Mother–young cohabitation in Phronimella elongata and Phronima spp. (Amphipoda, Hyperiidea, Phronimidae)

2013 ◽  
Vol 93 (6) ◽  
pp. 1553-1556 ◽  
Author(s):  
Masakazu N. Aoki ◽  
Chie Matsumoto-Ohshima ◽  
Euichi Hirose ◽  
Jun Nishikawa
Keyword(s):  
Growth Stage ◽  
Gelatinous Zooplankton ◽  
Growth Stages ◽  
Single Female ◽  
Reproductive Characteristics

Reproductive characteristics of poorly studied hyperiid amphipods, especially Phronimella elongata, are described. Among nine species of hand-collected phronimids, females of Phronimella elongata, Phronima dunbari and Phronima sedentaria cohabited with their young in a ‘barrel' derived from gelatinous zooplankton. Five growth stages of young were identified in Phronimella elongata: young of stages I–IV were found with the mother in the barrel, but stage-V young clinged to the mother retaining no barrel. The cohabiting young in Phronimella elongata and Phronima sedentaria always consisted of single growth stage. In a single female of Phronima dunbari, however, two different stages of young coexisted in a barrel. In Phronimella elongata, the mother size significantly correlated with the number of brooded eggs or cohabiting young regardless of growth stages of young. Considerable variation in the number of eggs or young per female among phronimid species may attribute to the differences in the volumes of the brood pouches.

scholarly journals Growth Stages Classification of Potato Crop Based on Analysis of Spectral Response and Variables Optimization

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 3995 ◽  
Author(s):  
Ning Liu ◽  
Ruomei Zhao ◽  
Lang Qiao ◽  
Yao Zhang ◽  
Minzan Li ◽  
...  
Keyword(s):  
Growth Stage ◽  
Spectral Response ◽  
Classification Model ◽  
Growth Stages ◽  
Potato Field ◽  
Spectral Bands ◽  
Svm Model ◽  
Selection Algorithms ◽  
Potato Crops

Potato is the world’s fourth-largest food crop, following rice, wheat, and maize. Unlike other crops, it is a typical root crop with a special growth cycle pattern and underground tubers, which makes it harder to track the progress of potatoes and to provide automated crop management. The classification of growth stages has great significance for right time management in the potato field. This paper aims to study how to classify the growth stage of potato crops accurately on the basis of spectroscopy technology. To develop a classification model that monitors the growth stage of potato crops, the field experiments were conducted at the tillering stage (S1), tuber formation stage (S2), tuber bulking stage (S3), and tuber maturation stage (S4), respectively. After spectral data pre-processing, the dynamic changes in chlorophyll content and spectral response during growth were analyzed. A classification model was then established using the support vector machine (SVM) algorithm based on spectral bands and the wavelet coefficients obtained from the continuous wavelet transform (CWT) of reflectance spectra. The spectral variables, which include sensitive spectral bands and feature wavelet coefficients, were optimized using three selection algorithms to improve the classification performance of the model. The selection algorithms include correlation analysis (CA), the successive projection algorithm (SPA), and the random frog (RF) algorithm. The model results were used to compare the performance of various methods. The CWT-SPA-SVM model exhibited excellent performance. The classification accuracies on the training set (Atrain) and the test set (Atest) were respectively 100% and 97.37%, demonstrating the good classification capability of the model. The difference between the Atrain and accuracy of cross-validation (Acv) was 1%, which showed that the model has good stability. Therefore, the CWT-SPA-SVM model can be used to classify the growth stages of potato crops accurately. This study provides an important support method for the classification of growth stages in the potato field.

scholarly journals Effect of Herbicides on the Management of the Invasive Weed Solanum rostratum Dunal (Solanaceae)

Plants ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 284
Author(s):  
Jackline Abu-Nassar ◽  
Maor Matzrafi
Keyword(s):  
Growth Stage ◽  
Late Summer ◽  
Early Spring ◽  
Growth Stages ◽  
Weed Species ◽  
Invasive Weed ◽  
Solanum Rostratum ◽  
Stage 4 ◽  
Chemical Solutions ◽  
Late Growth

