Transformation of Plot Ear Corn Yield to Dry Shelled Grain Yield
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The article presents the results of research on the formation of corn yield for grain depending on the elements of cultivation technology in the Forest-Steppe of Ukraine. The goal of the research was to identify the influence of plant density and fertilizer system on the yield of corn hybrids for grain. The research was conducted during 2017-2019 in the research field of Bila Tserkva National Agrarian University (Bila Tserkva NAU). Research methods: field, calculation and statistical. Results. Regularities of growth, development and formation of yield by plants are revealed, both in concrete conditions of years of researches, and taking into account average long-term values taking into account features of hybrid-oriented technology. According to the results of the experiment it was recorded that the maximum yields for growing early-maturing maize hybrid DN PIVYHA with FAO 180 in general were obtained at a pre-harvest density of 75 thousand units/ha and the use of combined organo-mineral fertilizer system - 11.09 t/ha; medium-early maize hybrid DN ORLYK, FAO 280 in general in the experiment provided a grain yield of 9.60 t/ha, and in terms of 2017 - 7.86 t/ha, in 2018 - 11.22 t/ha and in 2019 - 9, 72 t/ha, but the medium-ripe hybrid of corn DN SARMAT, FAO 380 provided a grain yield of 10.81 t/ha, and in the context of 2017 - 9.31 t/ha, in 2018 - 11.68 t/ha and in 2019 - 11.44 t/ha. Significant influence on the formation of the yield of corn has a hybrid factor (27 %), fertilizer system determines the level of productivity by 21 % and interacts closely with the conditions of the growing season (factor BV 9 %), growing season conditions also determine the level of productivity of corn plants (19 %), and the pre-harvest density determines this feature by 18 %. Conclusions: In the conditions of the Right Bank part of the Forest-Steppe of Ukraine there is an increase in the level of productivity of maize hybrids from early to medium-ripe hybrids, regardless of the influence of other experimental factors.

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Variable-rate in corn sowing for maximizing grain yield

Scientific Reports ◽

10.1038/s41598-021-92238-4 ◽

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.

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One Year Residual Effect of Sewage Sludge Biochar as a Soil Amendment for Maize in a Brazilian Oxisol

Sustainability ◽

10.3390/su13042226 ◽

2021 ◽

Vol 13 (4) ◽

pp. 2226

Author(s):

Joisman Fachini ◽

Thais Rodrigues Coser ◽

Alyson Silva de Araujo ◽

Ailton Teixeira do Vale ◽

Keiji Jindo ◽

...

Keyword(s):

Sewage Sludge ◽

Grain Yield ◽

Nutrient Availability ◽

Pyrolysis Temperature ◽

Residual Effect ◽

Soil Nutrient ◽

Mineral Fertilizer ◽

Corn Yield ◽

Soil Nutrient Availability ◽

One Year

The thermochemical transformation of sewage sludge (SS) to biochar (SSB) allows exploring the advantages of SS and reduces possible environmental risks associated with its use. Recent studies have shown that SSB is nutrient-rich and may replace mineral fertilizers. However, there are still some questions to be answered about the residual effect of SSB on soil nutrient availability. In addition, most of the previous studies were conducted in pots or soil incubations. Therefore, the residual effect of SSB on soil properties in field conditions remains unclear. This study shows the results of nutrient availability and uptake as well as maize yield the third cropping of a three-year consecutive corn cropping system. The following treatments were compared: (1) control: without mineral fertilizer and biochar; (2) NPK: with mineral fertilizer; (3) SSB300: with biochar produced at 300 °C; (4) SSB300+NPK; (5) SSB500: with biochar produced at 500 °C; and (6) SSB500+NPK. The results show that SSB has one-year residual effects on soil nutrient availability and nutrient uptake by maize, especially phosphorus. Available soil P contents in plots that received SSB were around five times higher than the control and the NPK treatments. Pyrolysis temperature influenced the SSB residual effect on corn yield. One year after suspending the SSB application, SSB300 increased corn yield at the same level as the application of NPK. SSB300 stood out and promoted higher grain yield in the residual period (8524 kg ha−1) than SSB500 (6886 kg ha−1). Regardless of pyrolysis temperature, biochar boosted the mineral fertilizer effect resulting in higher grain yield than the exclusive application of NPK. Additional long-term studies should be focused on SSB as a slow-release phosphate fertilizer.

