In-Season Prediction of Corn Grain Yield Potential Using Normalized Difference Vegetation Index

2006 ◽  
Vol 98 (6) ◽  
pp. 1488-1494 ◽  
Author(s):  
R. K. Teal ◽  
B. Tubana ◽  
K. Girma ◽  
K. W. Freeman ◽  
D. B. Arnall ◽  
...  
Keyword(s):  
Grain Yield ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Yield Potential ◽  
Corn Grain ◽  
Corn Grain Yield

Estimating Rice Grain Yield Potential Using Normalized Difference Vegetation Index

2011 ◽  
Vol 103 (6) ◽  
pp. 1717-1723 ◽  
Author(s):  
D. L. Harrell ◽  
B. S. Tubaña ◽  
T. W. Walker ◽  
S. B. Phillips
Keyword(s):  
Grain Yield ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Yield Potential ◽  
Rice Grain

scholarly journals Effect of plant row spacing and herbicide use on weed aboveground biomass and corn grain yield

2006 ◽  
Vol 24 (2) ◽  
pp. 287-293 ◽  
Author(s):  
H.A. Acciares ◽  
M.S. Zuluaga
Keyword(s):  
Grain Yield ◽  
Interspecific Competition ◽  
Aboveground Biomass ◽  
Yield Potential ◽  
Photon Flux ◽  
Row Spacing ◽  
Use Of Resources ◽  
Narrow Row ◽  
Corn Grain ◽  
Corn Grain Yield

The use of narrow plant spacing in corn (Zea mays) has been suggested as a technological alternative to obtain grain yield increases, due to a better use of resources. The regular pattern could diminish intraspecific competition while favoring interspecific competition with weeds. The objective of this study was to analyze the effect of corn row spacing on weed aboveground biomass and corn grain yield. Field experiments were conducted during 2002/2003 and 2003/2004 growing seasons. Three corn hybrids with two-row width (0.70 and 0.35 m) were tested. A greater photosynthetic photon flux density (PPFD) interception with a lower weed aboveground dry matter in narrow row arrangement was obtained. Corn grain yield was greater in the narrow row arrangement than in the wide row spacing. This increase in grain yield was related to a better resource use that allows for a reduced interspecific competition. The use of reduced spatial arrangement appeared to be an interesting alternative to increase both the grain yield potential and corn suppressive ability against weeds in corn dryland production systems.

scholarly journals Use of optical sensor for in-season nitrogen management and grain yield prediction in maize

2015 ◽  
Vol 1 (1) ◽  
pp. 64-70 ◽  
Author(s):  
Bandhu Raj Baral ◽  
Parbati Adhikari
Keyword(s):  
Grain Yield ◽  
Optical Sensors ◽  
Precision Agriculture ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Winter Season ◽  
Strong Relationship ◽  
Yield Potential ◽  
Yield Response ◽  
Exponential Relationship

Precision agriculture technologies have developed optical sensors which can determine plant’s normalized difference vegetation index (NDVI).To evaluate the relationship between maize grain yield and early season NDVI readings, an experiment was conducted at farm land of National Maize Research Program, Rampur, Chitwan during winter season of 2012. Eight different levels of N 0, 30, 60, 90, 120, 150, 180 and 210 kg N/ha were applied for hybrid maize RML 32 × RML 17 to study grain yield response and NDVI measurement. Periodic NDVI was measured at 10 days interval from 55 days after sowing (DAS) to 115 DAS by using Green seeker hand held crop sensor. Periodic NDVI measurement taken at a range of growing degree days (GDD) was critical for predicting grain yield potential. Poor exponential relationship existed between NDVI from early reading measured before 208 GDD (55 DAS) and grain yield. At the 261GDD (65DAS) a strong relationship (R2 = 0.70) was achieved between NDVI and grain yield. Later sensor measurements after 571 GDD (95DAS) failed to distinguish variation in green biomass as a result of canopy closure. N level had significantly influenced on NDVI reading, measured grain yield, calculated in season estimated yield (INSEY), predicted yield with added N (YPN), response index (RI) and grain N demand. Measuring NDVI reading by GDD (261–571 GDD) allow a practical window of opportunity for side dress N applications. This study showed that yield potential in maize could be accurately predicted in season with NDVI measured with the Green Seeker crop sensor.Journal of Maize Research and Development (2015) 1(1):64-70DOI: http://dx.doi.org/10.5281/zenodo.34261

Vegetation sensors as a tool for plant population identification and corn grain yield estimation

2021 ◽  
Vol 51 ◽  
Author(s):  
André Luis Vian ◽  
Christian Bredemeier ◽  
Maicon Andreo Drum ◽  
João Leonardo Fernandes Pires ◽  
Elizandro Fochesatto
Keyword(s):  
Grain Yield ◽  
Vegetation Index ◽  
Field Experiments ◽  
Plant Density ◽  
Plant Population ◽  
Growth Stages ◽  
Phenological Stages ◽  
Plant Densities ◽  
Corn Grain ◽  
Corn Grain Yield

ABSTRACT The estimated corn grain yield is dependent on plant density and should be monitored from the beginning of its development, especially between the phenological stages V3 and V10, since these stages are more responsive to management strategies. This study aimed to evaluate the efficiency of two methods [normalized difference vegetation index (NDVI) and plant occupation index (POI)] to estimate the density of corn plants, in order to identify the plant population in different phenological stages and corn grain yield. Two field experiments were conducted in two crop seasons and treatments consisted of four plant densities (4, 6, 8 and 10 plants m-2). The NDVI measurements of the vegetative canopy were performed in the growth stages V4, V5, V6, V7, V8 and V9 (2014) and V3, V5, V6, V8, V9, V10 and V13 (2015/2016). For the POI, the measurements were performed in the stages V5, V6, V8 and V9, in both crop seasons. The different plant densities were efficient in generating variability in the NDVI and POI values throughout the corn crop development cycle, and both tools were efficient in identifying density variations. It was observed that these tools should be used between the V4 and V9 growth stages.

