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336 results for “Drought Stress”
Banks grass mite (Acari: Tetranychidae) suppression may add to the benefit of drought-tolerant corn hybrids exposed to water-stress
<p class="CxSpFirst">Spider mite (Acari: Tetranychidae) outbreaks are common on corn grown in the arid West. Hot and dry conditions reduce mite development time, increase fecundity, and accelerate egg hatch. Climate change is predicted to increase drought incidents and produce more intense temperature patterns. Together, these environmental shifts may cause more frequent and severe spider mite infestations. Spider mite management is difficult as many commercially-available acaricides are ineffective due to the development of resistance traits in field mite populations. Therefore, alternative approaches to suppress outbreaks are critically needed. Drought-tolerant plant hybrids alleviate the challenges of growing crops in water-limited environments; yet, it is unclear if drought-tolerant hybrids exposed to water-stress affects mite outbreaks under these conditions. We conducted a greenhouse experiment to evaluate the effect of drought-tolerant corn hybrids on Banks grass mite, a primary pest of corn, under optimal irrigation and water-stress irrigation. This was followed by a 2-year field study investigating the effect of drought-tolerant corn hybrids exposed to the same irrigation treatments on Banks grass mite artificially infested on hybrids and resident spider mite populations. Results showed that water-stressed drought-tolerant hybrids had significantly lower Banks grass mite and resident spider mite populations than water-stressed drought-susceptible hybrids. Interestingly, water-stressed drought-tolerant hybrids had equal Banks grass mite populations to drought-susceptible and drought-tolerant hybrids under optimal irrigation. We posit that planting drought-tolerant hybrids may suppress spider mite outbreaks in water-challenged areas.</p>
Cowpea drought stress application at early vegetative stage 2022 - screen 02 - day 08 - raw image data
<p>Cowpea (<em>Vigna unguiculata</em>) miniCore accessions were screened for responses to drought stress at early vegetative stress. The cowpea seedlings were exposed to drought stress at 17 days after germination using the weight of the pot and AAWEsmo device, developed in Julkowska Lab, Boyce Thompson Institute. The seedlings were kept at 60 and 10% of soil water holding capacity for 2 weeks and the data on cowpea shoot size, evapotranspiration and photosystem II efficiency was collected. </p> <p>This dataset represents the images collected for Screen number 02 and day 08 after drought stress application. </p>
Fig. 7 in Phenolic and lipophilic metabolite adjustments in Olea europaea (olive) trees during drought stress and recovery
Fig. 7. General overview of phenolic and lipophilic profile variation after stress treatments (exposure) and stress relief (recovery). Relative levels [expressed as log2 (stress/control)] are given besides each identified metabolite as a heatmap: WD – water deficit and WDHS+UVB – water deficit with heat and high UVB shocks. Nd - not detected.
Fig. 6 in Phenolic and lipophilic metabolite adjustments in Olea europaea (olive) trees during drought stress and recovery
Fig. 6. Carbohydrates profile of O. europaea leaves from plants under control (C) conditions and exposed to WD and WD HS+UVB treatments. Values are means ± standard deviation (n = 4). For each compound, the different letters indicate statistical between treatments (P <0.05).
Fig. 3 in Phenolic and lipophilic metabolite adjustments in Olea europaea (olive) trees during drought stress and recovery
Fig. 3. Fatty acids and sterols profiles of O. europaea leaves from plants under control (C) conditions and exposed to WD and WDHS+UVB treatments. Values are means ± standard deviation (n = 4). For each compound, the different letters indicate statistical between treatments (P <0.05).
Fig. 5 in Phenolic and lipophilic metabolite adjustments in Olea europaea (olive) trees during drought stress and recovery
Fig. 5. Terpenes profile of O. europaea leaves from plants under control (C) conditions and exposed to WD and WDHS+UVB treatments. Values are means ± standard deviation (n = 4). For each compound, the different letters indicate statistical between treatments (P <0.05).
Fig. 2 in Phenolic and lipophilic metabolite adjustments in Olea europaea (olive) trees during drought stress and recovery
Fig. 2. Secoiridoids and HCAds profiles of O. europaea leaves from plants under control (C) conditions and exposed to WD and WDHS+UVB treatments. Values are means ± standard deviation (n = 4). For each compound, the different letters indicate statistical between treatments (P <0.05). Nd – not detected (2′′- methoxyoleuropein was not detected in DS plants and methyloleuropein was not detected in DSHS+UVB plants during the stress recovery phase).
Fig. 1 in Phenolic and lipophilic metabolite adjustments in Olea europaea (olive) trees during drought stress and recovery
Fig. 1. Flavonoids profile of O. europaea leaves from plants under control conditions (C) and exposed to WD and WDHS+UVB treatments. Values are means ± standard deviation (n = 4). For each compound, the different letters indicate statistical differences between treatments (P <0.05).