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Poultry Litter, Biochar, and Fertilizer Effect on Corn Yield, Nutrient Uptake, N2O and CO2 Emissions

Environments ◽

10.3390/environments6050055 ◽

2019 ◽

Vol 6 (5) ◽

pp. 55 ◽

Cited By ~ 7

Author(s):

Karamat R. Sistani ◽

Jason R. Simmons ◽

Marcia Jn-Baptiste ◽

Jeff M. Novak

Keyword(s):

Grain Yield ◽

Co2 Emissions ◽

Greenhouse Gas Emission ◽

Poultry Litter ◽

First Year ◽

Corn Yield ◽

Soil Microbial ◽

Significant Difference ◽

Biomass Yields ◽

Corn Productivity

Biochar holds promise as a soil amendment with potential to sequester carbon, improve soil fertility, adsorb organic pollutants, stimulate soil microbial activities, and improve crop yield. We used a hardwood biochar to assess its impact on corn (Zea mays) grain, biomass yields and greenhouse gas emission in central Kentucky, USA. Six treatments included as follows: control (C) with no amendment applied; poultry litter (PL); biochar (B); biochar + poultry litter (B + PL); fertilizers N-P-K (F); and biochar + fertilizers (B + F). Biochar was applied only once to plots in 2010 followed by rototilling all plots. Only PL and fertilizer were applied annually. When applied alone, biochar did not significantly increase dry matter, grain yield, and N-P-K uptake. There was also no significant difference between the combined treatments when compared with PL or F applications alone. We observed a slight increasing trend in corn grain yield in the following 2 years compared to the first year from biochar treatment. Poultry litter treatment produced significantly greater N2O and CO2 emissions, but emissions were lower from the B+PL treatment. We conclude that this biochar did not improve corn productivity in the short term but has potential to increase yield in the long term and may have some benefit when combined with PL or F in reducing N2O and CO2 emissions.

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Weed control in corn and weed sample size for growth evaluations

Planta Daninha ◽

10.1590/s0100-83582014000100006 ◽

2014 ◽

Vol 32 (1) ◽

pp. 51-59 ◽

Cited By ~ 1

Author(s):

L.B. Tavella ◽

P.S.L. Silva ◽

V.R. Oliveira ◽

P.L.O. Fernandes ◽

R.P. Sousa

Keyword(s):

Grain Yield ◽

Sample Size ◽

Weed Control ◽

Block Design ◽

Corn Yield ◽

Weed Growth ◽

Randomized Block Design ◽

Experimental Variation ◽

Yield Values ◽

Viable Seeds

The objectives of this study were to evaluate baby corn yield, green corn yield, and grain yield in corn cultivar BM 3061, with weed control achieved via a combination of hoeing and intercropping with gliricidia, and determine how sample size influences weed growth evaluation accuracy. A randomized block design with ten replicates was used. The cultivar was submitted to the following treatments: A = hoeings at 20 and 40 days after corn sowing (DACS), B = hoeing at 20 DACS + gliricidia sowing after hoeing, C = gliricidia sowing together with corn sowing + hoeing at 40 DACS, D = gliricidia sowing together with corn sowing, and E = no hoeing. Gliricidia was sown at a density of 30 viable seeds m-2. After harvesting the mature ears, the area of each plot was divided into eight sampling units measuring 1.2 m² each to evaluate weed growth (above-ground dry biomass). Treatment A provided the highest baby corn, green corn, and grain yields. Treatment B did not differ from treatment A with respect to the yield values for the three products, and was equivalent to treatment C for green corn yield, but was superior to C with regard to baby corn weight and grain yield. Treatments D and E provided similar yields and were inferior to the other treatments. Therefore, treatment B is a promising one. The relation between coefficient of experimental variation (CV) and sample size (S) to evaluate growth of the above-ground part of the weeds was given by the equation CV = 37.57 S-0.15, i.e., CV decreased as S increased. The optimal sample size indicated by this equation was 4.3 m².