Response of Corn Grain Yield to Spatial and Temporal Variability in Emergence

Crop Science ◽  
2004 ◽  
Vol 44 (3) ◽  
pp. 847 ◽  
Author(s):  
Weidong Liu ◽  
Matthijs Tollenaar ◽  
Greg Stewart ◽  
William Deen
Keyword(s):  
Grain Yield ◽  
Temporal Variability ◽  
Spatial And Temporal Variability ◽  
Corn Grain ◽  
Corn Grain Yield

scholarly journals Relationship between MODIS Derived NDVI and Yield of Cereals for Selected European Countries

Agronomy ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 340
Author(s):  
Ewa Panek ◽  
Dariusz Gozdowski
Keyword(s):  
Linear Regression ◽  
Grain Yield ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Arable Land ◽  
Early Spring ◽  
European Countries ◽  
Yield Prediction ◽  
Country Level ◽  
Using Data

In this study, the relationships between normalized difference vegetation index (NDVI) obtained based on MODIS satellite data and grain yield of all cereals, wheat and barley at a country level were analyzed. The analysis was performed by using data from 2010–2018 for 20 European countries, where percentage of cereals is high (at least 35% of the arable land). The analysis was performed for each country separately and for all of the collected data together. The relationships between NDVI and cumulative NDVI (cNDVI) were analyzed by using linear regression. Relationships between NDVI in early spring and grain yield of cereals were very strong for Croatia, Czechia, Germany, Hungary, Latvia, Lithuania, Poland and Slovakia. This means that the yield prediction for these countries can be as far back as 4 months before the harvest. The increase of NDVI in early spring was related to the increase of grain yield by about 0.5–1.6 t/ha. The cumulative of averaged NDVI gives more stable prediction of grain yield per season. For France and Belgium, the relationships between NDVI and grain yield were very weak.

Assessing the impact of agricultural field traffic on corn grain yield using remote sensing and machine learning

2021 ◽  
Vol 208 ◽  
pp. 104880
Author(s):  
Sami Khanal ◽  
Andrew Klopfenstein ◽  
Kushal KC ◽  
Venkatesh Ramarao ◽  
John Fulton ◽  
...  
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Grain Yield ◽  
Agricultural Field ◽  
The Impact ◽  
Corn Grain ◽  
Corn Grain Yield

GRAIN YIELD COMPARISON OF PURE STANDS AND MIXTURES OF DIFFERENT PROPORTIONS FOR TWO HYBRIDS OF MAIZE

1985 ◽  
Vol 65 (3) ◽  
pp. 481-485 ◽  
Author(s):  
G. J. HOEKSTRA ◽  
L. W. KANNENBERG ◽  
B. R. CHRISTIE
Keyword(s):  
Zea Mays ◽  
Grain Yield ◽  
Zea Mays L ◽  
Pure Stand ◽  
Higher Plant ◽  
Data Support ◽  
Plant Densities ◽  
The Difference ◽  
Corn Grain ◽  
Corn Grain Yield

The objective of this study was to determine the effects on grain yield of growing cultivars in mixtures of different proportions. Two maize (Zea mays L.) hybrids, Pride 116 and United 106, were grown for 2 yr in pure stand and in seven mixtures of different proportions (7:1, 6:2, 5:3, 4:4, 3:5, 2:6, 1:7) at plant densities of 61 500, 99 400, and 136 000 plants per hectare. The total number of mixture combinations was 42, i.e. 2 years × three densities × seven proportions. All but one mixture yielded as expected based on the yield of component hybrids in pure stand. The higher yielding hybrid (United 106) yielded significantly less grain per plant in mixtures than in pure stand. The lower yielding hybrid (Pride 116) yielded more in mixtures than in pure stand, although the difference was not significant. These data support previous observations that the ability of a hybrid to yield in pure stands is not necessarily related to its ability to yield in mixtures. High plant densities appear to enhance the likelihood of interactions occurring among hybrids. For United 106, the number of proportions yielding less grain per plant than in pure stand was highly significant at the two higher plant densities. For Pride 116, the number of proportions yielding more than in pure stand was highly significant at the highest plant density.Key words: Corn, grain yield, mixtures of different proportions, high plant densities, Zea mays

Analysis of genotypic variation for normalized difference vegetation index and its relationship with grain yield in winter wheat under terminal heat stress

2012 ◽  
Vol 131 (6) ◽  
pp. 716-721 ◽  
Author(s):  
Shahnoza Hazratkulova ◽  
Ram C. Sharma ◽  
Safar Alikulov ◽  
Sarvar Islomov ◽  
Tulkin Yuldashev ◽  
...  
Keyword(s):  
Heat Stress ◽  
Winter Wheat ◽  
Grain Yield ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Genotypic Variation ◽  
Terminal Heat Stress
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