scholarly journals RESEARCHES OF OPTIMUM LEAF AREA INDEX DYNAMICMODELS FOR RAPE(BRASSICA NAPUS L.)

2009 ◽  
pp. 1585-1594 ◽  
Author(s):  
Hongxin Cao ◽  
Chunlei Zhang ◽  
Guangming Li ◽  
Baojun Zhang ◽  
Suolao Zhao ◽  
...  
Keyword(s):  
Brassica Napus ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Brassica Napus L ◽  
Area Index

GROWTH ANALYSIS OF BRASSICA NAPUS CV. TOWER

1978 ◽  
Vol 58 (3) ◽  
pp. 587-595 ◽  
Author(s):  
J. M. CLARKE ◽  
G. M. SIMPSON
Keyword(s):  
Brassica Napus ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Seed Yield ◽  
Growth Analysis ◽  
Plant Morphology ◽  
Brassica Napus L ◽  
Area Index ◽  
Matter Production ◽  
Net Assimilation

Growth analysis of field-grown rape (Brassica napus L.) was carried out during 1975 and 1976 at Saskatoon. Plant morphology was altered by the use of four planting densities under three water regimes. High seeding rates and non-irrigated conditions caused a greater proportion of dry matter production to occur before flowering than after flowering, while the reverse occurred at low seeding rates and under irrigated conditions. Leaf area index reached a maximum near the start of flowering, and then declined rapidly. Pod surface area was increased by irrigation and was higher at the high seeding rates than at the low seeding rates. Maximum leaf area index was correlated with seed yield. Correlations between pod area and seed yield were poor, particularly in 1976. The growth functions mean net assimilation rate [Formula: see text] and mean crop growth rate [Formula: see text] were influenced by both seeding rates and irrigation. There was an increase in [Formula: see text] during the ripening phase, suggesting increased photosynthetic efficiency. No evidence of a distinct optimum leaf area index was found.

scholarly journals   Ground cover and leaf area index relationship in a grass, legume and crucifer crop

2012 ◽  
Vol 58 (No. 8) ◽  
pp. 385-390 ◽  
Author(s):  
J. Ramirez-Garcia ◽  
P. Almendros ◽  
M. Quemada
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Ground Cover ◽  
Mean Square ◽  
Hordeum Vulgare L ◽  
Brassica Napus L ◽  
Area Index ◽  
Active Radiation ◽  
The Relationship ◽  
Quadratic Models

Canopy characterization is essential for describing the interaction of a crop with its environment. The goal of this work was to determine the relationship between leaf area index (LAI) and ground cover (GC) in a grass, a legume and a crucifer crop, and to assess the feasibility of using these relationships as well as LAI-2000 readings to estimate LAI. Twelve plots were sown with either barley (Hordeum vulgare L.), vetch (Vicia sativa L.), or rape (Brassica napus L.). On 10 sampling dates the LAI (both direct and LAI-2000 estimations), fraction intercepted of photosynthetically active radiation (FIPAR) and GC were measured. Linear and quadratic models fitted to the relationship between the GC and LAI for all of the crops, but they reached a plateau in the grass when the LAI > 4. Before reaching full cover, the slope of the linear relationship between both variables was within the range of 0.025 to 0.030. The LAI-2000 readings were linearly correlated with the LAI but they tended to overestimation. Corrections based on the clumping effect reduced the root mean square error of the estimated LAI from the LAI-2000 readings from 1.2 to less than 0.50 for the crucifer and the legume, but were not effective for barley.  

