Specific leaf area development of autumn-sown sugar beet (Beta vulgaris L.) on different sowing dates in northern Germany

2015 ◽  
Vol 153 (7) ◽  
pp. 1292-1301 ◽  
Author(s):  
H. STEPHAN ◽  
U. BÖTTCHER ◽  
H. KAGE
Keyword(s):  
Sugar Beet ◽  
Leaf Area ◽  
Specific Leaf Area ◽  
Leaf Growth ◽  
Multiple Linear Regression Model ◽  
Growth Period ◽  
Stepwise Multiple Regression ◽  
Growth Stages ◽  
Northern Germany ◽  
Area Index

SUMMARYIn most regions, sugar beet is normally sown as a spring crop. If sown in autumn the crop remains on the field over winter and may achieve fast re-growth in spring from assimilates stored within the beet, allowing earlier leaf growth and light interception in spring. The specific leaf area (SLA) (ratio between leaf surface and leaf mass) is mainly affected by leaf area expansion and consequently affects productivity in early growth stages. The aim of the present study was (i) to examine the SLA dynamics of autumn-sown sugar beet before and after winter and (ii) to develop an empiric approach describing SLA changes during the growth period. A field trial in northern Germany with three different sowing times (mid-April, mid-June and mid-August) and varying plant densities (148 000, 246 000 and 370 000 plants/ha) was carried out in 2009/10 to 2011/12. The average SLA of the canopy was the highest (>25 m2/kg) directly after emergence, then decreased until autumn (<13 m2/kg) and increased again up to 20 m2/kg during re-growth of winter sugar beet in spring. A stepwise multiple regression analysis revealed mean photosynthetically active radiation over 10 days before measurement (PARmean), leaf area index (LAI), mean temperature over 10 days before measurement (Tmean) and temperature sum since sowing (Tsum) as the main influences on SLA dynamics. The strongest correlation to SLA was shown by Tmean (r = 0·69) and the weakest by Tsum (r = −0·28). A multiple linear regression model was fitted to the dataset with Tmean, PARmean and log (Tsum) achieving an adjusted R2 of 0·64. This empirical equation is suitable for use in a crop growth model for winter sugar beet.

Pronamide Effects on Physiology and Yield of Sugar Beet

Weed Science ◽  
2008 ◽  
Vol 56 (3) ◽  
pp. 457-463 ◽  
Author(s):  
Kalliopi Kadoglidou ◽  
Chrysovalantis Malkoyannidis ◽  
Kalliopi Radoglou ◽  
Ilias Eleftherohorinos ◽  
Helen-Isis A. Constantinidou
Keyword(s):  
Sugar Beet ◽  
Leaf Area ◽  
Field Experiments ◽  
Leaf Growth ◽  
Sugar Yield ◽  
Growth Stages ◽  
Area Index ◽  
Vegetative Period ◽  
Leaf Stage ◽  
Photosynthetic Yield

Field experiments were conducted in northern Greece during 2001 and repeated in 2002 and 2004 to evaluate the effects of pronamide on sugar beet. Total leaf area, leaf area index (LAI), leaf and root dry weights, photosynthetic yield (quantum yield of photochemical energy conversion in photosystem II), chlorotic index, and yield components of sugar beet were monitored after pronamide application. Three sugar beet cultivars, ‘Avantage’, ‘Dorothea’, and ‘Bianca’, requiring short, intermediate, and long vegetative periods, respectively, were subjected to treatment. Pronamide was applied on sugar beet either as a double application of 0.63 kg ai ha−1at the two- to four-leaf and 0.63 kg ai ha−1at the four- to six-leaf stage or as a single application of 1.26 kg ai ha−1performed at the latter leaf stage. Both application procedures were combined with a split application of phenmedipham at 0.04 kg ai ha−1plus desmedipham at 0.04 kg ai ha−1plus metamitron at 0.70 kg ai ha−1plus ethofumesate at 0.10 kg ai ha−1plus mineral oil at 0.50 L ha−1applied POST at the cotyledon–to–two-leaf as well as at the four-leaf growth stages. Pronamide (both single and double application) initially caused chlorosis and reduction of sugar beet growth. LAI and photosynthetic yield were also significantly affected for a 2-mo period following the final application, after which the negative effects caused by pronamide were ameliorated. At harvest, sugar beet root and sugar yield, sucrose, K+, Na+, and N-amino acid concentrations were not affected by the herbicide treatments compared with those produced in weed-free and herbicide-free plots, indicating that all cultivars managed to overcome the transient pronamide stress. Regarding sugar beet cultivars, root and sugar yield of Avantage and Dorothea at harvest were higher than that of Bianca, whereas sucrose concentration of Avantage was the lowest. There was not an apparent relationship between the order of sugar yield per cultivar (Dorothea > Avantage > Bianca) and the length of the vegetative period (Avantage < Dorothea < Bianca).

