scholarly journals Influence of different sowing density in two varieties of maize. Part I. Relation to yielding

2021 ◽  
Vol 58 (2) ◽  
pp. 199-208
Author(s):  
Katarzyna Ambroży-Deręgowska ◽  
Piotr Szulc
Keyword(s):  
Plant Density ◽  
Unit Area ◽  
Weather Conditions ◽  
Stay Green ◽  
First Order ◽  
Growing Seasons ◽  
Maize Varieties ◽  
Order Factor ◽  
Green Mass Yield ◽  
Lower Plant

Summary A study was carried out to determine the effect of sowing density on the yield of maize of two different varieties. The field experiment was carried out in 2012–2014 at the Department of Agronomy of Poznań University of Life Sciences. The first-order factor was the variety: SY Cooky and Drim “stay-green”; the second-order factor was sowing density: 6, 7, 8, 9, 10 plants per m2. Weather conditions during the maize growing seasons significantly influenced the values of the studied traits. Significantly the lowest green mass yield of maize was obtained at the sowing density of 6 plants m−2, and the highest for 10 plants m−2. The “stay-green” variety significantly responded to an increase in sowing density with reduced fresh weight of leaf blades of a single plant compared with the conventional variety. This indicated highly effective photosynthesis with a lower plant density per unit area, which is also the basis for effective absorption of solar radiation for these maize varieties.

Economic optimum plant density of irrigated early-maturity soybean in southern Alberta

2021 ◽  
Author(s):  
Tram T.N. Thai ◽  
Danny G. Le Roy ◽  
Manjula S. Bandara ◽  
James E. Thomas ◽  
Francis J Larney
Keyword(s):  
Plant Density ◽  
Profit Maximization ◽  
Seeding Density ◽  
Early Maturity ◽  
Growing Seasons ◽  
Southern Alberta ◽  
Soybean Genotypes ◽  
Glycine Max L ◽  
The Difference ◽  
Lower Plant

With soybean [Glycine max (L.) Merr.] seed cost increasing in Alberta, understanding economic optimum plant density (EOPD) could help growers save on input expenses. A study was conducted at two irrigated locations in southern Alberta (Bow Island and Lethbridge), in three growing seasons (2014–16), using two maturity group (MG) 00 soybean genotypes, two row spacings (RS; narrow, 17.5 cm; wide, 35 cm), and three seeding densities (SD; 30, 50 and 80 seeds m-2). Exponential plant density-yield relationships were used to estimate EOPD. The earlier MG 00.4 genotype compensated yield at lower plant density (39 vs. 43 plants m-2) and emergence (74 vs. 80%) than the later MG 00.8 genotype. The EOPD gaps between environments, genotypes, and RS were minimal (from 1–3 plants m-2), resulting in only 1.3–2.0% differences in grain yield (37–56 kg ha-1), and gross revenue at EOPD ($16–24 ha-1). The overall EOPD estimate was 46 plants m-2, regardless of environment, genotype or RS. The study highlighted the difference between agronomic production and profit maximization in choosing an optimum plant density, and the need to establish a seeding density calculator for irrigated soybean in southern Alberta.

scholarly journals The Role of Agrotechnical Factors in Shaping the Protein Yield of Maize (Zea mays L.)

2020 ◽  
Vol 12 (17) ◽  
pp. 6833
Author(s):  
Piotr Szulc ◽  
Katarzyna Ambroży-Deręgowska ◽  
Iwona Mejza ◽  
Joanna Kobus-Cisowska ◽  
Marta Ligaj
Keyword(s):  
Field Experiments ◽  
Atmospheric Precipitation ◽  
Weather Conditions ◽  
Protein Yield ◽  
Stay Green ◽  
Growing Seasons ◽  
Two Component ◽  
Maize Protein ◽  
Relationship Of ◽  
Np Fertilizer

