Leaf area durations and grain yields of two tropical rice varieties

1968 ◽  
Vol 8 (34) ◽  
pp. 587
Author(s):  
PC Owen
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Photosynthetic Efficiency ◽  
Temperate Climate ◽  
Growth Stages ◽  
Rice Varieties ◽  
Area Index ◽  
Grain Yields ◽  
Different Growth Stages

A series of differing leaf area index regimes during the growth of two tropical rice varieties was produced by partial defoliation at different growth stages. In addition, part of the crop was completely defoliated after panicle emergence. Comparison of the effects of the range of leaf area durations (D) thus produced showed that these rice varieties differed from temperate climate cereals. Grain yields were least associated with D after panicle emergence, but were most influenced by D before emergence. This effect is mainly via an influence upon the number of spikelets formed per panicle. Grain : leaf ratio, a measure of photosynthetic efficiency, was considerably lower than values reported for wheat.

scholarly journals Remote sensing retrieval of winter wheat leaf area index and canopy chlorophyll density at different growth stages

2021 ◽  
pp. 1-23
Author(s):  
Naichen Xing ◽  
Wenjiang Huang ◽  
Huichun Ye ◽  
Yingying Dong ◽  
Weiping Kong ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Winter Wheat ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Growth Stages ◽  
Area Index ◽  
Wheat Leaf ◽  
Different Growth Stages

scholarly journals Phosphorus and Zinc Interaction Influence Leaf Area Index in Fine vs. Coarse Rice (Oryza sativa L) Genotypes in Northwest Pakistan

2016 ◽  
Vol 2 ◽  
Author(s):  
Amanullah , ◽  
Inamullah , ◽  
Zahir Shah ◽  
Shad Khan Khalil
Keyword(s):  
Oryza Sativa ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Growth And Yield ◽  
Growth Stages ◽  
Area Index ◽  
Physiological Maturity ◽  
Rice Genotypes ◽  
The Impact ◽  
Different Growth Stages

Leaf area index (LAI) is a measure of leafiness per unit ground area and denotes the extent of photosynthetic machinery is an important growth and yield-determining factor because it is a major determinant of light interception and transpiration. Phosphorus (P) and zinc (Zn) and rate are the most important factors affecting leaf area index (LAI) of rice(<em>Oryza sativa</em> L.). A field experiment was conducted to assess the impact of phosphorus (0, 40, 80, 120 kg P ha<sup>-1</sup>) and zinc levels (0, 5, 10, 15 kg Zn ha<sup>-1</sup>) on LAI of rice (<em>Oryza sativa</em> L.) genotypes [fine (Basmati-385) and coarse (Fakhr-e-Malakand &amp; Pukhraj)]. The experiment was conducted on farmer field at Batkhela, Malakadnd in Northwest Pakistan during summer 2011 and 2012. When combined over the two years, the data revealed that the highest LAI at three different growth stages (tillering, heading and physiological maturity) was obtained with application of the highest P level (120 kg ha<sup>-1</sup>) being at par with 80 kg P ha<sup>-1</sup>, while the lowest LAI was recorded when P was not applied. Similarly, the highest LAI was obtained with application of the two higher Zn levels (10 and 15 kg Zn ha<sup>-1</sup>), while the lowest LAI was recorded when Zn was not applied. In case of rice genotypes, the highest LAI was obtained from Pukhraj than other two genotypes at all growth stages. The other two rice genotypes (Fakher-e-Malakand and Basmati-385) produced statistically similar LAI at different growth stages. The higher LAI of Pukhraj was attributed to its long and wider leaves that resulted in higher mean single leaf area, leaf area per tiller, per hill and per square meter. The LAI was highest at heading stages than at early (tillering) and later (physiological maturity) growth stages. The increase in LAI was attributed to the increase in tillers number and leaf area hill<sup>-1</sup>. The increase in LAI showed positive impact on crop growth rate, dry matter accumulationand yield. Application of 120 kg P + 10 kg Zn ha<sup>-1</sup> to rice genotype Pukhraj was more beneficial in terms of higher LAI and productivity in the study area.

