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Figure 4 in Influence of Trichoderma harzianum and Bacillus thuringiensis with reducing rates of NPK on growth, physiology, and fruit quality of Citrus aurantifolia
Figure 4. Effect of two biofertilizers mixing with different level of NPK on leaf TSS content of Key lemon (Limau nipis). Error bars indicates ±SE. Different letters in the bar graph represent the statistically significant at 5% level. T0, control; T1, NPK 100% (100 g); T2, T. harzianum 50% (5g) + NPK 50%; T3, B. thuringiensis 50% (5g) + NPK 50%; T4, T. harzianum 75% (7.5g) + NPK 25%; T5, B. thuringiensis 75% (7.5 g) + NPK 25%, T6, 100% T. harzianum (10 g); T7, 100% B. thuringiensis (10 g).
Figure 5 in Influence of Trichoderma harzianum and Bacillus thuringiensis with reducing rates of NPK on growth, physiology, and fruit quality of Citrus aurantifolia
Figure 5. Effect of two biofertilizers mixing with different level of NPK on fruit TSS content of Key lemon (Limau nips). Error bars indicates ±SE. Different letters in the bar graph represent the statistically significant at 5% level. T0, control; T1, NPK 100% (100 g); T2, T. harzianum 50% (5g) + NPK 50%; T3, B. thuringiensis 50% (5g) + NPK 50%; T4, T. harzianum 75% (7.5g) + NPK 25%; T5, B. thuringiensis 75% (7.5 g) + NPK 25%, T6, 100% T. harzianum (10 g); T7, 100% B. thuringiensis (10 g).
Figure 1 in Influence of Trichoderma harzianum and Bacillus thuringiensis with reducing rates of NPK on growth, physiology, and fruit quality of Citrus aurantifolia
Figure 1. Effect of two biofertilizers mixing with different level of NPK on specific leaf area of limau nipis. Error bars indicate ± S. E. Different small case letters in mean value bars represent statistical difference at 5% level. T0, control; T1, NPK 100% (100 g); T2, T. harzianum 50% (5g) + NPK 50%; T3,B. thuringiensis 50% (5g) + NPK 50%; T4, T. harzianum 75% (7.5g) + NPK 25%; T5, B. thuringiensis 75% (7.5 g) + NPK 25%, T6, 100% T. harzianum (10 g); T7, 100% B. thuringiensis (10 g).
Data from: A reaction norm for flowering time plasticity reveals physiological footprints of maize adaptation
<div> <p>Understanding how plant phenotypes are shaped by their environments is crucial for addressing questions about crop adaptation to new environments. This study investigated the interplay between developmental responses to temperature fluctuations and photoperiod perception in maize that contribute to genotype-by-environment variation in flowering time. We present a physiological reaction norm for flowering time plasticity (PRN-FTP) for studying large collections of genotypes tested in multi-environment trial (MET) networks. Using a new variable for computational envirotyping of sensed photoperiod, it was found that, at high latitudes, different genotypes in the same environment can experience hours-long differences in photoperiod. This emphasizes the importance of considering genotype-specific differences in the experienced environment when investigating plasticity. A statistical framework is introduced for modeling the PRN-FTP as a non-linear response function, with parameters putatively linked to different regulatory modules for flowering time. Applying the PRN-FTP to a sample of global breeding material for maize showed that tropical and temperate maize occupy distinct territories of the trait space for PRN-FTP parameters, supporting that the geographical spread and adaptation of maize was differentially mediated by exogenous and endogenous pathways for flowering time regulation. Our results have implications for understanding crop adaptation and for future crop improvement efforts.</p> </div>
Рис. 2. СреΑнее процентное соΑержание в гастроΛитах гусей основных грануΛометрических фракций зерен (сΛева) и их минераΛьных разновиΑностей (справа) Fig. 2. Average percentage of the main granulometric fractions of grains (left) and their mineral varieties (right) in goose gastroliths in The mineral composition of gastroliths in the stomachs of Anatidae in Primorsky Region and the importance of silicon minerals in the physiology of birds
Рис. 2. СреΑнее процентное соΑержание в гастроΛитах гусей основных грануΛометрических фракций зерен (сΛева) и их минераΛьных разновиΑностей (справа) Fig. 2. Average percentage of the main granulometric fractions of grains (left) and their mineral varieties (right) in goose gastroliths