The subject of the work was the evaluation of maize protein yield conditioned by various agrotechnical factors. The test results are derived from two different field experiments covering a total of seven years of observation. Protein yield was significantly dependent on changing weather conditions in the growing seasons. Protein yield was significantly lower in the dry and hot years. The sum of precipitation for the month of May was positively correlated with maize protein yield. However, there was no correlation between the average air temperature and the amount of protein yield. The sum of atmospheric precipitation for the entire growing season (IV–X) shaped maize protein yield in over 96%. A non-linear relationship of the 2nd degree was determined between these traits. Sowing maize into the soil cultivated traditionally (autumn tillage), “stay-green” type cultivars and row fertilization positively influenced maize protein yield. Initial fertilization (regardless of depth) with two-component NP fertilizer, in relation to broadcast fertilization, significantly increased maize protein yield from 11.4% to 18%, respectively. The type of nitrogen fertilizer did not differentiate the value of this trait. Pre-sowing nitrogen application was more effective compared to the top dressing, and significantly increased protein yield. Row fertilization with two-component NP fertilizer clearly affected the content protein in grain. The interdependence of genetic and agronomic progress is an important factor shaping the potential of maize protein yield and cannot be attributed to either breeding (cultivar) or agronomy.

scholarly journals Yielding of two types of maize cultivars in relation to selected agrotechnical factors

2019 ◽  
Vol 65 (No. 8) ◽  
pp. 416-423 ◽  
Author(s):  
Małgorzata Jagła ◽  
Piotr Szulc ◽  
Katarzyna Ambroży-Deręgowska ◽  
Iwona Mejza ◽  
Joanna Kobus-Cisowska
Keyword(s):  
Field Experiments ◽  
Weather Conditions ◽  
Fertilizer Application ◽  
Stay Green ◽  
Growing Seasons ◽  
Maize Cultivars ◽  
Clear Result ◽  
The Difference ◽  
Area Unit ◽  
Np Fertilizer

The study presents the results of field experiments, the aim of which was to assess the yield of maize cultivars with different genetic profiles depending on the method of soil preparation for sowing and the method of NP fertilizer application. The yield and water content in the grain were significantly dependent on changing weather conditions in the growing seasons. Sowing maize into the soil cultivated traditionally (autumn ploughing), stay-green type cultivars and row fertilization positively influenced maize yielding. The stay-green cultivar yielded at a higher level compared to the fast maturing cultivar, the difference being significant in the year characterized by unfavourable distribution (deficit) of precipitation in the growing season. The stay-green cultivar reacted favourably to the localized application of NP fertilizer, the clear result of which was the increase in grain yield. Direct maize sowing significantly reduced the number of production ears per surface area unit and the number of grains on the ear. Selection of the stay-green cultivar and row fertilization with NP fertilizer improved this condition.  

The influence of density and nitrogen in seed production stands of S 37 cocksfoot (Dactylis glomerata L.)

1963 ◽  
Vol 61 (3) ◽  
pp. 361-373 ◽  
Author(s):  
D. A. Lambert
Keyword(s):  
Seed Production ◽  
Plant Density ◽  
Unit Area ◽  
The Third ◽  
Plant Densities ◽  
Dactylis Glomerata L ◽  
High Level ◽  
Seed Yields ◽  
Area Percentage ◽  
Lower Plant

1. Seed production stands of S 37 cocksfoot were obtained with varying plant densities by utilizing two drill widths, removing sections of drill, or over-sowing drilled material. All density treatments were operative at two levels of N, 87 or 174 lb. N per acre per annum.2. Tillers in selected quadrats were labelled at monthly intervals during autumn and/or winter for 3 years. Performances of tiller populations were assessed from these quadrats.3. Seed yields were increased in many cases by reducing plant density from a continuous drill pattern. Increased plant density reduced yields. With plant communities on a 1 ft. square arrangement at the high level of nitrogen, an increase of 33%, or 243 lb. seed, per year over a 3-year period was obtained compared with continuous rows at any level of N. The yield of gapped stands increased over the 3-year period, whilst the yields of continuous rows dropped in the final year.4. Nitrogen significantly increased the yield of cocksfoot, except in the third year, by increasing the weight of seed per ear.5. Tiller numbers per quadrat increased in most treatments over the course of the experiment, both within years and from year to year; seasonal peaks of tillering were apparent. The effect of N on tiller numbers differed each year, presumably due to the state of the populations when the N was applied.6. Higher tiller numbers per plant were obtained with lower plant numbers per unit area. Percentage fertility of tillers was generally higher with lower plant densities, and lower tiller numbers per plant, other factors being equal. The only significant effect of N on fertility was to decrease it in the third year.

