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122 results for “Cannabis sativa”
Figure 7 in Host status and susceptibility of Cannabis sativa cultivars to root-knot nematodes
Figure 7: Hemp plant dry weights (g) two hemp cultivars (Eletta Campana = fiber, Cherry Blossom x T1 = CBD) exposed to two RKN species, M. enterolobii and M. hapla. Factor levels not connected by the same letter are significantly different according to Tukey's HSD where P ≤ 0.05. PCBxT1 = Cherry Blossom x T1, PEC = Eletta (Trial 5).
Figure 3 in Host status and susceptibility of Cannabis sativa cultivars to root-knot nematodes
Figure 3: Hemp plant dry weights (g) with a mixed population of root-knot species and 11 hemp cultivars; all plants were inoculated with 10,000 RKN eggs. Factor levels not connected by the same letter are significantly different according to Tukey's HSD with P ≤ 0.05 (Trial 2).
Figure 2 in Host status and susceptibility of Cannabis sativa cultivars to root-knot nematodes
Figure 2: Hemp plant dry weights (g) for inoculated (+) and uninoculated (-) plants with a mixed population of root-knot species and six European hemp cultivars. Factor levels not connected by the same letter are significantly different according to Tukey's HSD with P ≤ 0.05 (Trial 1).
Figure 1 in Host status and susceptibility of Cannabis sativa cultivars to root-knot nematodes
Figure 1: Root galls caused by RKN (M. javanica and M. incognita mixed population) on hemp roots (cv. Carmagnola Selezionata, left) compared to cucumber roots (cv. Dasher II, middle) (Trial 1) and cv. Cherry Blossom x T1 (right; Trial 2) (Photos J. Coburn).
Figure 5 in Host status and susceptibility of Cannabis sativa cultivars to root-knot nematodes
Figure 5: Hemp plant dry weights (g) for two cannabigerol (CBG) hemp cultivars and a nematicide in naturally RKN-infested soil. P values (P ≤ 0.05) represent significant differences between cultivars by treatment (PG = Gold, PP= Panacea; NA = naturally infested soil, V = Velum, ST = steamed soil.). Velum was applied at 0.48 kg a.i./Ha. Factor levels not connected by the same letter are significantly different according to Tukey's HSD with P ≤ 0.05 (Trial 4).
Figure 6 in Host status and susceptibility of Cannabis sativa cultivars to root-knot nematodes
Figure 6: Cannabis sativa (cv. Panacea) 60 days after planting in RKN-infested field soil. (Left) naturally infested soil, (middle) nematicide-treated (fluopyram) soil, (right) steamed soil (Photo J. Coburn).
Figure 4 in Host status and susceptibility of Cannabis sativa cultivars to root-knot nematodes
Figure 4: Hemp plant dry weights (g) for RKN inoculated (+) and uninoculated (-) plants with two CBD and two Chinese fiber hemp cultivars. Factor levels not connected by the same letter are significantly different according to Tukey's HSD with P ≤ 0.05 (Trial 3).
Figure 1 in Review of nematode interactions with hemp (Cannabis sativa)
Figure 1: Time chart of primary literature reporting root-knot nematode-Cannabis sativa associations. Mh, Meloidogyne hapla; Mi, M. incognita; Mj, M. javanica.
Figure 3 in Review of nematode interactions with hemp (Cannabis sativa)
Figure 3: Chemicals isolated from Cannabis sativa roots. (A) Phytosterols. (B) Triterpenoids. (C) Cannabinoids: - (−)-trans-∆9-tetrahydrocannabinol (THC); cannabidiol (CBD); cannabidiolic acid (CBDA). (D) Nitrogen-containing compounds.
Figure 2 in Review of nematode interactions with hemp (Cannabis sativa)
Figure 2: Galling of Meloidogyne incognita on Cannabis sativa 'Cherry', Pi = 10,000 eggs. (A) Entire root system. (B) Closeup of small, white galls. Scale = 5 mm.
Figure 2 in First report of Meloidogyne hapla on hemp (Cannabis sativa) in Oregon
Figure 2: Phylogenetic relationships between Meloidogyne species as inferred from the Bayesian analysis of the mitochondrial DNA CoxII-IGS under the GTR + I + G model. Posterior probabilities of over 50% are given for appropriate clades. Sequences generated in this study are identified in bold. Meloidoyne hapla sequences were retrieved from GenBank, aligned, and trimmed with BioEdit v.7.0.5.3. The best substitution model was determined using jModelTest 2.1.10 v20160303 and the Bayesian analysis was performed using MrBayes v3.2.6. Finally, the tree was visualized using FigTree v1.4.3.
Figure 1 in First report of Meloidogyne hapla on hemp (Cannabis sativa) in Oregon
Figure 1: Meloidogyne hapla, A) body length, B) stylet (S) and knobs (Kn), C) and D) tail. Scales: A: 100 μm, B: 20 μm, and C,D: 50 μm.
Figura 1 in Artropofauna asociada al cultivo de Cannabis sativa L., 1753 (Urticales: Cannabaceae) medicinal en Antioquia, Colombia
Figura 1. Proporción de órdenes y familias de insectos, método de captura utilizado, hábito del insecto y etapa fenológica del cultivo de Cannabis sativa medicinal en Colombia. / Proportion of insect orders and families, capture method used, insect habit and phenological stage of medicinal Cannabis sativa crop in Colombia.
Figuras 3a-r in Artropofauna asociada al cultivo de Cannabis sativa L., 1753 (Urticales: Cannabaceae) medicinal en Antioquia, Colombia
Figuras 3a-r. Insectos recolectados en un cultivo de Cannabis sativa. / Insect collected in a Cannabis sativa crop. a) Notiobia sp. b) Platynus sp. c) Labarrus pseudolividus. d) Spodoptera cf. ornithogalli. e) Agrius cingulata. f) Xylophanes tersa. g) Polyglypta costata. h) Chinavia sp. i) Agallia sp. j) Linepithema sp. k) Pheidole sp. l) Campsomeris sp. m) Eucelatoria sp. n) Palpada pos. prietorum. o) Sarcofahrtiopsis sp. p) Kopis sp. q) Brachybaenus rubrinervosus. r) Orphulella concinnula.
Quantification of Fatty Acids in Hemp Seeds (Cannabis sativa L.) and Yield Prediction Using Machine Learning for Soxhlet and Ultrasound Extraction Methods
<p>This study focuses on the quantification of fatty acids present in hemp seeds (Cannabis sativa L.) cultivated in the Ecuadorian Andes using Soxhlet and ultrasound extraction methods. The aim is to evaluate and compare the extraction efficiency of these two techniques. Furthermore, machine learning models are applied to predict extraction yields based on experimental conditions. Using locally cultivated seeds provides valuable insights into the influence of regional agro-climatic conditions on the chemical composition. The integration of predictive algorithms offers a novel approach to optimizing the extraction process, enhancing both precision and efficiency. The findings could contribute to developing sustainable extraction methods for high-value bioactive compounds in the food and pharmaceutical industries.</p>
Cannabis sativa L. (BR0000011857501)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Cannabis sativa L. (BR0000009497207)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Cannabis sativa L. (BR0000014442995)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Cannabis sativa L. (BR0000011859017)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Cannabis sativa L. (BR0000011857020)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
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