Solanum rostratum Dunal is an invasive weed species that invaded Israel in the 1950s. The weed appears in several germination flashes, from early spring until late summer. Recently, an increase in its distribution range was observed, alongside the identification of new populations in the northern part of Israel. This study aimed to investigate the efficacy of herbicide application for the control of S. rostratum using two field populations originated from the Golan Heights and the Jezreel Valley. While minor differences in herbicide efficacy were recorded between populations, plant growth stage had a significant effect on herbicide response. Carfentrazone-ethyl was found to be highly effective in controlling plants at both early and late growth stages. Metribuzin, oxadiazon, oxyfluorfen and tembutrione showed reduced efficacy when applied at later growth stage (8–9 cm height), as compared to the application at an early growth stage (4–5 cm height). Tank mixes of oxadiazon and oxyfluorfen with different concentrations of surfactant improved later growth stage plant control. Taken together, our study highlights several herbicides that can improve weed control and may be used as chemical solutions alongside diversified crop rotation options. Thus, they may aid in preventing the spread and further buildup of S. rostratum field populations.

scholarly journals Effect of Growth Stage on Susceptibility of Grape Berry and Rachis Tissues to Infection by Phomopsis viticola

Plant Disease ◽  
2001 ◽  
Vol 85 (5) ◽  
pp. 517-520 ◽  
Author(s):  
O. Erincik ◽  
L. V. Madden ◽  
D. C. Ferree ◽  
M. A. Ellis
Keyword(s):  
Growth Stage ◽  
Grape Berry ◽  
Growth Stages ◽  
Phomopsis Viticola ◽  
Over Time

Intact ‘Seyval’ grape clusters in the greenhouse and ‘Catawba’ clusters in the field were inoculated with conidia of Phomopsis viticola at seven Eichorn-Lorenz growth stages between 12 (prebloom) and 35 (véraison) in 1998. Five pots (10 clusters) were used per inoculation, and the experiment was repeated three times. Also, 10 to 20 randomly selected Catawba clusters were inoculated in the field for each of three replications at each growth stage. Studies were repeated in 1999. In addition, Chambourcin clusters were also inoculated at four growth stages in the greenhouse in 1999. Results obtained in the greenhouse and field during both years and for all cultivars indicate that berry and rachis infections can occur at all growth stages between 12 and 35 with no evidence of decreasing susceptibility over time. Results disagree with some literature reports that indicate that berry infection occurs primarily during bloom and shortly after bloom, and susceptibility decreases as fruit matures.

scholarly journals Hormesis with glyphosate depends on coffee growth stage

2013 ◽  
Vol 85 (2) ◽  
pp. 813-822 ◽  
Author(s):  
LEONARDO B. DE CARVALHO ◽  
PEDRO L.C.A. ALVES ◽  
STEPHEN O. DUKE
Keyword(s):  
Plant Growth ◽  
Weed Management ◽  
Growth Stage ◽  
Growth Stages ◽  
Coffee Plant ◽  
Herbicide Application ◽  
Coffee Plantations ◽  
Plant Growth Stages ◽  
Coffee Plants ◽  
Almost All

Weed management systems in almost all Brazilian coffee plantations allow herbicide spray to drift on crop plants. In order to evaluate if there is any effect of the most commonly used herbicide in coffee production, glyphosate, on coffee plants, a range of glyphosate doses were applied directly on coffee plants at two distinct plant growth stages. Although growth of both young and old plants was reduced at higher glyphosate doses, low doses caused no effects on growth characteristics of young plants and stimulated growth of older plants. Therefore, hormesis with glyphosate is dependent on coffee plant growth stage at the time of herbicide application.

