Normalized Difference Vegetative Index Used to Identify Spatial Variability in Vegetative Growth and Grain Yield of Corn

2012 ◽  
Vol 11 (1) ◽  
pp. 1-9
Author(s):  
Joshua J. Henik ◽  
Allen D. Knapp ◽  
Kenneth J. Moore ◽  
C. Lee Burras
Keyword(s):  
Spatial Variability ◽  
Grain Yield ◽  
Vegetative Growth ◽  
Normalized Difference Vegetative Index

scholarly journals Variable-rate in corn sowing for maximizing grain yield

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Eder Eujácio da Silva ◽  
Fábio Henrique Rojo Baio ◽  
Daniel Fernando Kolling ◽  
Renato Schneider Júnior ◽  
Alex Rogers Aguiar Zanin ◽  
...  
Keyword(s):  
Grain Yield ◽  
Vegetative Growth ◽  
Maximum Yield ◽  
Influential Factors ◽  
Plant Population ◽  
Seeding Density ◽  
Corn Yield ◽  
Growth Indices ◽  
Experimental Conditions ◽  
Soil Attributes

AbstractSowing density is one of the most influential factors affecting corn yield. Here, we tested the hypothesis that, according to soil attributes, maximum corn productivity can be attained by varying the seed population. Specifically, our objectives were to identify the soil attributes that affect grain yield, in order to generate a model to define the optimum sowing rate as a function of the attributes identified, and determine which vegetative growth indices can be used to predict yield most accurately. The experiment was conducted in Chapadão do Céu-GO in 2018 and 2019 at two different locations. Corn was sown as the second crop after the soybean harvest. The hybrids used were AG 8700 PRO3 and FS 401 PW, which have similar characteristics and an average 135-day cropping cycle. Tested sowing rates were 50, 55, 60, and 65 thousand seeds ha−1. Soil attributes evaluated included pH, calcium, magnesium, phosphorus, potassium, organic matter, clay content, cation exchange capacity, and base saturation. Additionally, we measured the correlation between the different vegetative growth indices and yield. Linear correlations were obtained through Pearson’s correlation network, followed by path analysis for the selection of cause and effect variables, which formed the decision trees to estimate yield and seeding density. Magnesium and apparent electrical conductivity (ECa) were the most important soil attributes for determining sowing density. Thus, the plant population should be 56,000 plants ha−1 to attain maximum yield at ECa values > 7.44 mS m−1. In addition, the plant population should be 64,800 plants ha−1 at values < 7.44 mS m−1 when magnesium levels are greater than 0.13 g kg−1, and 57,210 plants ha−1 when magnesium content is lower. Trial validation showed that the decision tree effectively predicted optimum plant population under the local experimental conditions, where yield did not significantly differ among populations.

FACTORS UNDERLYING GRAIN YIELD SPATIAL VARIABILITY IN THREE IRRIGATED WHEAT FIELDS

1999 ◽  
Vol 42 (5) ◽  
pp. 1187-1202 ◽  
Author(s):  
R. E. Plant ◽  
A. Mermer ◽  
G. S. Pettygrove ◽  
M. P. Vayssieres ◽  
J. A. Young ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Grain Yield ◽  
Irrigated Wheat

Dry Matter, Nodulation and Nutrient Uptake in Chickpea (Cicer arietinum) as Influenced by Irrigation and Phosphorus

1989 ◽  
Vol 25 (3) ◽  
pp. 349-355 ◽  
Author(s):  
S. S. Parihar ◽  
R. S. Tripathi
Keyword(s):  
Grain Yield ◽  
Nutrient Uptake ◽  
Irrigation Water ◽  
Vegetative Growth ◽  
Dry Matter ◽  
Dry Weight ◽  
Irrigation Scheduling ◽  
Dry Matter Accumulation ◽  
Pan Evaporation ◽  
Eastern India

SUMMARYThe response of chickpea to irrigation and phosphorus was studied at Kharagpur in Eastern India. Irrigation scheduling was based on the ratio between irrigation water applied and cumulative pan evaporation (ID/CPE), and had little effect on dry matter accumulation. Increasing the frequency and amount of irrigation reduced the number and dry weight of nodules per plant, which increased to a maximum 70 days after sowing and then declined. Irrigation significantly reduced grain yield as a result of excessive vegetative growth at the expense of pod formation. Application of phosphorus promoted nodulation and increased both nodule dry weight and the concentration of N, P and K in grain and stover. Uptake of N, P and K by the crop was also increased.