EFFECT OF ALTERING PLANT DENSITY ON GROWTH CHARACTERISTICS OF SUMMER RAPE

1990 ◽  
Vol 70 (1) ◽  
pp. 139-149 ◽  
Author(s):  
M. J. MORRISON ◽  
P. B. E. McVETTY ◽  
R. SCARTH
Keyword(s):  
Brassica Napus ◽  
Leaf Area ◽  
Growth Analysis ◽  
Plant Density ◽  
Dry Weight ◽  
Growth Characteristics ◽  
Row Spacing ◽  
Vegetative Development ◽  
Brassica Napus L ◽  
Area Index

The effect of 15- and 30-cm row spacings and 1.5, 3.0, 6.0 and 12.0 kg ha−1 seeding rates on growth characteristics, as measured by growth analysis, of summer rape (Brassica napus L.) was studied under southern Manitoba growing conditions. Growing degree days (GDD) was used in the growth analysis formulae as a measurement of time. Over all seeding rates, summer rape grown in rows spaced 15 cm apart produced more dry weight (W), a greater leaf area index (LAI) and a greater leaf area duration (LAD) than when grown in rows spaced 30 cm apart. The 15-cm row spacing treatments had a higher crop growth rate (CGR) and a greater net assimilation rate (NAR) than the 30-cm row spacing treatments. Summer rape grown at seeding rates of 6.0 and 12.0 kg ha−1 had a greater W, LAI and LAD during vegetative development than summer rape grown at seeding rates of 1.5 and 3.0 kg ha−1. This was primarily due to increased plant density. After flowering there were no differences for W, LAI and LAD attributable to differences in seeding rates. Summer rape grown at seeding rates of 6.0 and 12.0 kg ha−1 had a lower CGR and NAR during flowering than that grown at 1.5 and 3.0 kg ha−1 seeding rates indicating that plants produced from lower seeding rates were more photosynthetically efficient than plants produced from higher seeding rates.Key words: Brassica napus, growth analysis, row spacing, seeding rates, rape (summer)

scholarly journals Analogy-Based Crop Yield Forecasts Based on Temporal Similarity of Leaf Area Index

2021 ◽  
Vol 13 (16) ◽  
pp. 3069
Author(s):  
Yadong Liu ◽  
Junhwan Kim ◽  
David H. Fleisher ◽  
Kwang Soo Kim
Keyword(s):  
Time Series ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Crop Yield ◽  
Satellite Data ◽  
Growing Season ◽  
Environmental Data ◽  
Area Index ◽  
Current Season ◽  
Wide Range

Seasonal forecasts of crop yield are important components for agricultural policy decisions and farmer planning. A wide range of input data are often needed to forecast crop yield in a region where sophisticated approaches such as machine learning and process-based models are used. This requires considerable effort for data preparation in addition to identifying data sources. Here, we propose a simpler approach called the Analogy Based Crop-yield (ABC) forecast scheme to make timely and accurate prediction of regional crop yield using a minimum set of inputs. In the ABC method, a growing season from a prior long-term period, e.g., 10 years, is first identified as analogous to the current season by the use of a similarity index based on the time series leaf area index (LAI) patterns. Crop yield in the given growing season is then forecasted using the weighted yield average reported in the analogous seasons for the area of interest. The ABC approach was used to predict corn and soybean yields in the Midwestern U.S. at the county level for the period of 2017–2019. The MOD15A2H, which is a satellite data product for LAI, was used to compile inputs. The mean absolute percentage error (MAPE) of crop yield forecasts was <10% for corn and soybean in each growing season when the time series of LAI from the day of year 89 to 209 was used as inputs to the ABC approach. The prediction error for the ABC approach was comparable to results from a deep neural network model that relied on soil and weather data as well as satellite data in a previous study. These results indicate that the ABC approach allowed for crop yield forecast with a lead-time of at least two months before harvest. In particular, the ABC scheme would be useful for regions where crop yield forecasts are limited by availability of reliable environmental data.

Hyperspectral characteristics and leaf area index monitoring of rice (Oryza sativa L.) under carbon dioxide concentration enrichment

2021 ◽  
Vol 54 (3) ◽  
pp. 231-243
Author(s):  
Chao Liu ◽  
Zhenghua Hu ◽  
Rui Kong ◽  
Lingfei Yu ◽  
Yuanyuan Wang ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Oryza Sativa ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Oryza Sativa L ◽  
Carbon Dioxide Concentration ◽  
Area Index
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