Dwarf sunflower response to row spacing, stand reduction, and defoliation at different growth stages

2003 ◽  
Vol 83 (2) ◽  
pp. 319-326 ◽  
Author(s):  
B. L. Johnson
Keyword(s):  
Helianthus Annuus ◽  
Oil Content ◽  
Growth Stage ◽  
Total Yield ◽  
Reciprocal Relationship ◽  
Yield Response ◽  
Yield Reduction ◽  
Row Spacing ◽  
Growth Stages ◽  
Helianthus Annuus L

Growth compensation of dwarf sunflower (Helianthus annuus L.) hybrids to low initial stands, later stand losses, or plant defoliation has not been reported regarding replanting decisions and crop insurance yield loss assessment. Three experiments were conducted to study the affect of stand reduction, defoliation, and row spacing on dwarf sunflower yield and quality when grown in eastern North Dakota. Experiment 1 evaluated stand reduction (0, 25, 50 and 75%) applied at growth stages (V4, R1 and R6) in 15, 45 and 76 cm spaced rows. Row spacing interactions with stand reduction and growth stage were not significant for yield indicating growth stage and stand reduction effects on yield response were independent of row spacing. In exp. 2, significant growth stage (V4, V8, R1, R2, R3, R5 and R6) by stand reduction (0, 12, 25, 37, 50, 62 and 75%) interaction showed stand reduction at vegetative growth stages not influencing yield, but as maturity progressed yield reductions became greater with increased stand reduction. Achene weight increased with increasing stand reduction at vegetative and early reproductive stages. A reciprocal relationship was noted between achene weight and achene oil content where oil content decreased as achene weight increased. Interaction of growth stage (R1 and R6) and defoliation (0, 25, 50, 75 and 100%) in exp. 3 indicated greater reduction in yield, test weight, 1000-achene weight, and achene oil conte nt as defoliatin increased at growth stage R6. Yield compensating ability of dwarf sunflower is dependent on type and level of damage and growth stage of occurrence, with total yield reduction considering all effects. Key words: Sunflower, Helianthus annuus L., row spacing, stand reduction, defoliation

scholarly journals Lettuce growth stage identification based on phytomorphological variations using coupled color superpixels and multifold watershed transformation

2020 ◽  
Vol 6 (3) ◽  
pp. 261
Author(s):  
Ronnie Sabino Concepcion II ◽  
Jonnel Dorado Alejandrino ◽  
Sandy Cruz Lauguico ◽  
Rogelio Ruzcko Tobias ◽  
Edwin Sybingco ◽  
...  
Keyword(s):  
Machine Learning ◽  
Growth Stage ◽  
Growth Stages ◽  
Learning Models ◽  
Lettuce Plant ◽  
Watershed Transformation ◽  
Head Development ◽  
Area And Perimeter ◽  
Lettuce Growth ◽  
Machine Learning Models

Identifying the plant's developmental growth stages from seed leaf is crucial to understand plant science and cultivation management deeply. An efficient vision-based system for plant growth monitoring entails optimum segmentation and classification algorithms. This study presents coupled color-based superpixels and multifold watershed transformation in segmenting lettuce plant from complicated background taken from smart farm aquaponic system, and machine learning models used to classify lettuce plant growth as vegetative, head development and for harvest based on phytomorphological profile. Morphological computations were employed by feature extraction of the number of leaves, biomass area and perimeter, convex area, convex hull area and perimeter, major and minor axis lengths of the major axis length the dominant leaf, and length of plant skeleton. Phytomorphological variations of biomass compactness, convexity, solidity, plant skeleton, and perimeter ratio were included as inputs of the classification network. The extracted Lab color space information from the training image set undergoes superpixels overlaying with 1,000 superpixel regions employing K-means clustering on each pixel class. Six-level watershed transformation with distance transformation and minima imposition was employed to segment the lettuce plant from other pixel objects. The accuracy of correctly classifying the vegetative, head development, and harvest growth stages are 88.89%, 86.67%, and 79.63%, respectively. The experiment shows that the test accuracy rates of machine learning models were recorded as 60% for LDA, 85% for ANN, and 88.33% for QSVM. Comparative analysis showed that QSVM bested the performance of optimized LDA and ANN in classifying lettuce growth stages. This research developed a seamless model in segmenting vegetation pixels, and predicting lettuce growth stage is essential for plant computational phenotyping and agricultural practice optimization.

scholarly journals Scale-Dependent Effects of Growth Stage and Elevational Gradient on Rice Phyllosphere Bacterial and Fungal Microbial Patterns in the Terrace Field