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Green ear yield and grain yield of maize cultivars in competition with weeds

Planta Daninha ◽

10.1590/s0100-83582010000100010 ◽

2010 ◽

Vol 28 (1) ◽

pp. 77-85 ◽

Cited By ~ 5

Author(s):

P.S.L. Silva ◽

K.M.B. Silva ◽

P.I.B. Silva ◽

V.R. Oliveira ◽

J.L.B. Ferreira

Keyword(s):

Grain Yield ◽

Plant Height ◽

Block Design ◽

Corn Yield ◽

Modern Agriculture ◽

Maize Cultivars ◽

Randomized Complete Block Design ◽

Ear Height ◽

Herbicide Use ◽

Ground Part

The reduction in herbicide use is one of the greatest interests for modern agriculture and several alternatives are being investigated with this objective, including the adoption of cultivars that suppress weeds. The objective of this study was to verify if maize cultivars develop differently, in competition with weeds, to produce green ears and grain. Randomized complete block design was used, with split-plots and five replications. Cultivars DKB 390, DKB 466, DKB 350, AG 7000, AG 7575 and Master, were evaluated in the plots, without weeding and two weedings (at 22 and 41 days after sowing) in sub plots. Twenty-one species were identified in the experimental area, the most frequent being Gramineae (Poaceae), Euphorbiaceae, Leguminosae (Fabaceae) and Convolvulaceae species. There was no difference in the dry biomass above-ground part of the weeds in the plots of the evaluated cultivars. The cultivars behaved similarly in treatments with or without hoeing, except for plant height and ear height evaluations. Without hoeing, plant height increased in cultivar DKB 390, while plant height and ear height decreased in cultivar AG 7575. In the other cultivars, these traits did not change under weed control. The presence of weeds decreased the values of all traits employed to assess green corn yield, with the exception of the total number of green ears and grain yield.

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Influence of Weed Density and Distribution on Corn (Zea mays) Yield

Weed Science ◽

10.1017/s0043174500081091 ◽

1995 ◽

Vol 43 (2) ◽

pp. 215-218 ◽

Cited By ~ 19

Author(s):

Mark J. Vangessel ◽

Edward E. Schweizer ◽

Karen A. Garrett ◽

Philip Westra

Keyword(s):

Zea Mays ◽

Grain Yield ◽

Management Model ◽

Yield Reduction ◽

Corn Yield ◽

Weed Population ◽

Weed Density ◽

Weed Distribution ◽

The Impact

The impact of weed density and weed distribution on irrigated corn yield was investigated in Colorado. Weed densities examined were 0,33,50, or 100% of the indigenous weed population. A series of weed distribution treatments were achieved by varying the length of the weed-free and weedy zones within the corn row while maintaining a constant weed population of 33 or 50% of the indigenous weed level. Grain yield was affected by weed density, but not by weed distribution. Each additional weed reduced corn yield 8.5 and 2.3 kg ha−1in 1991 and 1992, respectively. When corn yields were estimated with a computer weed/corn management model, weed densities 5 to 8 wk after planting provided a better yield reduction estimate than weed densities immediately before harvest.

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Application Timing for Weed Control in Corn (Zea mays) with Dicamba Tank Mixtures

Weed Technology ◽

10.1017/s0890037x00045498 ◽

1997 ◽

Vol 11 (3) ◽

pp. 602-607 ◽

Cited By ~ 4

Author(s):

Eric Spandl ◽

Thomas L. Rabaey ◽

James J. Kells ◽

R. Gordon Harvey

Keyword(s):

Zea Mays ◽

Grain Yield ◽

Weed Control ◽

Field Studies ◽

Corn Yield ◽

Application Timing ◽

Common Lambsquarters ◽

Giant Foxtail ◽

Corn Grain ◽

Corn Grain Yield

Optimal application timing for dicamba–acetamide tank mixes was examined in field studies conducted in Michigan and Wisconsin from 1993 to 1995. Dicamba was tank mixed with alachlor, metolachlor, or SAN 582H and applied at planting, 7 d after planting, and 14 d after planting. Additional dicamba plus alachlor tank mixes applied at all three timings were followed by nicosulfuron postemergence to determine the effects of noncontrolled grass weeds on corn yield. Delaying application of dicamba–acetamide tank mixes until 14 d after planting often resulted in lower and less consistent giant foxtail control compared with applications at planting or 7 d after planting. Corn grain yield was reduced at one site where giant foxtail control was lower when application was delayed until 14 d after planting. Common lambsquarters control was excellent with 7 or 14 d after planting applications. At one site, common lambsquarters control and corn yield was reduced by application at planting. Dicamba–alachlor tank mixes applied 7 d after planting provided similar weed control or corn yield, while at planting and 14 d after planting applications provided less consistent weed control or corn yield than a sequential alachlor plus dicamba treatment or an atrazine-based program.