Corn Emergence and Yield Response to Row-unit Depth and Downforce for Varying Field Conditions

2019 ◽  
Vol 35 (3) ◽  
pp. 399-408
Author(s):  
Aurelie M. Poncet ◽  
John P. Fulton ◽  
Timothy P. McDonald ◽  
Thorsten Knappenberger ◽  
Joey N. Shaw
Keyword(s):  
Weather Conditions ◽  
Field Conditions ◽  
Yield Response ◽  
Soil Conditions ◽  
Plant Populations ◽  
Growing Seasons ◽  
Combine Harvester ◽  
Growing Conditions ◽  
Unit Depth ◽  
Lower Plant

Abstract. Optimum row-crop planter seeding depth performance is required to place seeds within proper soil conditions to ensure quick germination and maximize the likelihood of uniform emergence. Seeding depth is adjusted prior to planting by selecting a row-unit depth, followed by the adjustment of a row-unit downforce for proper seed-soil contact. Optimum row-unit depth and downforce settings required to maintain a consistent seeding depth are variable. The objective of this study was to evaluate corn ( L) emergence and yield response to row-unit depth and downforce in changing field conditions between sites and growing seasons. Corn was planted with a 6-row John Deere MaxEmerge Plus planter equipped with heavy duty downforce springs. The experiment was conducted in 2014 and 2015 in Central Alabama for non-irrigated corn. Two fields, three row-unit depths (4.4, 7.0, and 9.5 cm), and three row-unit downforce settings (0.0, 1.1, and 1.8 kN) were evaluated. Emergence was measured at 75 and 100 Growing Degree Days (GDDs). Yield was measured using a yield monitor installed on the combine harvester. Corn emergence was mainly affected by changes in weather conditions. Row-unit depth and downforce did not affect corn emergence in warmer weather conditions but the 4.4 cm row-unit depth resulted in more emergence than the other row-unit depth settings in cooler weather conditions. Yield ranged from 8,000 to 13,000 kg ha-1 across treatments and yield was mostly affected by changing growing conditions between fields and growing seasons. Plant population significantly varied with treatments, but lower plant populations did not always result in lower corn yields. These findings provided a better understanding of corn emergence and yield response to row-unit depth and downforce in varying field conditions. Keywords: Corn, Depth, Downforce, Emergence, Maize, Planter, Yield.

Challenging the Multidimensional Conception of Perceived Person-Environment Fit

2020 ◽  
pp. 1-9
Author(s):  
Julian M. Etzel ◽  
Gabriel Nagy
Keyword(s):  
Higher Education ◽  
University Students ◽  
Educational Outcomes ◽  
Factor Model ◽  
Higher Order ◽  
Substantial Proportion ◽  
Unique Variance ◽  
First Order ◽  
Person Environment Fit ◽  
Order Factor

Abstract. In the current study, we examined the viability of a multidimensional conception of perceived person-environment (P-E) fit in higher education. We introduce an optimized 12-item measure that distinguishes between four content dimensions of perceived P-E fit: interest-contents (I-C) fit, needs-supplies (N-S) fit, demands-abilities (D-A) fit, and values-culture (V-C) fit. The central aim of our study was to examine whether the relationships between different P-E fit dimensions and educational outcomes can be accounted for by a higher-order factor that captures the shared features of the four fit dimensions. Relying on a large sample of university students in Germany, we found that students distinguish between the proposed fit dimensions. The respective first-order factors shared a substantial proportion of variance and conformed to a higher-order factor model. Using a newly developed factor extension procedure, we found that the relationships between the first-order factors and most outcomes were not fully accounted for by the higher-order factor. Rather, with the exception of V-C fit, all specific P-E fit factors that represent the first-order factors’ unique variance showed reliable and theoretically plausible relationships with different outcomes. These findings support the viability of a multidimensional conceptualization of P-E fit and the validity of our adapted instrument.

scholarly journals Mathematical Creativity in Adults: Its Measurement and Its Relation to Intelligence, Mathematical Competence and General Creativity