Using Hemispherical Photography to Determine Leaf Area Index of Landscape Trees in Urban Green Space of Dongguan, South China

2014 ◽  
Vol 955-959 ◽  
pp. 4034-4038
Author(s):  
Luo Jian Mo ◽  
Wen Bin Li ◽  
Yong Chang Ye ◽  
Yong Wen Zhou ◽  
Song Song Liu ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Green Space ◽  
Urban Green Space ◽  
Growth Stages ◽  
Hemispherical Photography ◽  
Area Index ◽  
Urban Green ◽  
Large Trees ◽  
Landscape Trees

Transect sampling method was used to measure structural attributes of landscape trees in urban green space of three city parks and one residential greenbelt in Dongguan. Leaf area index (LAI) of the landscape trees in each urban green space was determined using hemispherical photography. Average DBH (diameter at the breast height) and CW(crown width) in Wenhua Square were the largest due to the presence of heritage large trees, while the landscape trees were species diverse in Renmin Park. A comparison of LAI in the green space gave a result in descending order: Renmin Park > Wenhua Square > Jinhuwan greenbelt > Yuanmei Park. The case of Renmin Park indicated that when a green space consisted of various structural attributes, landscape trees in different growth stages tended to have large LAI. Findings of our study suggested that a diversity of trees with potentially different LAI should be selected when planning urban green space.

scholarly journals Quantifying Uncertainty and Bridging the Scaling Gap in the Retrieval of Leaf Area Index by Coupling Sentinel-2 and UAV Observations

2020 ◽  
Vol 12 (11) ◽  
pp. 1843 ◽  
Author(s):  
Andrew Revill ◽  
Anna Florence ◽  
Alasdair MacArthur ◽  
Stephen Hoad ◽  
Robert Rees ◽  
...  
Keyword(s):  
Spatial Heterogeneity ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Growth Stages ◽  
Two Stage ◽  
Area Index ◽  
Field Surveys ◽  
Red Edge ◽  
Calibration Approach ◽  
Sentinel 2

Leaf area index (LAI) estimates can inform decision-making in crop management. The European Space Agency’s Sentinel-2 satellite, with observations in the red-edge spectral region, can monitor crops globally at sub-field spatial resolutions (10–20 m). However, satellite LAI estimates require calibration with ground measurements. Calibration is challenged by spatial heterogeneity and scale mismatches between field and satellite measurements. Unmanned Aerial Vehicles (UAVs), generating high-resolution (cm-scale) LAI estimates, provide intermediary observations that we use here to characterise uncertainty and reduce spatial scaling discrepancies between Sentinel-2 observations and field surveys. We use a novel UAV multispectral sensor that matches Sentinel-2 spectral bands, flown in conjunction with LAI ground measurements. UAV and field surveys were conducted on multiple dates—coinciding with different wheat growth stages—that corresponded to Sentinel-2 overpasses. We compared chlorophyll red-edge index (CIred-edge) maps, derived from the Sentinel-2 and UAV platforms. We used Gaussian processes regression machine learning to calibrate a UAV model for LAI, based on ground data. Using the UAV LAI, we evaluated a two-stage calibration approach for generating robust LAI estimates from Sentinel-2. The agreement between Sentinel-2 and UAV CIred-edge values increased with growth stage—R2 ranged from 0.32 (stem elongation) to 0.75 (milk development). The CIred-edge variance between the two platforms was more comparable later in the growing season due to a more homogeneous and closed wheat canopy. The single-stage Sentinel-2 LAI calibration (i.e., direct calibration from ground measurements) performed poorly (mean R2 = 0.29, mean NRMSE = 17%) when compared to the two-stage calibration using the UAV data (mean R2 = 0.88, mean NRMSE = 8%). The two-stage approach reduced both errors and biases by >50%. By upscaling ground measurements and providing more representative model training samples, UAV observations provide an effective and viable means of enhancing Sentinel-2 wheat LAI retrievals. We anticipate that our UAV calibration approach to resolving spatial heterogeneity would enhance the retrieval accuracy of LAI and additional biophysical variables for other arable crop types and a broader range of vegetation cover types.

scholarly journals Effect Of Planting Geometry On Growth Of Rice Varieties

2017 ◽  
Vol 5 (4) ◽  
pp. 423-429 ◽  
Author(s):  
Mohan Mahato ◽  
Bishnu Bilas Adhikari
Keyword(s):  
Growth Rate ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Plant Height ◽  
Dry Matter ◽  
Dry Matter Accumulation ◽  
Rice Varieties ◽  
Area Index ◽  
Crop Growth Rate ◽  
Planting Geometry

