scholarly journals Dihydroisocoumarin Content and Phenotyping of Hydrangea macrophylla subsp. serrata Cultivars under Different Shading Regimes

Agronomy ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 1743
Author(s):  
Marcel Dieter Moll ◽  
Alena Sophia Vieregge ◽  
Charis Wiesbaum ◽  
Maria Blings ◽  
Frederik Vana ◽  
...  
Keyword(s):  
Growth Factor ◽  
Dry Matter ◽  
Vegetation Indices ◽  
Ornamental Plants ◽  
Ornamental Plant ◽  
Total Biomass ◽  
Light Conditions ◽  
Active Radiation ◽  
Growing Seasons ◽  
Hydrangea Macrophylla

Hortensias (Hydrangea macrophylla L.) are well known as ornamental plants with their impressive flowers. Besides being an ornamental plant, some hortensia species contain constituents of nutritional and pharmaceutical interest. In this context, H. macrophylla subsp. serrata contains dihydroisocoumarins (DHCs), in particular hydrangenol (HG) and phyllodulcin (PD), which determine produce quality. For the successful cultivation of H. macrophylla subsp. serrata, shading may be required. The response of H. macrophylla subsp. serrata as a source for DHCs was investigated in two growing seasons using three different cultivars (‘Amagi Amacha’, ‘Oamacha’ and ‘Odoriko Amacha’) under three different light conditions: no shade (100% photosynthetic active radiation, PAR), partial (72% PAR) and full shading (36% PAR). The shading regimes had no significant effect on dihydroisocoumarin content in leaf dry matter in each single cultivar. However, ‘Amagi Amacha’ and ‘Oamacha’ yielded significantly higher PD content in comparison to ‘Odoriko Amacha’, which showed, in contrast, the significantly highest HG content. The total biomass was not significantly affected by the shading regime, but slightly higher biomass was observed under partially shaded and full-shade conditions. Hyperspectral vegetation indices (VIs) and color measurements indicate less vital plants under no shade conditions. While lighting is an important growth factor for hortensia production, DHC is cultivar dependent.

scholarly journals Paclobutrazol Improves Sesame Yield by Increasing Dry Matter Accumulation and Reducing Seed Shattering Under Rainfed Conditions

2021 ◽  
Author(s):  
Muhammad Zeeshan Mehmood ◽  
Ghulam Qadir ◽  
Obaid Afzal ◽  
Atta Mohi Ud Din ◽  
Muhammad Ali Raza ◽  
...  
Keyword(s):  
Leaf Area ◽  
Seed Production ◽  
Seed Yield ◽  
Dry Matter ◽  
Biomass Accumulation ◽  
Total Biomass ◽  
Dry Matter Accumulation ◽  
Seed Shattering ◽  
Rainfed Conditions ◽  
Leaf Greenness

AbstractSeveral biotic and abiotic stresses significantly decrease the biomass accumulation and seed yield of sesame crops under rainfed areas. However, plant growth regulators (such as Paclobutrazol) can improve the total dry matter and seed production of the sesame crop. The effects of the paclobutrazol application on dry matter accumulation and seed yield had not been studied before in sesame under rainfed conditions. Therefore, a two-year field study during 2018 and 2019 was conducted with key objectives to assess the impacts of paclobutrazol on leaf greenness, leaf area, total dry matter production and partitioning, seed shattering, and seed yield of sesame. Two sesame cultivars (TS-5 and TS-3) were treated with four paclobutrazol concentrations (P0 = Control, P1 = 100 mg L−1, P2 = 200 mg L−1, P3 = 300 mg L−1). The experiment was executed in RCBD-factorial design with three replications. Compared with P0, treatment P3 improved the leaf greenness of sesame by 17%, 38%, and 60% at 45, 85, and 125 days after sowing, respectively. However, P3 treatment decreased the leaf area of sesame by 14% and 20% at 45 and 85 days after sowing than P0, respectively. Compared with P0, treatment P3 increased the leaf area by 46% at 125 days after sowing. On average, treatment P3 also improved the total biomass production by 21% and partitioning in roots, stems, leaves, capsules, and seeds by 23%, 19%, 23%, 22%, and 40%, respectively, in the whole growing seasons as compared to P0. Moreover, under P3 treatment, sesame attained the highest seed yield and lowest seed shattering by 27% and 30%, respectively, compared to P0. This study indicated that by applying the paclobutrazol concentration at the rate of 300 mg L−1 in sesame, the leaf greenness, leaf areas, biomass accumulation, partitioning, seed yield, and shatter resistance could be improved. Thus, the optimum paclobutrazol level could enhance the dry matter accumulation and seed production capacity of sesame by decreasing shattering losses under rainfed conditions.

