Academic literature on the topic 'Seedling color'
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Journal articles on the topic "Seedling color"
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Jacobs, Douglass F. "Reforestation of a Salvage-Logged High-Elevation Clearcut: Engelmann Spruce Seedling Response to Tree Shelters after 11 Growing Seasons." Western Journal of Applied Forestry 26, no. 2 (2011): 53–56. http://dx.doi.org/10.1093/wjaf/26.2.53.
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Abstract High-elevation clearcut sites in the southern Rocky Mountains are difficult to reforest successfully and many sites remain poorly stocked decades after harvest. This article presents results after 11 growing seasons of a project designed to examine use of tree shelters to provide initial shade for planted Engelmann spruce (Picea englemannii Parry ex Engelm.) seedlings. Seedlings were planted in 1996 on a 48-ha site at an elevation of approximately 3,273 m in southwestern Colorado, with different shelter colors providing various shading levels. A control, consisting of shading using debris within the site, was also included. Results after 2 years were presented previously. To examine seedling response to tree shelter removal after seedling establishment, half of shelters were removed in 2000 and seedlings were reassessed in 2007. Control seedlings had lower survival (35%) than any other treatment (ranging from 59 to 78%). Shelter removal in the lightest two shelter color treatments did not reduce survival, suggesting that seedlings can grow in full sun after 4 years of shading. The best overall seedling development (i.e., survival, absolute height, and root collar diameter) occurred in the lightest shelter color with shelters removed. Tree shelters offer a viable means to restore high-elevation spruce-fir sites where past reforestation has proven difficult.
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Zhang, Gan, Yongshuang Wen, Yuzhi Tan, et al. "Identification of Cabbage Seedling Defects in a Fast Automatic Transplanter Based on the maxIOU Algorithm." Agronomy 10, no. 1 (2020): 65. http://dx.doi.org/10.3390/agronomy10010065.
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The automatic identification of seedling defects is an important technology of an intelligent automatic transplanting machine, which effectively improves the quality of the transplanting machine’s operation. The accurate segmentation of seedling substrate and seedling region is the key to the success of the seedling defect recognition algorithm. This paper proposes the maxIOU algorithm to calculate the image segmentation threshold: The image G channel and excess green color space were selected as the color space for the segmentation of the substrate region and seedling region by analyzing the color histogram. Several images were randomly selected from the dataset to generate a training set and were labeled manually as the ground truth. The training set images were segmented using a threshold of zero to 255, and the intersection over union (IOU) were calculated using the algorithm segmented result and the ground truth. The threshold corresponding to the average IOU maximum was used as the segmentation threshold. After image segmentation, three features (area of the substrate, area of the seedling, and filling ratio of the lower part of the substrate) were obtained by the algorithm, and the image was identified for whether there was an empty conveyor belt, seedling deficiency, multiple seedlings, skew, and damaged substrate. The algorithm was tested on the automatic transplanter test platform. The experiment results were as follows: Firstly, the image segmentation threshold was calculated by the maxIOU method. The color component interval corresponding to the segmented substrate region was [0, 24] in the G channel, and the color component interval corresponding to the segmented seedling region was [21, 255] in the excess green channel. The average IOU of the substrate area was 0.854, and the average IOU of the seedling area was 0.820 in the verification experiment. Secondly, a dataset including 431 normal seedling images and 69 defective seedling images (empty conveyor belt, seedling deficiency, multiple seedlings, skew, and damaged substrate) was identified for defects. The accuracy, precision, and recall were 97.6%, 97.4%, and 99.8%. The processing time was 71.4 ms. The conclusion of the experiment was as follows: the maxIOU algorithm had high accuracy in the segmentation of the substrate and seedling region. The defect identification algorithm had high accuracy for defect identification of cabbage seedlings, and the algorithm had good real-time performance, which can be applied to high speed field transplanters.
