Field Competition between Ivyleaf Morningglory (Ipomea hederacea) and Soybeans (Glycine max)

Weed Science ◽  
1984 ◽  
Vol 32 (3) ◽  
pp. 364-370 ◽  
Author(s):  
Ronald C. Cordes ◽  
Thomas T. Bauman
Keyword(s):  
Soil Moisture ◽  
Glycine Max ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Dry Weight ◽  
Growth And Yield ◽  
Yield Reduction ◽  
Area Index ◽  
Soybean Yield ◽  
Competition Effects

Detrimental effects on growth and yield of soybeans [Glycine max(L.) Merr. ‘Amsoy 77′] from density and duration of competition by ivyleaf morningglory [Ipomea hederacea(L.) Jacq. ♯3IPOHE] was evaluated in 1981 and 1982 near West Lafayette, IN. Ivyleaf morningglory was planted at densities of 1 plant per 90, 60, 30, and 15 cm of row in 1981 and 1 plant per 60, 30, 15, and 7.5 cm of row in 1982. Each density of ivyleaf morningglory competed for 22 to 46 days after emergence and the full season in 1981, and for 29 to 60 days after emergence and the full season in 1982. The best indicators of competition effects were leaf area index, plant dry weight, and yield of soybeans. Ivyleaf morningglory was more competitive during the reproductive stage of soybean growth. Photosynthetic irradiance and soil moisture measurements indicated that ivyleaf morningglory does not effectively compete for light or soil moisture. All densities of ivyleaf morningglory could compete with soybeans for 46 and 60 days after emergence in 1981 and 1982, respectively, without reducing soybean yield. Full-season competition from densities of 1 ivyleaf morningglory plant per 15 cm of row significantly reduced soybean yield by 36% in 1981 and 13% in 1982. The magnitude of soybean growth and yield reduction caused by a given density of ivyleaf morningglory was greater when warm, early season temperatures favored rapid weed development.

scholarly journals Nodulation, Growth and Yield of Soybean [Glycine max (L.) Merrill] as Influenced by Biofertilizer and Inorganic Fertilizers in Assosa Zone, Western Ethiopia

2021 ◽  
Author(s):  
Abiyot Abeje ◽  
Getachew Alemayehu ◽  
Tesfaye Feyisa
Keyword(s):  
Glycine Max ◽  
Grain Yield ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Growth And Yield ◽  
Inorganic Fertilizers ◽  
Area Index ◽  
Plant Leaf ◽  
Glycine Max L ◽  
Western Ethiopia

Background: The productivity of soybean in Assosa Zone particularly in Assosa and Bambassi districts is very low due to poor soil fertility management practices which resulted in severe soil acidity and low N-fixing inoculant in the soil. Hence, this experiment was conducted to evaluate the influence of biofertilizer and inorganic fertilizers on nodulation, growth and yield of soybean [Glycine max (L.) Merrill]. Methods: During the period 2019-2020 factorial combinations of four levels of biofertilizer inoculants [without inoculant (B1), SB12 inoculant (B2), MAR1495 inoculant (B3) and SB12 plus MAR1495 inoculants (B4); and four inorganic fertilizer types NP (F1), NPS (F2), NPB (F3) and NPSB (F4) at their recommended rates for soybean] were laid out in a randomized complete block design (RCBD) with three replications in Assosa and Bambassi districts, Assosa Zone, Western Ethiopia. Number of effective nodules per plant, leaf area index and grain yield were collected following the standard procedures and were analyzed using SAS software version 9.1.3 and significant mean differences were separated using Duncan’s multiple range test (DMRT) at 5% significance level. Result: Number of effective nodules per plant, leaf area index and grain yield were highly significantly (P less than 0.01) affected by the interactions of biofertilizer and inorganic fertilizers at both locations and years. Thus, the maximum grain yield (2621.67 kg) was obtained from (SB12+MAR1495) + NPSB at Assosa and the maximum grain yield (2460.20 kg) was obtained from SB12+NPS at Bambassi. Hence, (SB12+MAR1495) + NPSB and SB12+NPS are recommended for higher soybean grain yield for Assosa and Bambassi districts and similar agro-ecologies, respectively.