Fig. 8 in Drought stress induces biosynthesis of flavonoids in leaves and saikosaponins in roots of Bupleurum chinense DC
Fig. 8. Effects of drought stress on expression of key enzyme genes. A: HMGR; B: IPPI; C: FPS; D: SS; E: SE; F: β-AS; G: P450-7; H: P450-12; I: UGT-8. Shown are the means ± standard deviation (n = 3). The asterisk indicates a significant difference (p <0.05) between drought-stressed and control plants (Duncan's single-factor variance analysis).
Fig. 7 in Drought stress induces biosynthesis of flavonoids in leaves and saikosaponins in roots of Bupleurum chinense DC
Fig. 7. Changes in saikosaponin content under drought stress. (A) Total saikosaponin content. (B) SS-a content. (C) SS-d content. (D) SS-c content. (E) SS-e content. (F) SS-f content. Shown are the means ± standard deviation (n = 9). The asterisk indicates a significant difference (p <0.05) between drought-stressed and control plants (Duncan's single-factor variance analysis).
Fig. 4 in Drought stress induces biosynthesis of flavonoids in leaves and saikosaponins in roots of Bupleurum chinense DC
Fig. 4. Effects of drought stress on activities of SOD, POD, and CAT. (A) Changes in SOD activity. (B) Changes in POD activity. (C) Changes in CAT activity. Shown are the means ± standard deviation (n = 3). The asterisk indicates a significant difference (p <0.05) between drought-stressed and control plants (Duncan's singlefactor variance analysis).
Fig. 5 in Drought stress induces biosynthesis of flavonoids in leaves and saikosaponins in roots of Bupleurum chinense DC
Fig. 5. Changes in flavonoid content under drought stress. (A) Rutin content. (B) Quercetin content. (C) Kaempferol content. (D) Isorhamnetin content. Shown are the means ± standard deviation (n = 9). The asterisk indicates a significant difference (p <0.05) between drought-stressed and control plants (Duncan's single-factor variance analysis).
Fig. 2 in Drought stress induces biosynthesis of flavonoids in leaves and saikosaponins in roots of Bupleurum chinense DC
Fig. 2. Changes in soil water content. Shown are the means ± standard deviation (n = 8). The asterisk indicates a significant difference (p <0.05) between drought-stressed and control plants (Duncan's Single-factor variance analysis).
Fig. 3 in Drought stress induces biosynthesis of flavonoids in leaves and saikosaponins in roots of Bupleurum chinense DC
Fig. 3. Changes in concentrations of malondialdehyde (MDA) and osmoregulatory substances during drought stress. (A) Soluble protein content. (B) Proline content. (C) Soluble sugar content. (D) MDA contents. Shown are expressed the means ± standard deviation (n = 3). The asterisk indicates a significant difference (p <0.05) between drought-stressed and control plants (Duncan's single-factor variance analysis).
Fig. 6 in Drought stress induces biosynthesis of flavonoids in leaves and saikosaponins in roots of Bupleurum chinense DC
Fig. 6. Effects of drought stress on expression of flavonoid biosynthesis key enzyme genes. A: C4H; B: 4CL; C: IFS; D: F3H; E: DFR. Shown are the means ± standard deviation (n = 3). The asterisk indicates a significant difference (p <0.05) between drought-stressed and control plants (Duncan's single-factor variance analysis).
Fig. 7 in Transcriptome sequencing of the apricot (Prunus armeniaca L.) and identification of differentially expressed genes involved in drought stress
Fig. 7. Effects of control and drought stress on leaf microstructure of apricot. a, c, e, represent the leaf stomata, vertical section, and cuticle in the control group, respectively. b, d, f, represent the leaf stomata, vertical section, and cuticle in the drought stress group, respectively.
Fig. 4 in Transcriptome sequencing of the apricot (Prunus armeniaca L.) and identification of differentially expressed genes involved in drought stress
Fig. 4. KEGG enrichment of annotated DEGs in Treat versus Control. The Y-axis shows the KEGG pathway and the X-axis shows the Rich factor. This q value goes from purple to red, which means from 1 to 0. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 3 in Transcriptome sequencing of the apricot (Prunus armeniaca L.) and identification of differentially expressed genes involved in drought stress
Fig. 3. GO classifications of DEGs for Treat versus Control. The Y-axis represents the number of DEGs in a category. The BP, CC and MF represent biological process, cellular component and molecular function respectively.
Fig. 5. SSR motifs distribution. The X in Transcriptome sequencing of the apricot (Prunus armeniaca L.) and identification of differentially expressed genes involved in drought stress
Fig. 5. SSR motifs distribution. The X-axis is SSR type, the Y-axis value is the coordinate, the specific number of repetitions should correspond to the legend according to the color, and the Z-axis is the number of SSR. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 1 in Transcriptome sequencing of the apricot (Prunus armeniaca L.) and identification of differentially expressed genes involved in drought stress
Fig. 1. Gene Function Classification of the assembled unigenes. Unigenes with BLAST hits were classified into three major categories and 56 sub-categories in GO. The Y-axis shows the number of genes in each sub-category.
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
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