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Liao, Juan, Yao Wang, Junnan Yin, Lu Liu, Shun Zhang, and Dequan Zhu. "Segmentation of Rice Seedlings Using the YCrCb Color Space and an Improved Otsu Method." Agronomy 8, no. 11 (2018): 269. http://dx.doi.org/10.3390/agronomy8110269.
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Rice seedling segmentation is a fundamental process of extracting the guidance line for automated rice transplanters with a visual navigation system, which can provide crop row information to ensure the transplanter plants seedlings along the crop row without damaging seedlings. However, obtaining accurate rice seedling segmentation in paddy fields is still a challenging task. In this paper, a rice seedling segmentation method in paddy fields is proposed. The method mainly consists of two steps: image graying and threshold segmentation. In the procedure of image graying, the RGB (Red Green Blue) seedling image is first converted into the YCrCb color space and a Cg component is constructed. A color-index 2Cg-Cb-Cr is then constructed for image graying based on the excess green index (2G-R-B), which can reduce the influence of illumination variation on the equality of image graying. For the second step, an improved Otsu method is proposed to segment rice seedlings. With respect to the improved Otsu method in this research, the background variance of within class variance is weighted by a probability parameter to ensure that the method works well for both bimodal and near-unimodal histogram images, and the search range of gray levels is constrained to reduce the time to search the segmentation threshold. Experimental results indicate that the proposed method achieves better segmentation results and reduces the computational cost compared with the traditional Otsu method and other improved Otsu methods.
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Grauke, L. J., and Richard D. O'Barr. "Initial Survival of Pecan Grafts on Seedling Rootstock of Pecan, Water Hickory, and their Interspecific Hybrid." HortTechnology 6, no. 1 (1996): 45–48. http://dx.doi.org/10.21273/horttech.6.1.45.
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`Oconee' pecan [Carya illinoinensis (Wangenh.) K. Koch] scions were grafted on seedling rootstock from nine open-pollinated seedstocks. Rootstock included three seedstocks each of pecan, water hickory [C. aquatica (F. Michx.) Nutt.], and their interspecific hybrid, Carya × lecontei (Little). Pecan seedlings had the largest basal diameters and water hickory seedlings the smallest. Seedlings of `Elliott' and `Curtis' seedstocks were larger than seedlings from `Moore' seedstock. Pecan and C. × lecontei seedlings were grafted more successfully than water hickory. Graft success varied among seedstocks of pecan and C. × lecontei Foliage color of seedlings, possibly indicative of iron nutritional status, was influenced by species; pecan seedling leaves were darker green than those of water hickory seedlings, but similar to C. × lecontei leaves. `Oconee' scion leaves were darker green on pecan rootstock than when grafted on C. × lecontei rootstock.
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Saputra, Hariadi, Yadi Setiadi, and Iwan Hilwan. "RESPON PERTUMBUHAN BIBIT ANGSANA (Pterocarpus indicus Willd.) TERHADAP MEDIA TUMBUH, PEMOTONGAN AKAR LATERAL DAN PEMBERIAN URIN SAPI Response of Angsana (Pterocarpus indicus Willd.) Seedling on Growing Media, Lateral Roots Cutting, and Cow’s Urine." Journal of Tropical Silviculture 8, no. 3 (2018): 154–59. http://dx.doi.org/10.29244/j-siltrop.8.3.154-159.
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Nursery is a process in producing good quality seedlings. Seedling quality is determined by physical-physiological quality including woody stem, health, height, diameter, number of leaves, leaf color and compactness of media. The quality of angsana seedlings in this study was observed using some growth media, lateral root cutting, and cow’s urine addition with various concentration and liquid organic fertilizer for 13 weeks. The study was conducted in a completely randomized design (CRD) in split plot with 3 growth mediums, 10 combinations of root-cutting and fertilizing treatment using 9 seedlings per treatment. Parameters observed during this study were seedling height (cm), seedling diameter (mm), total dry weight (g), shoot - root ratio (RPA) and compactness of roots. The results showed the media contain mixture of soil and manure (M2) with root-cutting treatment, addition of 20% cow urine and 5% EM4 (A2) was the best treatment for angsana seedlings with average value of 46.25 cm plant height, 6.09 mm diameter, 7.77 g total dry weight, shoot root ratio 1.89 and compactness of roots including the compact category.Key word : cow’s urine, lateral roots cutting, Pterocarpus indicus Willd., seedling quality.