A field experiment was conducted under humid subtropical agro-climatic condition of Nepal during rainy season of 2014. The experiment was laid out in to two factor Randomized Complete Block Design with  three replications consisting three drought tolerant rice varieties (Sukhadhan-4, Sukhadhan-5 and Radha-4) and four planting geometry (15 cm × 10 cm, 15 cm × 15 cm, 20 cm × 15 cm and 20 cm × 20 cm). The results revealed that the highest plant height and maximum leaf area index was recorded in planting geometry 15 cm × 10 cm in all growth stages. Whereas, planting geometry 20 cm × 15 cm produced the maximum number of tiller m-2 in all growth stage.  While planting geometry 20 cm × 15 cm and 20 cm × 20 cm produced statistically similar crop growth rate and dry matter accumulation in all stage of growth. Regarding the varieties, Sukhadhan- 4 showed highest plant height up to 75 DAT and plant height was statistically similar to Radha - 4 in 60 and 75 DAT. But maximum number of tiller m-2, leaf area index, crop growth rate and dry matter accumulation were recorded in Sukhadhan – 5 varieties. Int. J. Appl. Sci. Biotechnol. Vol 5(4): 423-429

scholarly journals Seasonal Net Carbon Exchange in Rotation Crops in the Temperate Climate of Central Lithuania

2019 ◽  
Vol 11 (7) ◽  
pp. 1966 ◽  
Author(s):  
Ligita Baležentienė ◽  
Ovidijus Mikša ◽  
Tomas Baležentis ◽  
Dalia Streimikiene
Keyword(s):  
Climate Change ◽  
Exchange Rate ◽  
Soil Respiration ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Co2 Emissions ◽  
Vegetation Period ◽  
Temperate Climate ◽  
Carbon Exchange ◽  
Area Index

Intelligent agricultural solutions require data on the environmental impacts of agriculture. In order for operationalize decision-making for sustainable agriculture, one needs to establish the corresponding datasets and protocols. Increasing anthropogenic CO2 emissions into the atmosphere force the choice of growing crops aimed at mitigating climate change. For this reason, investigations of seasonal carbon exchange were carried out in 2013–2016 at the Training Farm of the Vytautas Magnus University (former Aleksandras Stulginskis University), Lithuania. This paper compares the carbon exchange rate for different crops, viz., maize, ley, winter wheat, spring rapeseed and barley under conventional farming. This study focuses on the carbon exchange rate. We measure the emitted and absorbed CO2 fluxes by applying the closed chamber method. The biomass measurement and leaf area index (LAI) calculations at different plant growth stages are used to evaluate carbon exchange in different agroecosystems. The differences in photosynthetically assimilated CO2 rates were significantly impacted by the leaf area index (p = 0.04) during the plant vegetation period. The significantly (p = 0.02–0.05) strong correlation (r = 0.6–0.7) exists between soil respiration and LAI. Soil respiration composed only 21% of the agroecosystem carbon exchange. Plant respiration ranged between 0.034 and 3.613 µmol m−2 s−1 during the vegetation period composed of a negligible ratio (mean 16%) of carbon exchange. Generally, respiration emissions were obviously recovered by the gross primary production (GPP) of crops. Therefore, the ecosystems were acting as an atmospheric CO2 sink. Barley accumulated the lowest mean GPP 12.77 µmol m−2 s−1. The highest mean GPP was determined for ley (14.28 µmol m−2 s−1) and maize (15.68 µmol m−2 s−1) due to the biggest LAI and particular bio-characteristics. Due to the highest NEP, the ley (12.66 µmol m−2 s−1) and maize (12.76 µmol m−2 s−1) agroecosystems sank the highest C from the atmosphere and, thus, they might be considered the most sustainable items between crops. Consequently, the appropriate choice of crops and their area in crop rotations may reduce CO2 emissions and their impact on the environment and climate change.

scholarly journals RANDOM FOREST REGRESSION FOR THE ESTIMATION OF LEAF AREA INDEX OF OKRA CROP USING GROUND BASED BISTATIC SCATTEROMETER

2018 ◽  
Vol XLII-5 ◽  
pp. 719-725
Author(s):  
S. A. Yadav ◽  
R. Prasad ◽  
A. K. Vishwakarma ◽  
V. P. Yadav
Keyword(s):  
Regression Analysis ◽  
Random Forest ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Growth Stages ◽  
Data Sets ◽  
Angle Of Incidence ◽  
Random Forest Regression ◽  
Area Index ◽  
Scattering Coefficients