Lupin grain yields and fertiliser effectiveness are increased by banding superphosphate below the seed

1991 ◽  
Vol 31 (3) ◽  
pp. 357 ◽  
Author(s):  
RJ Jarvis ◽  
MDA Bolland
Keyword(s):  
Grain Yield ◽  
Vegetative Growth ◽  
Field Experiments ◽  
Soil Surface ◽  
Growing Season ◽  
Lupinus Angustifolius ◽  
Grain Yields ◽  
P Content ◽  
Better Than

Five field experiments with lupins (Lupinus angustifolius) measured the effectiveness, for production, of 4 superphosphate placements either: (i) drilled with the seed to a depth of 4 or 5 cm; (ii) applied to the soil surface (topdressed) before sowing; or (iii) banded 2.5-5 cm and 7.5-8 cm below the seed while sowing. Levels of applied phosphate (P) from 0 to 36 kg P/ha were tested. In all experiments lupin grain yield responded to the highest level of superphosphate applied. At this P level, the average grain yield from all trials was 1.16 t/ha for the deepest banded treatment. This was 0.38 t/ha (49%) better than P drilled with the seed, and 0.62 t/ha (115%) better than P topdressed. Relative to superphosphate drilled with the seed and regardless of the lupin cultivar or the phosphate status of the soil, the effectiveness of superphosphate was increased by 10-90% by banding below the seed, and decreased by 30-60% by topdressing. Increasing the levels of superphosphate drilled with the seed generally reduced the density of seedlings and reduced early vegetative growth, probably due to salt or P toxicity. However, during the growing season, the plants treated with high levels of superphosphate recovered, so that eventually yields of dried tops and grain responded to increasing superphosphate drilled with the seed. In each experiment there was a common relationship between yield and P content in lupin tissue, regardless of how the superphosphate was applied, suggesting that lupins responded solely to P, and other factors did not alter yield. We recommend that farmers band superphosphate 5-8 cm below the seed while sowing, rather than continue the present practices of either drilling the fertiliser with the seed, or topdressing it before sowing.

scholarly journals Correlations of soybean yield with soil porosity and bulk density of an Oxisol

2018 ◽  
Vol 48 (4) ◽  
pp. 476-485
Author(s):  
Sérgio Ricardo Lima Negro ◽  
Diego dos Santos Pereira ◽  
Rafael Montanari ◽  
Flávio Carlos Dalchiavon ◽  
Christtiane Fernandes Oliveira
Keyword(s):  
Spatial Variability ◽  
Grain Yield ◽  
Bulk Density ◽  
Yield Components ◽  
Particle Density ◽  
Soil Porosity ◽  
No Tillage ◽  
Soybean Yield ◽  
Volumetric Flask ◽  
Soil Attributes

ABSTRACT The spatial variability of soil physical attributes is important to indicate management practices that best suit agricultural areas. This study aimed to analyze spatial correlations between soybean grain yield and soil mass-volume relationships, in order to select which attribute is correlated with yield, as well as to evaluate the spatial variability of soil attributes and yield components of this crop, in an Oxisol under no-tillage system. The soil attributes analyzed (0.0-0.10 m and 0.10-0.20 m) were the following ones: soil bulk density (paraffin-coated clod and volumetric ring methods), particle density (volumetric flask and modified volumetric flask methods) and total porosity. The soybean yield components were evaluated as it follows: grain yield, number of pods per plant, number of grains per pod, mass of 100 grains, grain mass per plant, plant population and plant height. The total soil porosity, calculated by the relations between the bulk density (volumetric ring method) and particle density (volumetric flask), in the 0.10-0.20 m layer, was the best indicator of soybean grain yield under no-tillage conditions.

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