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Beckman, T. G., J. Rodriguez Alcazar, W. B. Sherman, and D. J. Werner. "Evidence for Qualitative Suppression of Red Skin Color in Peach." HortScience 40, no. 3 (2005): 523–24. http://dx.doi.org/10.21273/hortsci.40.3.523.
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Recently observed hybrid populations of peach [Prunus persica (L.) Batsch] provide evidence for the presence of a single gene suppressing red skin color. The fruit of seedling populations of FL90-48C and FL90-37C × FL84-18C, FL90-50CN × FL92-2C, FL90-48C × FL91-12, FL91-8 × FL88-6, and open-pollinated or selfed populations from unselected seedlings of `Contender' × PI65977 (`Giallo di Padova') and `Mexico Selection' × `Oro A' were rated for normal quantitative vs. no anthocyanin skin color at maturity. At this stage of development, anthocyaninless phenotypes displayed no red color over the entire surface of the fruit. Instead they were characterized by a bright yellow ground color that stood out visually in the seedling rows, and which was dubbed highlighter. The two crosses with FL84-18C yielded populations that approximated a 1:1 segregation ratio for quantitative red:no red skin color. All other crosses produced populations that closely approximated a 3:1 segregation ratio for quantitative red to no red. These data are consistent with the hypothesis that the highlighter phenotype is a single gene recessive trait. We propose the gene symbols of h and H for the recessive no red (highlighter) and dominant normal quantitative red (wild-type) alleles, respectively.
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Chen, Yajun, Zhangnan Wu, Bo Zhao, Caixia Fan, and Shuwei Shi. "Weed and Corn Seedling Detection in Field Based on Multi Feature Fusion and Support Vector Machine." Sensors 21, no. 1 (2020): 212. http://dx.doi.org/10.3390/s21010212.
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Detection of weeds and crops is the key step for precision spraying using the spraying herbicide robot and precise fertilization for the agriculture machine in the field. On the basis of k-mean clustering image segmentation using color information and connected region analysis, a method combining multi feature fusion and support vector machine (SVM) was proposed to identify and detect the position of corn seedlings and weeds, to reduce the harm of weeds on corn growth, and to achieve accurate fertilization, thereby realizing precise weeding or fertilizing. First, the image dataset for weed and corn seedling classification in the corn seedling stage was established. Second, many different features of corn seedlings and weeds were extracted, and dimensionality was reduced by principal component analysis, including the histogram of oriented gradient feature, rotation invariant local binary pattern (LBP) feature, Hu invariant moment feature, Gabor feature, gray level co-occurrence matrix, and gray level-gradient co-occurrence matrix. Then, the classifier training based on SVM was conducted to obtain the recognition model for corn seedlings and weeds. The comprehensive recognition performance of single feature or different fusion strategies for six features is compared and analyzed, and the optimal feature fusion strategy is obtained. Finally, by utilizing the actual corn seedling field images, the proposed weed and corn seedling detection method effect was tested. LAB color space and K-means clustering were used to achieve image segmentation. Connected component analysis was adopted to remove small objects. The previously trained recognition model was utilized to identify and label each connected region to identify and detect weeds and corn seedlings. The experimental results showed that the fusion feature combination of rotation invariant LBP feature and gray level-gradient co-occurrence matrix based on SVM classifier obtained the highest classification accuracy and accurately detected all kinds of weeds and corn seedlings. It provided information on weed and crop positions to the spraying herbicide robot for accurate spraying or to the precise fertilization machine for accurate fertilizing.