scholarly journals Response of Soil Temperature, Moisture, and Spring Maize (Zea mays L.) Root/Shoot Growth to Different Mulching Materials in Semi-Arid Areas of Northwest China

Agronomy ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 453
Author(s):  
Haidong Lu ◽  
Zhenqing Xia ◽  
Yafang Fu ◽  
Qi Wang ◽  
Jiquan Xue ◽  
...  
Keyword(s):  
Soil Temperature ◽  
Soil Water ◽  
Leaf Area ◽  
Growth Period ◽  
Soil Water Storage ◽  
Shoot Biomass ◽  
Growth Stages ◽  
Plastic Film ◽  
Area Index ◽  
Spring Maize

Adaptive highly efficient mulching technologies for use on dryland agricultural ecosystems are crucial to improving crop productivity and water-use efficiency (WUE) under climate change. Little information is available on the effect of using different types of mulch on soil water thermal conditions, or on root/shoot trait, leaf area index (LAI), leaf area duration (LAD), yield, and WUE of spring maize. Hence, in this study, white transparent plastic film (WF), black plastic film (BF), and maize straw (MS) was used, and the results were compared with a non-mulched control (CK). The results showed that the mean soil temperature throughout the whole growth period of maize at the 5–15 cm depth under WF and BF was higher than under MS and CK, but under BF, it was 0.6 °C lower than WF. Compared with CK, the average soil water storage (0–200 cm) over the whole growth period of maize was significantly increased under WF, BF, and MS. WF and BF increased the soil water and temperature during the early growth stages of maize and significantly increased root/shoot biomass, root volume, LAI, LAD, and yield compared with MS. Higher soil temperatures under WF obviously reduced the duration of maize reproductive growth and accelerated root and leaf senescence, leading to small root/shoot biomass accumulation post-tasseling and to losses in yield compared with BF

scholarly journals Nitrogen for growth of stock plants and production of strawberry runner tips

Bragantia ◽  
2012 ◽  
Vol 71 (3) ◽  
pp. 394-399 ◽  
Author(s):  
Djeimi Isabel Janisch ◽  
Jerônimo Luiz Andriolo ◽  
Vinícius Toso ◽  
Kamila Gabriele Ferreira dos Santos ◽  
Jéssica Maronez de Souza
Keyword(s):  
Leaf Area ◽  
Nutrient Solution ◽  
Dry Matter ◽  
Nitrogen Concentration ◽  
Growth Period ◽  
Dry Matter Partitioning ◽  
Area Index ◽  
Camino Real ◽  
Nitrogen Concentrations ◽  
Crown Roots

The objective of this research was to determine growth and dry matter partitioning among organs of strawberry stock plants under five Nitrogen concentrations in the nutrient solution and its effects on emission and growth of runner tips. The experiment was carried out under greenhouse conditions, from September 2010 to March 2011, in a soilless system with Oso Grande and Camino Real cultivars. Nitrogen concentrations of 5.12, 7.6, 10.12 (control), 12.62 and 15.12 mmol L-1 in the nutrient solution were studied in a 5x2 factorial randomised experimental design. All runner tips bearing at least one expanded leaf (patent requested) were collected weekly and counted during the growth period. The number of leaves, dry matter (DM) of leaves, crown and root, specific leaf area and leaf area index (LAI) was determined at the final harvest. Increasing N concentration in the nutrient solution from 5.12 to 15.12 mmol L-1 reduces growth of crown, roots and LAI of strawberry stock plants but did not affect emission and growth of runner tips. It was concluded that for the commercial production of plug plants the optimal nitrogen concentration in the nutrient solution should be 5.12 mmol L-1.

scholarly journals An Improved Canopy Integration Scheme for a Land Surface Model with Prognostic Canopy Structure