2022 ◽  
Vol 12 ◽  
Author(s):  
Pei Wang ◽  
Jianping Dai ◽  
Luyun Luo ◽  
Yong Liu ◽  
Decai Jin ◽  
...  
Keyword(s):  
Plant Growth ◽  
Growth Stage ◽  
Elevational Gradient ◽  
Fungal Communities ◽  
Growth Stages ◽  
Strong Positive Correlation ◽  
Elevation Gradients ◽  
Positive Correlation ◽  
Α Diversity ◽  
Phyllosphere Bacteria

The variation of phyllosphere bacterial and fungal communities along elevation gradients may provide a potential link with temperature, which corresponds to an elevation over short geographic distances. At the same time, the plant growth stage is also an important factor affecting phyllosphere microorganisms. Understanding microbiological diversity over changes in elevation and among plant growth stages is important for developing crop growth ecological theories. Thus, we investigated variations in the composition of the rice phyllosphere bacterial and fungal communities at five sites along an elevation gradient from 580 to 980 m above sea level (asl) in the Ziquejie Mountain at the seedling, heading, and mature stages, using high-throughput Illumina sequencing methods. The results revealed that the dominant bacterial phyla were Proteobacteria, Actinobacteria, and Bacteroidetes, and the dominant fungal phyla were Ascomycota and Basidiomycota, which varied significantly at different elevation sites and growth stages. Elevation had a greater effect on the α diversity of phyllosphere bacteria than on that phyllosphere fungi. Meanwhile, the growth stage had a great effect on the α diversity of both phyllosphere bacteria and fungi. Our results also showed that the composition of bacterial and fungal communities varied significantly along elevation within the different growth stages, in terms of both changes in the relative abundance of species, and that the variations in bacterial and fungal composition were well correlated with variations in the average elevation. A total of 18 bacterial and 24 fungal genera were significantly correlated with elevational gradient, displaying large differences at the various growth stages. Soluble protein (SP) shared a strong positive correlation with bacterial and fungal communities (p < 0.05) and had a strong significant negative correlation with Serratia, Passalora, unclassified_Trichosphaeriales, and antioxidant enzymes (R > 0.5, p < 0.05), and significant positive correlation with the fungal genera Xylaria, Gibberella, and Penicillium (R > 0.5, p < 0.05). Therefore, it suggests that elevation and growth stage might alter both the diversity and abundance of phyllosphere bacterial and fungal populations.

scholarly journals TIME SERIES ANALYSIS OF REMOTE SENSING OBSERVATIONS FOR CITRUS CROP GROWTH STAGE AND EVAPOTRANSPIRATION ESTIMATION

2016 ◽  
Vol XLI-B8 ◽  
pp. 1037-1042 ◽  
Author(s):  
S. A. Sawant ◽  
M. Chakraborty ◽  
S. Suradhaniwar ◽  
J. Adinarayana ◽  
S. S. Durbha
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Growth Stage ◽  
Crop Growth ◽  
Water Requirement ◽  
Growth Stages ◽  
Crop Water ◽  
Horticultural Crops ◽  
Crop Growth Stages ◽  
Crop Growth Stage