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Prato, Andrés I., L. Felipe Daibes, Miguel A. Pabón, Alvaro A. Castaño, Carolina Santos-Heredia, and Claudimar S. Fior. "Seedling Emergence of the Tree Legume Clathrotropis brunnea Amshoff, Endemic from a Colombian Tropical Rainforest." Forest Science 67, no. 4 (2021): 457–67. http://dx.doi.org/10.1093/forsci/fxab013.
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Abstract Seedling emergence is the main propagation method of forest species. Thus, we aimed to evaluate emergence aspects of the tree legume Clathrotropis brunnea Amshoff (sapán or blackheart sapán), a Fabaceae of high economic value endemic to the Colombian rainforest. We characterized the biometry of legumes and seeds and assessed seedling emergence in three experiments: (1) effect of fruit color and substrate, (2) seed conservation in storage, and (3) presoaking and seed position. Our results showed that seeds of green-yellow fruits have greater length and weight and a water content of up to 53%. Seedling emergence did not differ between green-yellow and dark-brown fruits but did differ with substrate type; nearly 80% of seedlings emerged in the sand substrate (S1), but only 62% emerged in the mixed substrate (S3). Fresh sapán seeds are nondormant, showing a recalcitrant behavior in which seedling emergence decreased after storage in all tested conditions. Both seed-sowing positions allowed an emergence of >80% with a small benefit of the hilum downward, regardless of presoaking treatments. However, these differences did not affect seedling height or biomass after emergence. Our results provide basic knowledge on production of tropical seedlings, seeking species conservation, and use in restoration projects.
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Mavi, K. "The relationship between seed coat color and seed quality in watermelon Crimson sweet." Horticultural Science 37, No. 2 (2010): 62–69. http://dx.doi.org/10.17221/53/2009-hortsci.
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This work was carried out to determine the relationship between seed coat color and seed quality in Crimson sweet watermelon. Seed lots (1, 2, 3, and 4) were prepared taking into consideration seed coat colors in fresh seeds with naked eye. The color parameters of these prepared seed lots were determined using Minolta colorimeter. To determine quality differences between the seed lots, standard germination test, seed weight, water uptake ratio, mean germination time, emergence percentage, mean emergence time, seedling fresh weight, seedling dry weight and electrical conductivity values were determined. The seed weight (57.22 mg), germination percentage (86.5%), emergence percentage (77.5% total and 76.5% normal), seedling fresh weight (978.7 mg), and dry weight (64.7 mg) of the brown seed lot (Lot 1) were markedly higher than lots having lighter seed coat (2, 3, and 4). On the other hand the mean emergence time (7.7 days) and electrical conductivity value (128.8 μS/cm g in 24 h) of the brown seed lot (Lot 1) were lower than lots having lighter seed coat (2, 3, and 4). The obtained data indicated that seed quality differences can be determined according to the seed coat color of Crimson sweet seeds. It was found that seed lot 1 had higher seed vigor and viability than seed lots 2, 3, and 4. Color parameters b*, C*, L*, and H°, determined by Minolta colorimeter, showed significant correlation with seeds quality parameters.
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Shaw, Douglas V. "Genetic Variation for Objective and Subjective Measures of Fresh Fruit Color in Strawberries." Journal of the American Society for Horticultural Science 116, no. 5 (1991): 894–98. http://dx.doi.org/10.21273/jashs.116.5.894.
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The heritabilities of, and genetic correlations among, variables that describe internal and external color in fresh strawberry (Fragaria × anarrassa) fruit were estimated using factorial analyses of seedlings from 20 controlled crosses. Hunter L and a values, and a subjective score generated by comparison with color plates were obtained for seedling genotypes and their parents at two locations. Genetic effects were responsible for 33% to 61% of the phenotypic variance for color traits, after correction for location effects. Means for objective color variables differed significantly between locations, but means for subjective color scores did not. Genetic × location interaction variances were usually nonsignificant, and were < 12% of the phenotypic variance for all variables. Phenotypic and genetic correlations between objective and subjective color scores were significant and large (absolute values of r = 0.42-0.69; rg = 0.84-1.00). Multiple regression of subjective scores on L and a explained 69% and 59% of the phenotypic variation for external and internal color, respectively. Genetic correlations between measures of internal and external color were small and mostly nonsignificant, suggesting that separate sets of genes condition these traits.