Field Competition Between Tall Morningglory and Soybean. I. Growth Analysis

Weed Science ◽  
1976 ◽  
Vol 24 (5) ◽  
pp. 482-488 ◽  
Author(s):  
L. R. Oliver ◽  
R. E. Frans ◽  
R. E. Talbert
Keyword(s):  
Growth Rate ◽  
Glycine Max ◽  
Intraspecific Competition ◽  
Growth Analysis ◽  
Dry Weight ◽  
Yield Reduction ◽  
Area Index ◽  
Crop Growth Rate ◽  
Soybean Yield ◽  
Ipomoea Purpurea

The intraspecific (competition between same species) and interspecific (competition between different species) competitiveness of tall morningglory [Ipomoea purpurea(L.) Roth] in soybeans [Glycine max(L.) Merr.] was evaluated for 3 yr at Fayetteville, Arkansas. Tall morningglory was planted at densities of one plant per 61, 30, and 15 cm of row, and competition duration ranged from 2 weeks to full-season. Soybeans were more competitive than tall morningglory for the first 6 to 8 weeks after emergence. The competitiveness of tall morningglory was dependent upon a rapid increase in photosynthetic area which occurred 4 to 6 weeks after emergence. Reductions in leaf area index (LAI) or plant dry weight and crop growth rate (CGR) of soybeans were closely correlated to percent soybean yield reduction. Tall morningglory could remain in soybeans for 12, 10, and 6 weeks without significantly reducing soybean yield at one plant per 61, 30, and 15 cm of row, respectively. Tall morningglory was three to four times more competitive during the soybean reproductive stage than during the vegetative stage.

scholarly journals Nodulation, Growth, and Yield of Soybean (Glycine max L. Merrill) as Affected by Bio-, Organic, and Inorganic NPSB Fertilizers, and Lime in Assosa Zone, Western Ethiopia

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Abiyot Abeje ◽  
Getachew Alemayehu ◽  
Tesfaye Feyisa
Keyword(s):  
Glycine Max ◽  
Grain Yield ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Block Design ◽  
Cattle Manure ◽  
Organic Fertilizers ◽  
Growth And Yield ◽  
Area Index ◽  
Glycine Max L

The productivity of soybean in Assosa Zone particularly in Assosa and Bambassi districts is very low due to poor soil fertility management practices that resulted in severe soil acidity and low N-fixing inoculants in the soil. Hence, this experiment was conducted during the main cropping season of 2019 and 2020 in Assosa and Bambassi districts to evaluate the effect of biofertilizers, organic fertilizers, inorganic NPSB fertilizers, and lime on nodulation, growth, and yield of soybean (Glycine max L. Merrill). Factorial combinations of two biofertilizer inoculants (without biofertilizer (B1) and SB12 plus MAR1495 biofertilizers at their recommended rates of 500 g·ha−1 (B2); two organic fertilizers: without fresh cattle manure (M1) and fresh cattle manure at 10 t·ha−1 (M2); two lime rates: without lime (L1) and lime at 5 t·ha−1 (L2); two inorganic NPSB fertilizers: NPSB at 9.5-23-3.5-0.05 (F1) and NPSB at 19-46-7-0.1 (F2) at their recommended rates for soybean) were laid out in a randomized complete block design with three replications. Effective nodules, leaf area index, and grain yield were collected and analyzed using SAS 9.1.3 software. Results of the experiment showed that effective nodules, leaf area index, grain yield, bulk density, pH, total nitrogen, available phosphorus, organic carbon, and cation exchange capacity were highly ( P < 0.01 ) affected by the interaction of bio-, organic, and inorganic fertilizers and lime at both locations and years. Across all treatments, the grain yield of soybean was increased in the second year, while it was lowest in the first year at both locations. Finally, the interaction of SB12 + MAR1495, 10 t·ha−1 fresh cattle manure, without lime, and NPSB at 19-46-7-0.1 increased the grain yield of soybean in both Assosa and Bambassi districts and should be adopted appropriately to enhance the productivity of soybean in the areas and similar agroecologies, while the interaction effect of SB12 + MAR1495, 10 t ha−1 FCM, 5 t·ha−1 lime, and NPSB at 19-46-7-0.1 improved soil physicochemical properties in both the districts and similar agroecologies.