Satellite based earth observation (EO) platforms have proved capability to spatio-temporally monitor changes on the earth's surface. Long term satellite missions have provided huge repository of optical remote sensing datasets, and United States Geological Survey (USGS) Landsat program is one of the oldest sources of optical EO datasets. This historical and near real time EO archive is a rich source of information to understand the seasonal changes in the horticultural crops. Citrus (Mandarin / Nagpur Orange) is one of the major horticultural crops cultivated in central India. Erratic behaviour of rainfall and dependency on groundwater for irrigation has wide impact on the citrus crop yield. Also, wide variations are reported in temperature and relative humidity causing early fruit onset and increase in crop water requirement. Therefore, there is need to study the crop growth stages and crop evapotranspiration at spatio-temporal scale for managing the scarce resources. In this study, an attempt has been made to understand the citrus crop growth stages using Normalized Difference Time Series (NDVI) time series data obtained from Landsat archives (<a href="http://earthexplorer.usgs.gov/"target="_blank">http://earthexplorer.usgs.gov/</a>). Total 388 Landsat 4, 5, 7 and 8 scenes (from year 1990 to Aug. 2015) for Worldwide Reference System (WRS) 2, path 145 and row 45 were selected to understand seasonal variations in citrus crop growth. Considering Landsat 30 meter spatial resolution to obtain homogeneous pixels with crop cover orchards larger than 2 hectare area was selected. To consider change in wavelength bandwidth (radiometric resolution) with Landsat sensors (i.e. 4, 5, 7 and 8) NDVI has been selected to obtain continuous sensor independent time series. The obtained crop growth stage information has been used to estimate citrus basal crop coefficient information (Kcb). Satellite based Kcb estimates were used with proximal agrometeorological sensing system observed relevant weather parameters for crop ET estimation. The results show that time series EO based crop growth stage estimates provide better information about geographically separated citrus orchards. Attempts are being made to estimate regional variations in citrus crop water requirement for effective irrigation planning. In future high resolution Sentinel 2 observations from European Space Agency (ESA) will be used to fill the time gaps and to get better understanding about citrus crop canopy parameters.

scholarly journals Is what you see what you get? The relationship between field observed and actual aphid parasitism rates in canola crops

2021 ◽  
Author(s):  
Samantha Ward ◽  
Paul A. Umina ◽  
Hazel Parry ◽  
Amber Balfour-Cunningham ◽  
Xuan Cheng ◽  
...  
Keyword(s):  
Growth Stage ◽  
Green Peach Aphid ◽  
South Australia ◽  
Field Work ◽  
Crop Growth ◽  
Diaeretiella Rapae ◽  
Growth Stages ◽  
Parasitoid Species ◽  
Parasitism Rates ◽  
Crop Growth Stage

AbstractBACKGROUNDEstimating parasitoid abundance in the field can be difficult, even more so when attempting to quantify parasitism rates and the ecosystem service of biological control that parasitoids can provide. To understand how ‘observed’ parasitism rates (in-field mummy counts) of the green peach aphid, Myzus persicae (Sulzer) (Homoptera: Aphididae) translate to ‘actual’ parasitism rates (laboratory-reared parasitoid counts), field work was undertaken in Australian canola fields over a growing season. Parasitoids were reared within a controlled laboratory setting.RESULTSTotal observed and actual parasitism rates of M. persicae varied considerably across regions, but less so on a field level. Overall, actual parasitism was on average 2.4 times higher than that observed in the field, with rates an average of 4-fold higher in South Australia. As crop growth stage progressed, the percentage of mummies observed increased. Percentage of parasitoids reared also increased with crop growth stage, averaging 3.4% during flowering and reaching 14.4% during podding/senescing. Although there was a greater diversity of reared parasitoid species at later crop growth stages, actual parasitism rate was unaffected by parasitoid species. Diaeretiella rapae was the most commonly reared parasitoid, increasing in abundance with crop growth stage.CONCLUSIONThese findings indicate that mummy counts alone do not provide a clear representation of parasitism within fields.

Tightening the Life-Cycle Construct: A Taxonomic Study of Growth Stage Configurations in High-Technology Organizations

1994 ◽  
Vol 18 (2) ◽  
pp. 5-29 ◽  
Author(s):  
Steven H. Hanks ◽  
Collin J. Watson ◽  
Erik Jansen ◽  
Gaylen N. Chandler
Keyword(s):  
Cluster Analysis ◽  
Life Cycle ◽  
Growth Stage ◽  
High Technology ◽  
Life Cycle Stage ◽  
Growth Stages ◽  
Taxonomic Study ◽  
Organization Context ◽  
Organization Life Cycle

Over the years much has been written about the organization life cycle, yet there has been remarkably little attention given to the underlying construct of a life-cycle stage. It is proposed in this study that each life-cycle stage consists of a unique configuration of variables related to organization context and structure. Cluster analysis is used to derive a taxonomy of growth stage configurations in a sample of 126 high-technology organizations. The derived configurations suggest a sequence of four growth stages.

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