Dissertations / Theses on the topic "Seedling color"
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Heer, Richard C. "Estimation of seedling density and evaluation of woody competition in young loblolly pine plantations using 35mm color aerial photography." Thesis, Virginia Polytechnic Institute and State University, 1986. http://hdl.handle.net/10919/94464.
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The potential for using large scale, small format aerial photography to obtain seedling density and woody competition information was investigated. Factors affecting photo interpretation of seedlings were examined and equations to predict seedling density and woody competition levels were developed and evaluated. Two scales of imagery, 1:4000 and 1:6000 were considered to compare their relative merits for these purposes.
Greater age of the seedlings and their inherent development generally served to improve photo interpretation. The amount of woody competition present in the plots tended to hinder seedling identification at the 1:4000 scale, while enhancing it when 1:6000 scale data was used. Seedling density estimation and evaluation of competition through Free-To-Grow classification predictions yielded results comparable to ground surveys. Estimation of total groundline basal area in all woody competition, and classification of the plots by the amount of hard-to-control competition they contained, were less successful. These results may have been due in part to the partial leaf fall that occurred prior to obtaining the imagery. Many of the results found in this study favored the larger scale (1:4000) imagery, and its use for the procedures described is recommended.<br>M.S.
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Zabot, Lucio. "Caracterização agronômica de cultivares transgênicas de soja cultivadas no Rio Grande do Sul." Universidade Federal de Santa Maria, 2009. http://repositorio.ufsm.br/handle/1/3186.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior<br>Aiming to characterize the main transgenic soybeans cultivars used in Rio Grande do Sul, experiments were conducted during the 2007/2008 season, in Santa Maria/RS. In the field, the cultivars Relmo Anta RR 82, A 6001 RG, A 8000 RG, FUNDACEP 53 RR, FUNDACEP 54 RR, FUNDACEP 56 RR, BRS 244 RR, and CD 214 RR CD 219 RR, drilled at seeds rates of 250, 400 and 550 thousand seed ha-1 and at row spacing of 0.30, 0.45 and 0.60m. The variables were: grain yield, yield components, distribution of income in different strata of the plant, morphological characteristics, rate of soil covering and amount of light incident on the canopy. The experimental design was a
randomized blocks, with 4 repetitions in trifatorial outline (9 cultivars x 3 seed rates x 3 row spacing).
In laboratory, tests of peroxidase reaction had been carried through only using the tegument of the
seeds or the entire seeds and also seedling color for 50 soybean cultivars. For the grain yield cultivars CD 214 RR and FUNDACEP 53 RR had the best results (3589 and 3530 kg ha-1, respectively). For the distribution of income in the plant strata, there is interaction between density of
planting and row spacing, which indicate the trends for each cultivar. For the amount of light incident
on the canopy, the interactions between the factors of planting density, row spacing, timing of the cycle of development and level of the canopy, combined with the architecture of each cultivar define the amount of light intercepted, after flowering. The morphological response of each cultivar is different for every situation tested, indicating the need for understanding the behavior of each material, to select the practices to maximize the yield. The use of the test of reaction of peroxidase used the
entire seed can be used of so efficient form how much the traditionally used method (tegument). The identification of the seedling color may be an early way to identify varietal blend.<br>Com o objetivo de caracterizar as principais cultivares transgênicas de soja utilizadas no Rio Grande do Sul, foram realizados experimentos durante a safra agrícola 2007/2008, em Santa Maria/RS. Em campo, as cultivares Relmo Anta 82 RR, A 6001 RG, A 8000 RG, FUNDACEP 53 RR, FUNDACEP 54
RR, FUNDACEP 56 RR, BRS 244 RR, CD 214 RR e CD 219 RR foram submetidas às densidade de semeadura de 250, 400 e 550 mil semente ha-1 e aos espaçamentos entre linhas de 0,30, 0,45 e 0,60m. As variáveis avaliadas foram: rendimento de grãos, componentes do rendimento, distribuição do rendimento em diferentes estratos da planta, características morfológicas, taxa de cobertura do solo e quantidade de luz incidente no dossel. O delineamento experimental utilizado foi o de blocos ao acaso, com 4 repetições, no esquema trifatorial (9 cultivares x 3 densidades de semeadura x 3
