. Now, a nanocluster is synthesized that is precisely characterized by mass spectrometry and single-crystal X-ray crystallography, revealing a layer stacking mode in which a half monolayer composed of 4 atoms (Au4 unit) is stacked on the full monolayer along the [001] direction. The size and the odevity of the kernel layer number influence the properties (polarity, photoluminescence) of gold nanoclusters. The obtained nanocluster extends the previous formula from Au8n+4 (TBBT)4n+8 to Au4n+4 (TBBT)2n+8 (n is the number of Au4 units).

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Individual kernel weight is an important trait for maize yield determination. We have identified genomic regions controlling this trait by using the B73xMo17 population; however, the effect of genetic background on control of this complex trait and its physiological components is not yet known. The objective of this study was to understand how genetic background affected our previous results. Two nested stable recombinant inbred line populations (N209xMo17 and R18xMo17) were designed for this purpose. A total of 408 recombinant inbred lines were genotyped and phenotyped at two environments for kernel weight and five other traits related to kernel growth and development. All traits showed very high and significant (P < 0.001) phenotypic variability and medium-to-high heritability (0.60-0.90). When N209xMo17 and R18xMo17 were analyzed separately, a total of 23 environmentally stable quantitative trait loci (QTL) and five epistatic interactions were detected for N209xMo17. For R18xMo17, 59 environmentally stable QTL and 17 epistatic interactions were detected. A joint analysis detected 14 stable QTL regardless of the genetic background. Between 57 and 83% of detected QTL were population specific, denoting medium-to-high genetic background effects. This percentage was dependent on the trait. A meta-analysis including our previous B73xMo17 results identified five relevant genomic regions deserving further characterization. In summary, our grain filling traits were dominated by small additive QTL with several epistatic and few environmental interactions and medium-to-high genetic background effects. This study demonstrates that the number of detected QTL and additive effects for different physiologically related grain filling traits need to be understood relative to the specific germplasm.

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Maize kernel weight (KW) is associated with the duration of the grain-filling period (GFD) and the rate of kernel biomass accumulation (KGR). It is also related to the dynamics of water and hence is physiologically linked to the maximum kernel water content (MWC), kernel desiccation rate (KDR), and moisture concentration at physiological maturity (MCPM). This work proposed that principles of phenotypic plasticity can help to consolidated the understanding of the environmental modulation and genetic control of these traits. For that purpose, a maize population of 245 recombinant inbred lines (RILs) was grown under different environmental conditions. Trait plasticity was calculated as the ratio of the variance of each RIL to the overall phenotypic variance of the population of RILs. This work found a hierarchy of plasticities: KDR ≈ GFD > MCPM > KGR > KW > MWC. There was no phenotypic and genetic correlation between traits per se and trait plasticities. MWC, the trait with the lowest plasticity, was the exception because common quantitative trait loci were found for the trait and its plasticity. Independent genetic control of a trait per se and genetic control of its plasticity is a condition for the independent evolution of traits and their plasticities. This allows breeders potentially to select for high or low plasticity in combination with high or low values of economically relevant traits.

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