Рис. 3. А — гастроΛиты гуся беΛоΛобого (кварц и отΑеΛьные кристаΛΛы амфибоΛов), ХороΛьский район, сеΛо Сиваковка; Б — гастроΛиты из жеΛуΑка гуся беΛоΛобого (размерность кварцевых зерен), южный берег оз. Ханка Fig. 3. A — gastroliths of a white-fronted goose (quartz and individual crystals of amphiboles), Khorolsky District, Sivakovka village; Б — gastroliths from the stomach of a white-fronted goose (dimension of quartz grains), the southern shore of Lake Khanka in The mineral composition of gastroliths in the stomachs of Anatidae in Primorsky Region and the importance of silicon minerals in the physiology of birds
Рис. 3. А — гастроΛиты гуся беΛоΛобого (кварц и отΑеΛьные кристаΛΛы амфибоΛов), ХороΛьский район, сеΛо Сиваковка; Б — гастроΛиты из жеΛуΑка гуся беΛоΛобого (размерность кварцевых зерен), южный берег оз. Ханка Fig. 3. A — gastroliths of a white-fronted goose (quartz and individual crystals of amphiboles), Khorolsky District, Sivakovka village; Б — gastroliths from the stomach of a white-fronted goose (dimension of quartz grains), the southern shore of Lake Khanka
Рис. 1. А — среΑнее процентное соΑержание грануΛометрических фракций в составе гастроΛитов уток с Ханкайского (сΛева) и с Хасанского (справа) участков; Б — среΑнее процентное соΑержание минераΛов в гастроΛитах уток с Ханкайского (сΛева) и с Хасанского (справа) участков in The mineral composition of gastroliths in the stomachs of Anatidae in Primorsky Region and the importance of silicon minerals in the physiology of birds
Рис. 1. А — среΑнее процентное соΑержание грануΛометрических фракций в составе гастроΛитов уток с Ханкайского (сΛева) и с Хасанского (справа) участков; Б — среΑнее процентное соΑержание минераΛов в гастроΛитах уток с Ханкайского (сΛева) и с Хасанского (справа) участков
Fig. 7 in Morphology of the female reproductive system and physiological age-grading of Megamelus scutellaris (Hemiptera: Delphacidae), a biological control agent of water hyacinth
Fig. 7. Number of eggs ovulated by adult females of Megamelus scutellaris correlated by a) age (days) and b) collar length (mm). The solid line represents the linear relationship between variables and the dashed lines is the 95% confidence interval (n = 15; P = 0.001 and r = 0.778).
Fig. 6. The 3 in Morphology of the female reproductive system and physiological age-grading of Megamelus scutellaris (Hemiptera: Delphacidae), a biological control agent of water hyacinth
Fig. 6. The 3 parous classes of Megamelus scutellaris. The P1 class (a and b) is characterized by the presence of follicular relics, which may not be present in some or all ovarioles, may be light in coloration and may or may not encircle the base of the ovariole. The follicular relics do not occur at high enough densities to cause an expansion or bulging. The collar may or may not be visible and does not extend past the follicular relic accumulation area. In the P2 class (c and d) follicular relics are present in all ovarioles and at high enough densities to cause bulging. They are distinctly yellow in coloration and relatively darker in comparison to those found in the P1 class. The collar is easily seen and typically extends past the follicular accumulation area. In the P3 class (e and f) follicular relics are variable, may or may not be in high enough densities to cause bulging, and typically completely encircle the base. The collar length easily surpasses the follicular relic accumulation area.
Fig. 4 in Morphology of the female reproductive system and physiological age-grading of Megamelus scutellaris (Hemiptera: Delphacidae), a biological control agent of water hyacinth
Fig. 4. Follicular relic formation and appearance in the distal area of an ovariole and anterior lateral oviduct (loa) with the germinal vesicle (gv), oocyte with yolk (oy), follicular epithelium (fe) beginning to slough off into the ovariole base (as shown by the arrow), follicular relics (fr), and collar in Megamelus scutellaris. Note the granular appearance of follicular relics having a high enough density to begin to expand or bulge the sides of the lateral oviduct.
Fig. 2 in Morphology of the female reproductive system and physiological age-grading of Megamelus scutellaris (Hemiptera: Delphacidae), a biological control agent of water hyacinth
Fig. 2. Photomicrographs of the female reproductive system of Megamelus scutellaris showing a) distal portion of the ovary showing the distal lateral oviduct (lop), common oviduct (co), bursa copulatrix (b), and spermatheca/spermathecal gland (spt and sptg, respectively), and b) close-up of ovariole morphology (b) showing the anterior lateral oviduct (loa), germarium (g), vitellarium (v), and terminal filament (tf).