espaçamentos entre linhas). Em laboratório, foram realizados testes de reação da peroxidase utilizando somente o tegumento das sementes ou as sementes inteiras e também coloração do hipocótilo para 50 cultivares de soja. Para o rendimento de grãos as cultivares CD 214 RR e FUNDACEP 53 RR apresentaram os melhores resultados (3589 e 3530 kg ha-1, respectivamente). Para a distribuição do rendimento nos estratos da planta, existe interação entre densidade de
semeadura e espaçamento entre linhas, os quais indicam as tendências para cada cultivar. Para a quantidade de luz incidente no dossel, as interações entre os fatores densidade de semeadura, espaçamento entre linhas, época do ciclo de desenvolvimento e nível do dossel, aliados à arquitetura
de cada cultivar definem a quantidade de luz interceptada, após o florescimento. A resposta morfológica de cada cultivar é diferenciada para todas as situações testadas, indicando a
necessidade do conhecimento do comportamento de cada material, para a escolha das práticas que visem maximizar o rendimento de grãos. O uso do teste de reação da peroxidase utilizando a semente inteira pode ser utilizado de forma tão eficiente quanto o método tradicionalmente utilizado
(tegumento). A identificação da coloração do hipocótilo pode ser uma forma precoce de identificar mistura varietal.
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Perissini, Ivan Carlos. "Análise experimental de algoritmos de constância de cor e segmentação para detecção de mudas de plantas." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/18/18149/tde-25052018-095947/.
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O uso da visão computacional vem ganhando espaço no contexto agrícola, especialmente com a evolução do conceito da agricultura de precisão. Aplicações como irrigação, fertilização e controle de pragas são apenas alguns dos cenários que essa tecnologia pode atender. Entretanto, a demanda por sistemas acessíveis e eficientes aliada às inconstâncias e ruídos visuais de um ambiente externo, apresentam desafios a estes processos. Foi proposto neste trabalho uma análise da literatura e uma série de investidas experimentais de técnicas de processamento de imagens, para buscar melhores relações entre custo computacional e desempenho da detecção de mudas de plantas, visando atingir operações em tempo real com o uso de hardwares comuns e de baixo custo. Para tanto o trabalho investiga a composição de estratégias de segmentação a partir de diferentes espaços de cor e métodos de constância de cor, de forma a reduzir a variação luminosa, uma das maiores fontes de instabilidade nas aplicações de visão na agricultura. Os experimentos propostos foram divididos em duas fases; na primeira o sistema de medidas foi avaliado, definindo as métricas e condições experimentais adequadas para a segunda fase, composta de uma sequência de experimentos comparativos entre estratégias de segmentação sob diferentes condições de iluminação. Os resultados mostraram que as soluções são muito dependentes das condições da cena e uma série de alternativas promissoras de segmentação foram obtidas. Sua elegibilidade, porém, depende de considerações sobre a disponibilidade computacional e contexto de aplicação.<br>The use of computer vision has been gaining ground in the agricultural context, especially with the evolution of the concept of precision agriculture. Applications such as irrigation, fertilization and pest control are just some of the scenarios that this technology can be used. However, the demand for accessible and efficient systems together with the variations and visual noise from an external environment presents challenges to these processes. It was proposed in this study an analysis of the literature and a series of experimental investigations of image processing techniques, to search for better relations between computational cost and performance in the detection of seedlings, aiming to achieve real time operations with the use of common and low cost hardware. For this, the work investigates the composition of segmentation strategies from different color spaces and color constancy methods, in order to combat light variation, one of the major sources of instability in agricultural vision applications. The proposed experiments were divided into two phases; in the first the measurement system was evaluated, defining the metrics and suitable conditions for the experiments at second phase, composed of a sequence of comparative experiments of segmentation strategies under different lighting conditions. The results showed that the solutions are very dependent on the conditions of the scene and a series of promising segmentation alternatives were obtained. Their eligibility, however, depends on considerations about the computational availability and context of the application.