scholarly journals Mapping Wheat Dry Matter and Nitrogen Content Dynamics and Estimation of Wheat Yield Using UAV Multispectral Imagery Machine Learning and a Variety-Based Approach: Case Study of Morocco

2021 ◽  
Vol 3 (1) ◽  
pp. 29-49
Author(s):  
Ghizlane Astaoui ◽  
Jamal Eddine Dadaiss ◽  
Imane Sebari ◽  
Samir Benmansour ◽  
Ettarid Mohamed
Keyword(s):  
Random Forest ◽  
Nitrogen Uptake ◽  
Dry Matter ◽  
Vegetation Indices ◽  
Wheat Yield ◽  
Wheat Crop ◽  
Multispectral Imagery ◽  
Biophysical Parameters ◽  
Phenological Stages ◽  
Wheat Varieties

Our work aims to monitor wheat crop using a variety-based approach by taking into consideration four different phenological stages of wheat crop development. In addition to highlighting the contribution of Red-Edge vegetation indices in mapping wheat dry matter and nitrogen content dynamics, as well as using Random Forest regressor in the estimation of wheat yield, dry matter and nitrogen uptake relying on UAV (Unmanned Aerial Vehicle) multispectral imagery. The study was conducted on an experimental platform with 12 wheat varieties located in Sidi Slimane (Morocco). Several flight missions were conducted using eBee UAV with MultiSpec4C camera according to phenological growth stages of wheat. The proposed methodology is subdivided into two approaches, the first aims to find the most suitable vegetation index for wheat’s biophysical parameters estimation and the second to establish a global model regardless of the varieties to estimate the biophysical parameters of wheat: Dry matter and nitrogen uptake. The two approaches were conducted according to six main steps: (1) UAV flight missions and in-situ data acquisition during four phenological stages of wheat development, (2) Processing of UAV multispectral images which enabled us to elaborate the vegetation indices maps (RTVI, MTVI2, NDVI, NDRE, GNDVI, GNDRE, SR-RE et SR-NIR), (3) Automatic extraction of plots by Object-based image analysis approach and creating a spatial database combining the spectral information and wheat’s biophysical parameters, (4) Monitoring wheat growth by generating dry biomass and wheat’s nitrogen uptake model using exponential, polynomial and linear regression for each variety this step resumes the varietal approach, (5) Engendering a global model employing both linear regression and Random Forest technique, (6) Wheat yield estimation. The proposed method has allowed to predict from 1 up to 21% difference between actual and estimated yield when using both RTVI index and Random Forest technique as well as mapping wheat’s dry biomass and nitrogen uptake along with the nitrogen nutrition index (NNI) and therefore facilitate a careful monitoring of the health and the growth of wheat crop. Nevertheless, some wheat varieties have shown a significant difference in yield between 2.6 and 3.3 t/ha.

scholarly journals Exploring the Potential of High Resolution WorldView-3 Imagery for Estimating Yield of Mango

2018 ◽  
Vol 10 (12) ◽  
pp. 1866 ◽  
Author(s):  
Muhammad Rahman ◽  
Andrew Robson ◽  
Mila Bristow
Keyword(s):  
High Resolution ◽  
Vegetation Indices ◽  
Sampling Technique ◽  
Fruit Yield ◽  
Ann Model ◽  
Tree Crown ◽  
Crown Area ◽  
Fruit Number ◽  
Growing Seasons ◽  
Yield Parameters

Pre-harvest yield estimation of mango fruit is important for the optimization of inputs and other resources on the farm. Current industry practice of visual counting the fruit on a small number of trees for yield forecasting can be highly inaccurate due to the spatial variability, especially if the trees selected do not represent the entire crop. Therefore, this study evaluated the potential of high resolution WorldView-3 (WV3) satellite imagery to estimate yield of mango by integrating both geometric (tree crown area) and optical (spectral vegetation indices) data using artificial neural network (ANN) model. WV3 images were acquired in 2016–2017 and 2017–2018 growing seasons at the early fruit stage from three orchards in Acacia Hills region, Northern Territory, Australia. Stratified sampling technique (SST) was applied to select 18 trees from each orchard and subsequently ground truthed for yield (kg·tree−1) and fruit number per tree. For each sampled tree, spectral reflectance data and tree crown area (TCA) was extracted from WV3 imagery. The TCA was identified as the most important predictor of both fruit yield (kg·tree−1) and fruit number, followed by NDVI red-edge band when all trees from three orchards in two growing seasons were combined. The results of all sampled trees from three orchards in two growing seasons using ANN model produced a strong correlation (R2 = 0.70 and 0.68 for total fruit yield (kg·tree−1) and fruit number respectively), which suggest that the model can be obtained to predict yield on a regional level. On orchard level also the ANN model produced a high correlation when both growing seasons were combined. However, the model developed in one season could not be applied in another season due to the influence of seasonal variation and canopy condition. Using the relationship derived from the measured yield parameters against combined VIs and TCA data, the total fruit yield (t·ha−1) and fruit number were estimated for each orchard, produced 7% under estimation to less than 1% over estimation. The accuracy of the findings showed the potential of WV3 imagery to better predict the yield parameters than the current practice across the mango industry as well as to quantify lost yield as a result of delayed harvest.