2007 ◽  
Vol 20 (15) ◽  
pp. 3902-3923 ◽  
Author(s):  
Peter E. Thornton ◽  
Niklaus E. Zimmermann
Keyword(s):  
Leaf Area ◽  
Specific Leaf Area ◽  
Land Surface ◽  
Temperate Climate ◽  
Integration Scheme ◽  
Surface Model ◽  
Area Index ◽  
Climate System Model ◽  
Community Land Model ◽  
Canopy Model

Abstract A new logical framework relating the structural and functional characteristics of a vegetation canopy is presented, based on the hypothesis that the ratio of leaf area to leaf mass (specific leaf area) varies linearly with overlying leaf area index within the canopy. Measurements of vertical gradients in specific leaf area and leaf carbon:nitrogen ratio for five species (two deciduous and three evergreen) in a temperate climate support this hypothesis. This new logic is combined with a two-leaf (sunlit and shaded) canopy model to arrive at a new canopy integration scheme for use in the land surface component of a climate system model. An inconsistency in the released model radiation code is identified and corrected. Also introduced here is a prognostic canopy model with coupled carbon and nitrogen cycle dynamics. The new scheme is implemented within the Community Land Model and tested in both diagnostic and prognostic canopy modes. The new scheme increases global gross primary production by 66% (from 65 to 108 Pg carbon yr−1) for diagnostic model simulations driven with reanalysis surface weather, with similar results (117 PgC yr−1) for the new prognostic model. Comparison of model predictions to global syntheses of observations shows generally good agreement for net primary productivity (NPP) across a range of vegetation types, with likely underestimation of NPP in tundra and larch communities. Vegetation carbon stocks are higher than observed in forest systems, but the ranking of stocks by vegetation type is accurately captured.

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 Suitability of Canopy Temperature Depression, Specific Leaf Area, and SPAD Chlorophyll Reading for Genotypic Comparison of Peanut Grown in a Sub-humid Environment

2014 ◽  
Vol 41 (2) ◽  
pp. 100-110 ◽  
Author(s):  
D. Singh ◽  
M. Balota ◽  
T. G. Isleib ◽  
E. Collakova ◽  
G. E. Welbaum
Keyword(s):  
Leaf Area ◽  
Water Deficit ◽  
Specific Leaf Area ◽  
Canopy Temperature ◽  
Physiological Characteristics ◽  
Growth Stages ◽  
Pod Yield ◽  
Humid Environment ◽  
Canopy Temperature Depression ◽  
Temperature Depression

ABSTRACT Peanut (Arachis hypogaea L.) is mostly grown under rainfed production with water deficit being the major limiting factor. Several physiological characteristics have been proposed as surrogates for yield and genotypic selection under water deficit in arid climates, but their suitability for selection under sub-humid rainfed production where water deficit can also occur is not clear. Canopy temperature depression (CTD), specific leaf area (SLA), and SPAD chlorophyll reading of eight virginia-type peanut genotypes were evaluated at three growth stages in field trials involving rainfed and irrigated plants in sub-humid environments in northeastern Virginia-Carolina (VC) region in 2011 and 2012. Significant (p≤0.05) variation in pod yield and all physiological characteristics was observed in response to water regime in both years. Rainfed plants had warmer (CTD 2.2 vs. 3.1 °C) and greener canopies in 2011 but cooler (CTD 3.9 vs. 2.2 °C) and less green canopies in 2012 than the irrigated plants. Compared to irrigated plants, rainfed plants had slightly increased SLA in 2011 (135 vs. 131 cm2 g−1), but decreased SLA in 2012 (133 vs. 144 cm2 g−1). Differences (p≤0.05) among genotypes were observed for pod yield, SLA, and SPAD chlorophyll reading, but not for CTD. Among the physiological characteristics, only SPAD chlorophyll readings were significantly correlated to pod yield in all water regimes and growth stages in 2012, but not in 2011. Based on these results, CTD, SLA, and SPAD chlorophyll reading appear to be unsuited for genotypic selection for yield and water-deficit tolerance for peanut grown in sub-humid environment of the Virginia-Carolina region in part due to unpredictable rainfall amount and distribution. For reproducible field evaluations, additional methods will have to be used such as use of rain exclusion shelters.

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