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ming, Chang jeng, and 張仁明. "Segmentation and Feature Extraction of Color Seedling Images under Natural Lighting." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/94347527219569977726.
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碩士<br>國立臺灣大學<br>農業機械工程學系研究所<br>87<br>The measurement of plant growth is helpful in understanding the interaction between plant growth and environmental factors. Therefore, we developed an intelligent machine vision system to determine seedling morphological characteristics non-destructively in this research. The image segmentation of seedling from background natural lighting was discussed and an operating algorithms to measure seedling morphological characteristics was developed. Preliminary information was obtained from the top view image and side view images of the seedling. Seedling characteristics such as leaf number and leaf angle on the top view image were first determined. According to these characteristics, the side view images were acquired by rotating the rotary stage to specified angles for later analysis. From the side view images, other seedling characteristics, including seedling height, span, projection area and total leaf area were then determined by calculation and calibration. For seedling within 6 leaves, the error of leaf number was within 1 leaf, and for seedling within 5 leaves, the accuracy of leaf area was 92%. The measured data can be further processed for 3D reconstruction of graphical display of the measured seedling.
Books on the topic "Seedling color"
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Peter Rabbit's Colors: A Peter Rabbit Seedlings Book (Peter Rabbit Seedlings). Warne, 2003.
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Williams, Joan, and J. Morrison. ADAS Colour Atlas of Weed Seedlings. Manson Publishing Ltd, 1987.
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Potter, Beatrix. Peter Rabbit's Rainbow Shapes & Colors (Peter Rabbit Seedlings). Warne, 2006.
Find full textBook chapters on the topic "Seedling color"
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Mitra, Sisir. "Cultivars and plant improvement." In Guava: botany, production and uses. CABI, 2021. http://dx.doi.org/10.1079/9781789247022.0006.
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Abstract The major objectives of guava breeding are aimed at improving both plant and fruit characteristics such as to develop high-yielding, high-quality dwarf cultivars with fruits of uniform shape, good size, attractive skin and pulp colour, fewer and/or soft seeds, resistant to wilt, nematodes and long storage life. Selection of superior seedlings has resulted in the development of a number of cultivars in different countries. This chapter describes the Psidium species used in breeding (Psidium cattleyanum, P. guineense, P. acutangulum, P. friedrichsthalianum, P. angulatum and P. littorale), objectives of breeding programmes, introduction and selection, inheritance pattern, interspecific hybridization, polyploidy, mutation and molecular characterization. Guava cultivars growing in different countries (Brazil, China, Egypt, India, Israel, Malaysia, Mexico, Pakistan, South Africa, Taiwan, Thailand, USA and vietnam) are also described.
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Williams, John B., John R. Morrison, and Cathy Wood. "Introduction." In A Colour Atlas of Weed Seedlings. CRC Press, 2020. http://dx.doi.org/10.1201/9780429069871-1.
Full textConference papers on the topic "Seedling color"
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Franze, Guilherme Pereira Jorge, Emanuel Rocha Woiski, and Luiz Carlos Sandoval Goes. "HSV and NDVI Color Space Analysis and Sampling Procedure for Counting of Seedlings in Eucalyptus spp Plantations from High Definition Aerial Images." In 2017 International Conference on Computational Science and Computational Intelligence (CSCI). IEEE, 2017. http://dx.doi.org/10.1109/csci.2017.77.
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