scholarly journals Variation of MODIS reflectance and vegetation indices with viewing geometry and soybean development

2012 ◽  
Vol 84 (2) ◽  
pp. 263-274 ◽  
Author(s):  
Fábio M. Breunig ◽  
Lênio S. Galvão ◽  
Antônio R. Formaggio ◽  
José C.N. Epiphanio
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Constant Factor ◽  
The Other ◽  
Large Field ◽  
Phenological Stages ◽  
Water Index ◽  
Growing Seasons ◽  
Moderate Resolution Imaging Spectroradiometer

Directional effects introduce a variability in reflectance and vegetation index determination, especially when large field-of-view sensors are used (e.g., Moderate Resolution Imaging Spectroradiometer - MODIS). In this study, we evaluated directional effects on MODIS reflectance and four vegetation indices (Normalized Difference Vegetation Index - NDVI; Enhanced Vegetation Index - EVI; Normalized Difference Water Index - NDWI1640 and NDWI2120) with the soybean development in two growing seasons (2004-2005 and 2005-2006). To keep the reproductive stage for a given cultivar as a constant factor while varying viewing geometry, pairs of images obtained in close dates and opposite view angles were analyzed. By using a non-parametric statistics with bootstrapping and by normalizing these indices for angular differences among viewing directions, their sensitivities to directional effects were studied. Results showed that the variation in MODIS reflectance between consecutive phenological stages was generally smaller than that resultant from viewing geometry for closed canopies. The contrary was observed for incomplete canopies. The reflectance of the first seven MODIS bands was higher in the backscattering. Except for the EVI, the other vegetation indices had larger values in the forward scattering direction. Directional effects decreased with canopy closure. The NDVI was lesser affected by directional effects than the other indices, presenting the smallest differences between viewing directions for fixed phenological stages.

scholarly journals Development of experimental structure and influence of high CO2 concentration in maize cro

2012 ◽  
Vol 32 (2) ◽  
pp. 306-314 ◽  
Author(s):  
João B. Lopes da Silva ◽  
Paulo A. Ferreira ◽  
Eduardo G. Pereira ◽  
Luís C. Costa ◽  
Glauco V. Miranda
Keyword(s):  
Experimental Design ◽  
Dry Matter ◽  
Co2 Concentration ◽  
Dry Mass ◽  
C4 Plant ◽  
Active Radiation ◽  
High Co2 ◽  
Photosynthetic Rates ◽  
High Co2 Concentration ◽  
Experimental Structure

Maize is a C4 plant that shows few or no response to high [CO2]. Thus, this study aimed to analyze the photosynthetic rate and yield of maize under high [CO2] and develop open-top chambers (OTC) to create an atmosphere enriched with CO2. The experiment was conducted between October 2008 and March 2009. The OTCs were developed in modular scheme. Measurement of photosynthetic rates, transpiration, stomata conductance, grain yield and dry matter were performed. The experimental design was randomized blocks with four replications and three treatments: P1 - plants grown in OTC with 700 ppm [CO2], P2 - plants grown in OTC with environmental [CO2], and P3 - control, cultivated in open field. The results were analyzed by ANOVA and Tukey's test (Pr< 0.05). The chambers can reduce by 25% the photosynthetically active radiation and increase the air and leaf temperatures. Plants under high [CO2] (P1) showed the highest photosynthetic rates and the lowest stomata conductance and transpiration. The total weight of grains (g) and dry mass of shoots (g) showed no increases for P1, despite their higher photosynthetic rates.

scholarly journals Effect of harvesting time on forage yield and quality of maize

2018 ◽  
Vol 34 (3) ◽  
pp. 345-353 ◽  
Author(s):  
Violeta Mandic ◽  
Zorica Bijelic ◽  
Vesna Krnjaja ◽  
Aleksandar Simic ◽  
Maja Petricevic ◽  
...  
Keyword(s):  
Protein Content ◽  
Crude Protein ◽  
Dry Matter ◽  
Matter Content ◽  
Forage Yield ◽  
Dry Matter Content ◽  
Crude Protein Content ◽  
Maize Hybrid ◽  
Growing Seasons ◽  
Yield And Quality