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Interference of Redroot Pigweed (Amaranthus retroflexus) in Corn (Zea mays)

Weed Science ◽

10.1017/s0043174500076967 ◽

1994 ◽

Vol 42 (4) ◽

pp. 568-573 ◽

Cited By ~ 131

Author(s):

Stevan Z. Knezevic ◽

Stephan F. Weise ◽

Clarence J. Swanton

Keyword(s):

Zea Mays ◽

Grain Yield ◽

Seed Production ◽

Field Experiments ◽

Amaranthus Retroflexus ◽

Corn Yield ◽

Leaf Stage ◽

Redroot Pigweed ◽

Emergence Date

Redroot pigweed is a major weed in corn throughout Ontario. Field experiments were conducted at two locations in 1991 and 1992 to determine the influence of selected densities and emergence times of redroot pigweed on corn growth and grain yield. Redroot pigweed densities of 0.5, 1, 2, 4 and 8 plants per m of row were established within 12.5 cm on either side of the corn row. In both years, redroot pigweed seeds were planted concurrently and with corn at the 3- to 5-leaf stage of corn growth. A density of 0.5 redroot pigweed per m of row from the first (earlier) emergence date of pigweed (in most cases, up to the 4-leaf stage of corn) or four redroot pigweed per m of row from the second (later) emergence date of pigweed (in most cases, between the 4- and 7-leaf stage of corn) reduced corn yield by 5%. Redroot pigweed emerging after the 7-leaf stage of corn growth did not reduce yield. Redroot pigweed seed production was dependent upon its density and time of emergence. The time of redroot pigweed emergence, relative to corn, may be more important than its density in assessing the need for postemergence control.

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Effect of Wheat Cover Crop and Split Nitrogen Application on Corn Yield and Nitrogen Use Efficiency

Agronomy ◽

10.3390/agronomy10081081 ◽

2020 ◽

Vol 10 (8) ◽

pp. 1081 ◽

Cited By ~ 6

Author(s):

Oladapo Adeyemi ◽

Reza Keshavarz-Afshar ◽

Emad Jahanzad ◽

Martin Leonardo Battaglia ◽

Yuan Luo ◽

...

Keyword(s):

Grain Yield ◽

Nitrogen Use Efficiency ◽

Cover Crops ◽

Cover Crop ◽

Block Design ◽

Corn Yield ◽

N Losses ◽

Nitrogen Use ◽

N Application ◽

Use Efficiency

Corn (Zea mays L.) grain is a major commodity crop in Illinois and its production largely relies on timely application of nitrogen (N) fertilizers. Currently, growers in Illinois and other neighboring states in the U.S. Midwest use the maximum return to N (MRTN) decision support system to predict corn N requirements. However, the current tool does not factor in implications of integrating cover crops into the rotation, which has recently gained attention among growers due to several ecosystem services associated with cover cropping. A two-year field trail was conducted at the Agronomy Research Center in Carbondale, IL in 2018 and 2019 to evaluate whether split N application affects nitrogen use efficiency (NUE) of corn with and without a wheat (Triticum aestivum L.) cover crop. A randomized complete block design with split plot arrangements and four replicates was used. Main plots were cover crop treatments (no cover crop (control) compared to a wheat cover crop) and subplots were N timing applications to the corn: (1) 168 kg N ha−1 at planting; (2) 56 kg N ha−1 at planting + 112 kg N ha−1 at sidedress; (3) 112 kg N ha−1 at planting + 56 kg N ha−1 at sidedress; and (4) 168 kg N ha−1 at sidedress along with a zero-N control as check plot. Corn yield was higher in 2018 than 2019 reflecting more timely precipitation in that year. In 2018, grain yield declined by 12.6% following the wheat cover crop compared to no cover crop control, indicating a yield penalty when corn was preceded with a wheat cover crop. In 2018, a year with timely and sufficient rainfall, there were no yield differences among N treatments and N balances were near zero. In 2019, delaying the N application improved NUE and corn grain yield due to excessive rainfall early in the season reflecting on N losses which was confirmed by lower N balances in sidedressed treatments. Overall, our findings suggest including N credit for cereals in MRTN prediction model could help with improved N management in the Midwestern United States.

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