scholarly journals Growth and yield of wheat at different dates of sowing under chrland ecosystem of Bangladesh

2017 ◽  
Vol 14 (2) ◽  
pp. 147-154 ◽  
Author(s):  
MM Kamrozzaman ◽  
MAH Khan ◽  
S Ahmed ◽  
N Sultana
Keyword(s):  
Growth Rate ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Dry Matter ◽  
Block Design ◽  
Grain Filling ◽  
Crop Growth ◽  
Growth And Yield ◽  
Area Index ◽  
Crop Growth Rate

An experiment was conducted at Sadipur charland under Farming System Research and Development Site, Hatgobindapur, Faridpur, during rabi season of 2012-13 and 2013-14 to study the growth and yield performance of cv. BARI Gom-24 as affected by different dates of sowing under Agro-ecological Zone-12 (AEZ-12) of Bangladesh. The experiment was laid out in randomized complete block design with six replications, comprising five different dates of sowing viz. November 5, November 15, November 25, December 5 and December 15. Results reveal that the tallest plant, leaf area index, total dry matter, and crop growth rate were observed in November 25 sown crop and leaf area index, total dry matter and crop growth rate were higher at booting, grain filling, and tillering stages of the crop. Maximum effective tillers hill-1 (3.49), spikes m-2, (311), number of grains spike-1 (42.20) and 1000-grain weight (52.10 g) were produced by November 25 sown crop exhibited the highest grain (4.30 t ha-1) and straw yield (4.94 t ha-1) as well as harvest index (46.88%) of the crop. Lowest performance was observed both in early (November 5) and late sown crop (December 15). The overall results indicated that November 25 sown crop showed better performance in respect of growth and yield of wheat under charland ecosystem of Bangladesh.J. Bangladesh Agril. Univ. 14(2): 147-154, December 2016

scholarly journals Extracting Leaf Area Index Using Viewing Geometry Effects - A New Perspective on High-Resolution Unmanned Aerial System Photography.

2020 ◽  
Author(s):  
Lukas Roth ◽  
Helge Aasen ◽  
Achim Walter ◽  
Frank Liebisch
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Plant Ecology ◽  
Growth And Yield ◽  
Unmanned Aerial System ◽  
Area Index ◽  
Handheld Device ◽  
Gap Fraction ◽  
Rgb Images ◽  
New Perspective

Abstract Extraction of leaf area index (LAI) is an important prerequisite in numerous studies related to plant ecology, physiology and breeding. LAI is indicative for the performance of a plant canopy and of its potential for growth and yield. In this study, a novel method to estimate LAI based on RGB images taken by an unmanned aerial system (UAS) is introduced. Soybean was taken as the model crop of investigation. The method integrates viewing geometry information in an approach related to gap fraction theory. A 3-D simulation of virtual canopies helped developing and verifying the underlying model. In addition, the method includes techniques to extract plot based data from individual oblique images using image projection, as well as image segmentation applying an active learning approach. Data from a soybean field experiment were used to validate the method. The thereby measured LAI 14 prediction accuracy was comparable with the one of a gap fraction-based handheld device (R2 of 0.92, RMSE of 0.42 m2 m2) and correlated well with destructive LAI measurements (R2 of 0.89, RMSE of 0.41 m2 m2). These results indicate that, if respecting the range (LAI ≤3) the method was tested for, extracting LAI from UAS derived RGB images using viewing geometry information represents a valid alternative to destructive and optical handheld device LAI measurements in soybean. Thereby, we open the door for automated, high-throughput assessment of LAI in plant and crop science.

scholarly journals Growth And Yield of Sorghum (Sorghum bicolor (L.) Moench) Varities in Sokoto Sudan Savanna of Nigeria

2021 ◽  
Vol 25 (8) ◽  
pp. 1513-1518
Author(s):  
A.S. Gunu ◽  
M. Musa
Keyword(s):  
Leaf Area ◽  
Block Design ◽  
Dry Weight ◽  
Growth And Yield ◽  
Area Index ◽  
Days To Heading ◽  
Number Of Leaves ◽  
Total Dry Weight ◽  
Sudan Savanna ◽  
Stalk Weight