<p><strong>Abstract.</strong> The specular bistatic scattering mechanism of Okra's crop was analyzed using dual polarized ground based bistatic scatterometer system at X, C, and L bands in the specular direction with the azimuthal angle(&amp;theta;<span class="thinspace"></span>=<span class="thinspace"></span>0&amp;deg;). An outdoor Okra crop bed of area 10<span class="thinspace"></span>&amp;times;<span class="thinspace"></span>10<span class="thinspace"></span>m<sup>2</sup> was specially prepared for the estimation of leaf area index (LAI) at HH and VV polarizations over the angular range of incidence angle 20&amp;deg; to 60&amp;deg; at steps of 10&amp;deg;. The regression analysis was done between bistatic specular scattering coefficients and crop biophysical parameter at X, C, and L bands for HH and VV polarization at different angle of incidence to determine the optimum parameters of bistatic scatterometer system. The linear regression analysis showed the high correlation at 40&amp;deg; angle of incidence for all bands and polarizations for the Okra crop. The computed scattering coefficients and measured LAI of Okra crop for the seven growth stages at 40&amp;deg; angle of incidence were interpolated into 61 data sets. The data sets were divided into input, validation and testing for the training and testing of the developed random forest regression (RF) model for the estimation of LAI for Okra crop. The estimated values of LAI of Okra crop, by the developed RF regression model, were found more closer to the observed values at X band for VV polarization with coefficient of determination (R<sup>2</sup><span class="thinspace"></span>=<span class="thinspace"></span>0.928) and low root mean square error (RMSE<span class="thinspace"></span>=<span class="thinspace"></span>0.260<span class="thinspace"></span>m<sup>2</sup>/m<sup>2</sup>) in comparison to C and L bands.</p>

scholarly journals Performance of Transplant Aus Rice Varieties under Different Nitrogen Management Practices

2021 ◽  
pp. 52-62
Author(s):  
Md. Omar Faruk ◽  
A. S. M. Iqbal Hussain ◽  
Md. Abu Yusuf ◽  
Md. Nazmul Hasan Mehedi
Keyword(s):  
Grain Yield ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Plant Height ◽  
Nitrogen Management ◽  
Grain Weight ◽  
Panicle Length ◽  
Rice Varieties ◽  
Area Index ◽  
1000 Grain Weight

Management of applied nitrogen in rice field is one tool that could lead to increase in rice yield, but often ignored by most farmers. The experiment was carried out from April to July 2015 at the Agronomy Field Laboratory of Patuakhali Science and Technology University, Dumki, Patuakhali to find out the influence of different nitrogen management and variety on the yield performance of transplant Ausrice. The study consisted of four levels of nitrogen viz. Control (without N), 30 kg N ha-1, 60 kg N ha-1 and urea super granule @ 52 kg N ha-1 and four Transplanted aus rice varieties viz. KaliHitta, ChaitaBoro, Abdul Hai and Gota IRRI, and was laid out in a split-plot design with three replications. The levels of nitrogen were assigned in the main plot and varieties were allocated in the sub-plots. Nitrogen management, variety and their interactions exerted significant (P ≤ 0.05) influence on plant characters, yield contributing characters and yield of transplanted Aus rice. In the case of nitrogen management, the tallest plant was 161.60 cm, maximum leaf area index(2.97, the highest number of effective tillers hill-115, longest panicle 24.30 cm with the maximum number of filled grains as94.73, 1000-grain weight gave 29.97 g. Grain yield of 2.48 t ha-1 were obtained from USG @ 52 kg N ha-1 and the shortest plant height of 136.90 cm with lowest leaf area index of 1.78, lowest number of effective tillers hill-1 (8.43), shortest panicle (18.84 cm) with the lowest numbers of filled grains panicle-1 (53.18), 1000-grain weight (24.33 g) and grain yield (1.40 t ha-1) were obtained in control (N1=O, kg N ha-1). Among the varieties, ChaitaBoro gave the tallest plant height (151.60 cm) and maximum leaf area index (2.54). While the highest number of effective tillers hill-1 (12.20), longest panicle (22.42 cm) with the maximum number of filled grains panicle-1 (73.50), highest 1000-grain weight (27.41 g) and highest grain yield (2.39 t ha-1) were recorded from Gota IRRI than other varieties. In case of interaction, Gota IRRI Fertilized with USG at 52 kg N ha-1 produced the highest number of effective tillers hill-1 (16.87), panicle length (25.13 cm), number of grains panicle-1 (105.70) and grain yield (3.13 t ha-1). The lowest number of effective tillers hill-1 (8.13), lowest panicle length (17.47 cm) with minimum numbers of filled grains 47.67) and grain yield (1.12 t ha-1) were produced by the interaction of control (N1=O, kg N ha-1) and Kali Hitta. So, cultivation of transplant Aus rice (Gota IRRI) appeared to be the best performance with USG @ 52 kg N ha-1 and recommended to the end users.

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