Fig. 1 in Morphology of the female reproductive system and physiological age-grading of Megamelus scutellaris (Hemiptera: Delphacidae), a biological control agent of water hyacinth
Fig. 1. Photomicrograph of the female reproductive system of Megamelus scutellaris showing ovaries (ov), common oviduct (c), anterior and posterior portions of the lateral oviduct (loa and lop, respectively), and overall structure of a follicle including the germinal vesicle (gv) and oocyte with yolk (oy).
Fig. 3 in Morphology of the female reproductive system and physiological age-grading of Megamelus scutellaris (Hemiptera: Delphacidae), a biological control agent of water hyacinth
Fig. 3. Photomicrographs of the female reproductive system of Megamelus scutellaris showing a) close-up of the distal portion of an ovariole showing the anterior lateral oviduct (loa), follicular epithelium (fe), ovariole sheath (os), germinal vesicle (gv), oocyte with yolk (oy), and collar (c), and b) distal portion of an ovariole showing a newly ovulated egg (e) into the anterior lateral oviduct (loa), ovary (ov), ovariole (lov), and the collar (c).
Fig. 5. The 3 in Morphology of the female reproductive system and physiological age-grading of Megamelus scutellaris (Hemiptera: Delphacidae), a biological control agent of water hyacinth
Fig. 5. The 3 nulliparous stages of Megamelus scutellaris. a) N1—Note the lack of differentiation in the vitellarium (v) and large size of the germarium (g) in comparison to the vitellarium. b) N2—In this stage the ovarioles are fully differentiated, no fully mature follicles, and no follicular relics. c and d) N3—In this stage the ovarioles are fully differentiated, no follicular relics are present, and at least 2 follicles are mature and ready to be ovulated as indicated by darkening of the interior of the oocyte by yolk deposition.
Fig. 3. Minimum spanning network for Haemoproteus and Plasmodium mitochondrial DNA cytochrome b in Spatial, temporal, molecular, and intraspecific differences of haemoparasite infection and relevant selected physiological parameters of wild birds in Georgia, USA
Fig. 3. Minimum spanning network for Haemoproteus and Plasmodium mitochondrial DNA cytochrome b haplotypes detected in four species of passerines from Georgia (USA). Circles are drawn proportional to the frequency at which haplotypes were observed. Color represents the host species from which haplotypes originated: red for Northern Cardinal (Cardinalis cardinalis), blue for Indigo Bunting (Passerina cyanea), yellow for White-throated Sparrow (Zonotrichia albicollis), and grey for Tufted Titmouse (Baeolophus bicolor). A single mutation separates nodes unless explicitly indicated by number. Letters within each node refer to Table 8 which indicates the haplotype name, sampling location, and other factors associated with hosts.
Fig. 1 in Spatial, temporal, molecular, and intraspecific differences of haemoparasite infection and relevant selected physiological parameters of wild birds in Georgia, USA
Fig. 1. Map of Georgia (USA) indicating the location of the six sampling sites for identifying haemoparasite infections of birds in the northern and southern regions of the state.
Fig. 2 in Spatial, temporal, molecular, and intraspecific differences of haemoparasite infection and relevant selected physiological parameters of wild birds in Georgia, USA
Fig. 2. Average percent cell volume (PCV) values for five target bird species from Georgia (USA). Different letters indicate significant differences between bird species (p <0.05).
Fig. 4 in Physiological and Biochemical Thermoregulatory Responses in Male Chinese Hwameis to Seasonal Acclimatization: Phenotypic Flexibility in a Small Passerine.
Fig. 4. Seasonal variation in dry mass (A), state-4respiration (B), and cytochrome c oxidase (C) in the pectoral muscle, heart, liver and kidneys of hwameis (Garrulaxcanorus) captured in either summer or winter in Wenzhou, China. Data are shown as mean ± SEM, *p <0.05, **p <0.01, ***p <0.001.
Fig. 3 in Physiological and Biochemical Thermoregulatory Responses in Male Chinese Hwameis to Seasonal Acclimatization: Phenotypic Flexibility in a Small Passerine.
Fig. 3. Correlations between body mass and resting metabolic rate (RMR) (A), between body mass and EWL (B), between RMR and EWL (C), and between RMR and thermal conductance (D) in Chinese hwameis (Garrulax canorus) captured in either summer or winter in Wenzhou, China.
Fig. 1 in Physiological and Biochemical Thermoregulatory Responses in Male Chinese Hwameis to Seasonal Acclimatization: Phenotypic Flexibility in a Small Passerine.
Fig. 1. Minimum, maximum and mean ambient daily summer (July to August 2013) and winter (January to February 2014) temperatures in Wenzhou, China. Mean ambient temperature ranged from 31.3 ± 0.2°C in summer to 8.6 ± 0.4°C in winter.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
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.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.