Field trial was carried out during the 2019 rainy season (June to October) at the Dryland Teaching and Research Farm of the Faculty of Agriculture, Usmanu Danfodiyo University, Sokoto to determine the growth and yield of sorghum varieties in the study area. The treatments consisted of five (5) sorghum varieties (Samsorg 45, Samsorg 46, Janjari, Yartawa and Jardawa), the treatments were laid out in a Randomized Complete Block Design (RCBD) replicated three (3) times. Data were collected on the growth and yield of the crop. Janjari and Jardawa varieties were higher in plant height. Jardawa and Yartawa varieties were higher in number of leaves. Janjari and Yartawa varieties were higher in total dry weight. Janjari, Jardawa and Yartawa varieties were higher in harvest index. Yartawa variety was higher in leaf area, leaf area index and 1000-grain weight. Jardawa variety was higher in panicle length. Janjari variety was early in number of days to heading, flowering, and maturity and was higher in dry stalk weight. The grain yield (249 – 1506kg ha-1 ) was higher in Janjari and Yartawa varieties (1268 – 1506 kg ha-1). Based on the findings of this research, it could be concluded that Janjari and Yartawa varieties performed better than other varieties in the study area.

Integrating remote sensing and climate data with process-based models to map forest productivity within west-central Alberta's boreal forest: Ecoleap-West

2006 ◽  
Vol 82 (2) ◽  
pp. 159-176 ◽  
Author(s):  
R J Hall ◽  
F. Raulier ◽  
D T Price ◽  
E. Arsenault ◽  
P Y Bernier ◽  
...  
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Management Practices ◽  
Forest Productivity ◽  
Process Models ◽  
Growth And Yield ◽  
Area Index ◽  
Study Region

Forest yield forecasting typically employs statistically derived growth and yield (G&Y) functions that will yield biased growth estimates if changes in climate seriously influence future site conditions. Significant climate warming anticipated for the Prairie Provinces may result in increased moisture deficits, reductions in average site productivity and changes to natural species composition. Process-based stand growth models that respond realistically to simulated changes in climate can be used to assess the potential impacts of climate change on forest productivity, and hence can provide information for adapting forest management practices. We present an application of such a model, StandLEAP, to estimate stand-level net primary productivity (NPP) within a 2700 km2 study region in western Alberta. StandLEAP requires satellite remote-sensing derived estimates of canopy light absorption or leaf area index, in addition to spatial data on climate, topography and soil physical characteristics. The model was applied to some 80 000 stand-level inventory polygons across the study region. The resulting estimates of NPP correlate well with timber productivity values based on stand-level site index (height in metres at 50 years). This agreement demonstrates the potential to make site-based G&Y estimates using process models and to further investigate possible effects of climate change on future timber supply. Key words: forest productivity, NPP, climate change, process-based model, StandLEAP, leaf area index, above-ground biomass

A study of growth in swards of timothy and meadow fescue. I. Uninterrupted growth

1958 ◽  
Vol 51 (3) ◽  
pp. 347-352 ◽  
Author(s):  
R. H. M. Langer
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Leaf Size ◽  
Dry Weight ◽  
Meadow Fescue ◽  
Area Index ◽  
Relative Growth ◽  
Relative Growth Rates ◽  
Number Of Leaves ◽  
Total Dry Weight

1. Swards of S. 48 timothy and S. 215 meadow fescue growing alone or together were sampled at intervals of 3 weeks throughout the season. The number and weight of leaves, stems and ears were determined, and leaf area was estimated.2. Despite high rainfall, the total number of tillers in both species declined from the beginning of the experiment until early July, but increased again from then onwards until the original complement had been approximately restored. The number of leaves failed to show a corresponding increase in the autumn because each tiller carried fewer leaves than earlier in the year.3. In the spring total dry weight increased more rapidly in meadow fescue than in timothy which in turn out-yielded meadow fescue later in the season. Both species attained their greatest dry weight soon after ear emergence, a period which was marked by considerable crop growth and relative growth rates.4. Leaf area index reached a maximum before total dry weight had increased to its highest level, but then declined in both species. Meadow fescue differed from timothy by producing a second crop of foliage after the summer with a leaf area index of about 7. This second rise appeared to be due mainly to increased leaf size in contrast to timothy whose leaves became progressively smaller towards the end of the season.5. The differences in growth between the species discussed with reference to their dates of ear emergence which in this experiment differed by about 6 weeks.