Maize is the very important silage source in the world. Timely harvesting ensure high maize forage yield and quality. Therefore, the study focused on the effects of four harvesting times (starting at the 12 August every 7 days) on yield and qualitative parameters of forage green mass of maize hybrid ZP 677. The experiment was set in Vojvodina Province, Serbia, during the 2013 and 2014 growing seasons. Plant height, stem diameter, number of leaves per plant, ear percentage, forage yield, dry matter content and crude protein content were higher, while stem percentage was lower in 2014 with favorable climatic condition. Forage yield, crude protein content, ADF and NDF decreased, while dry matter content significantly increased with delay in harvesting. The maize hybrid should be harvested when the milk line is three-quarter of the way down the grain that is in the third decade of August.

scholarly journals FEATURE FILTERING AND SELECTION FOR DRY MATTER ESTIMATION ON PERENNIAL RYEGRASS: A CASE STUDY OF VEGETATION INDICES

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 1827-1831 ◽  
Author(s):  
G. T. Alckmin ◽  
L. Kooistra ◽  
A. Lucieer ◽  
R. Rawnsley
Keyword(s):  
Feature Selection ◽  
Perennial Ryegrass ◽  
Dry Matter ◽  
Selection Process ◽  
Vegetation Indices ◽  
Robust Model ◽  
Trade Offs ◽  
Initial Dataset ◽  
High Degree

<p><strong>Abstract.</strong> Vegetation indices (VIs) have been extensively employed as a feature for dry matter (DM) estimation. During the past five decades more than a hundred vegetation indices have been proposed. Inevitably, the selection of the optimal index or subset of indices is not trivial nor obvious. This study, performed on a year-round observation of perennial ryegrass (n&amp;thinsp;=&amp;thinsp;900), indicates that for this response variable (i.e. kg.DM.ha<sup>&amp;minus;1</sup>), more than 80% of indices present a high degree of collinearity (correlation&amp;thinsp;&amp;gt;&amp;thinsp;|0.8|.) Additionally, the absence of an established workflow for feature selection and modelling is a handicap when trying to establish meaningful relations between spectral data and biophysical/biochemical features. Within this case study, an unsupervised and supervised filtering process is proposed to an initial dataset of 97 VIs. This research analyses the effects of the proposed filtering and feature selection process to the overall stability of final models. Consequently, this analysis provides a straightforward framework to filter and select VIs. This approach was able to provide a reduced feature set for a robust model and to quantify trade-offs between optimal models (i.e. lowest root mean square error &amp;ndash; RMSE&amp;thinsp;=&amp;thinsp;412.27&amp;thinsp;kg.DM.ha<sup>&amp;minus;1</sup>) and tolerable models (with a smaller number of features &amp;ndash; 4 VIs and within 10% of the lowest RMSE.)</p>

scholarly journals Exogenous Abscisic Acid Application Effects on Stomatal Closure, Water Use, and Shelf Life of Hydrangea (Hydrangea macrophylla)

2009 ◽  
Vol 27 (4) ◽  
pp. 234-238 ◽  
Author(s):  
Marc W. van Iersel ◽  
Kate Seader ◽  
Sue Dove
Keyword(s):  
Abscisic Acid ◽  
Shelf Life ◽  
Water Uptake ◽  
Stomatal Closure ◽  
Ornamental Plants ◽  
Detectable Effect ◽  
Water Control ◽  
Available Water ◽  
Hydrangea Macrophylla ◽  
Plant Available Water

Abstract A lack of adequate watering reduces the shelf life of many ornamental plants during retail. Our goals were to determine whether sprays or drenches with abscisic acid (ABA) can reduce transpiration and extend the shelf life of hydrangea (Hydrangea macrophylla). During the first 5 days after treatment, ABA drenches of 125 to 1000 ppm reduced stomatal conductance (gs) by 50 to 80% as compared to water. ABA-induced stomatal closure reduced plant water uptake from the substrate; control plants took up half of the plant-available water during the first 7 days after treatment, while it took 14 days for plants drenched with 1000 ppm to take up half of the available water. Control plants wilted after 12 days and time to wilting of drenched plants increased with increasing ABA concentrations, up to 23 days in the 1000 ppm treatment. Spray treatments had little effect on gs and no detectable effect on water uptake or time to wilting. Some yellowing of older leaves was seen with ABA drenches of 500 or 1000 ppm. Despite this side effect, ABA drenches have potential to extend the shelf life of hydrangeas in retail environments.

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