Influence of different organic manures on growth, yield and mineral nutrient accumulation in lettuce (Lactuca sativa L.)

2021 ◽  
Vol 30 (2) ◽  
pp. 159-168
Author(s):  
Shabnur Chowdhury ◽  
MK Rahman
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Lactuca Sativa ◽  
Dry Weight ◽  
Organic Manure ◽  
Leaf Number ◽  
Nutrient Accumulation ◽  
Area Index ◽  
Organic Manures ◽  
Lactuca Sativa L

Effects of organic manures on growth and yield of lettuce (Lactuca sativa L.) and nutrient accumulation in its leaves was examined. The experiment was conducted in a completely randomized design (CRD) replicated thrice with ten treatments involving nine organic manures and a control treatment. Growth parameters viz. plant height, leaf number, leaf length, leaf area, leaf area index and fresh and dry weight of leaf, stem and root were assessed. The highest height (23.69 cm), longest leaf (32.18cm), leaf area (5883.43cm2), leaf area index (6.434), fresh weight (85.41 g) and dry weight (42.73 g) were found in Payel organic manure. The maximum leaf number (27) was recorded in Approshika organic manure. The maximum content of nitrogen (6.12%), phosphorus (1.83%), potassium (4.11%) and Sulphur (1.69%) were observed in Payel organic manure. The best growth performance and nutrient accumulation was observed in Payel organic manure. Dhaka Univ. J. Biol. Sci. 30(2): 159-168, 2021 (July)

scholarly journals Watershed Modeling with Remotely Sensed Big Data: MODIS Leaf Area Index Improves Hydrology and Water Quality Predictions

2020 ◽  
Vol 12 (13) ◽  
pp. 2148 ◽  
Author(s):  
Adnan Rajib ◽  
I Luk Kim ◽  
Heather E. Golden ◽  
Charles R. Lane ◽  
Sujay V. Kumar ◽  
...  
Keyword(s):  
Water Quality ◽  
Soil Moisture ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Vegetation Dynamics ◽  
Watershed Modeling ◽  
Remotely Sensed ◽  
Area Index ◽  
Daily Streamflow ◽  
Modis Lai

Traditional watershed modeling often overlooks the role of vegetation dynamics. There is also little quantitative evidence to suggest that increased physical realism of vegetation dynamics in process-based models improves hydrology and water quality predictions simultaneously. In this study, we applied a modified Soil and Water Assessment Tool (SWAT) to quantify the extent of improvements that the assimilation of remotely sensed Leaf Area Index (LAI) would convey to streamflow, soil moisture, and nitrate load simulations across a 16,860 km2 agricultural watershed in the midwestern United States. We modified the SWAT source code to automatically override the model’s built-in semiempirical LAI with spatially distributed and temporally continuous estimates from Moderate Resolution Imaging Spectroradiometer (MODIS). Compared to a “basic” traditional model with limited spatial information, our LAI assimilation model (i) significantly improved daily streamflow simulations during medium-to-low flow conditions, (ii) provided realistic spatial distributions of growing season soil moisture, and (iii) substantially reproduced the long-term observed variability of daily nitrate loads. Further analysis revealed that the overestimation or underestimation of LAI imparted a proportional cascading effect on how the model partitions hydrologic fluxes and nutrient pools. As such, assimilation of MODIS LAI data corrected the model’s LAI overestimation tendency, which led to a proportionally increased rootzone soil moisture and decreased plant nitrogen uptake. With these new findings, our study fills the existing knowledge gap regarding vegetation dynamics in watershed modeling and confirms that assimilation of MODIS LAI data in watershed models can effectively improve both hydrology and water quality predictions.

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