2021 ◽  
Vol 9 (1) ◽  
pp. 10
Author(s):  
Michaela A. Meier ◽  
Julia A. Burgstaller ◽  
Mathias Benedek ◽  
Stephan E. Vogel ◽  
Roland H. Grabner
Keyword(s):  
Exploratory Study ◽  
Mathematical Creativity ◽  
Good Reliability ◽  
Mathematical Competence ◽  
First Order ◽  
The Past ◽  
Confirmatory Factor ◽  
Order Factor ◽  
General Creativity ◽  
Creativity Measure

Mathematical creativity is perceived as an increasingly important aspect of everyday life and, consequently, research has increased over the past decade. However, mathematical creativity has mainly been investigated in children and adolescents so far. Therefore, the first goal of the current study was to develop a mathematical creativity measure for adults (MathCrea) and to evaluate its reliability and construct validity in a sample of 100 adults. The second goal was to investigate how mathematical creativity is related to intelligence, mathematical competence, and general creativity. The MathCrea showed good reliability, and confirmatory factor analysis confirmed that the data fitted the assumed theoretical model, in which fluency, flexibility, and originality constitute first order factors and mathematical creativity a second order factor. Even though intelligence, mathematical competence, and general creativity were positively related to mathematical creativity, only numerical intelligence and general creativity predicted unique variance of mathematical creativity. Additional analyses separating quantitative and qualitative aspects of mathematical creativity revealed differential relationships to intelligence components and general creativity. This exploratory study provides first evidence that intelligence and general creativity are important predictors for mathematical creativity in adults, whereas mathematical competence seems to be not as important for mathematical creativity in adults as in children.

Underlying Common Factors of Adolescent Problem Behaviors

2002 ◽  
Vol 29 (2) ◽  
pp. 161-182 ◽  
Author(s):  
Lening Zhang ◽  
John W. Welte ◽  
William F. Wieczorek
Keyword(s):  
Problem Behaviors ◽  
Latent Variable ◽  
Factor Model ◽  
Common Factor ◽  
Measurement Model ◽  
First Order ◽  
Adolescent Problem Behaviors ◽  
The Common ◽  
Order Factor ◽  
Second Order Factor Analysis

The Buffalo Longitudinal Study of Young Men was used to address the possibility of a common factor underlying adolescent problem behaviors. First, a measurement model with a single first-order factor was compared to a model with three separate correlated first-order factors. The three-factor model was better supported, making it logical to conduct a second-order factor analysis, which confirmed the logic. Second, a substantive model was estimated in each of two waves with psychopathic state as the common factor predicting drinking, drug use, and delinquency. Psychopathic state was stable across waves. The theory that a single latent variable accounts for large covariance among adolescent problem behaviors was supported.

scholarly journals Observed and estimated leaf appearance of landrace and improved maize cultivars

2017 ◽  
Vol 48 (1) ◽  
Author(s):  
Josana Andreia Langner ◽  
Nereu Augusto Streck ◽  
Angelica Durigon ◽  
Stefanía Dalmolin da Silva ◽  
Isabel Lago ◽  
...  
Keyword(s):  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Sowing Date ◽  
Mean Square ◽  
Data Set ◽  
Growing Seasons ◽  
Maize Cultivars ◽  
Maize Varieties ◽  
Leaf Appearance

ABSTRACT: The objective of this study was to compare the simulations of leaf appearance of landrace and improved maize cultivars using the CSM-CERES-Maize (linear) and the Wang and Engel models (nonlinear). The coefficients of the models were calibrated using a data set of total leaf number collected in the 11/04/2013 sowing date for the landrace varieties ‘Cinquentinha’ and ‘Bico de Ouro’ and the simple hybrid ‘AS 1573PRO’. For the ‘BRS Planalto’ variety, model coefficients were estimated with data from 12/13/2014 sowing date. Evaluation of the models was with independent data sets collected during the growing seasons of 2013/2014 (Experiment 1) and 2014/2015 (Experiment 2) in Santa Maria, RS, Brazil. Total number of leaves for both landrace and improved maize varieties was better estimated with the Wang and Engel model, with a root mean square error of 1.0 leaf, while estimations with the CSM-CERES-Maize model had a root mean square error of 1.5 leaf.

scholarly journals PLANT DENSITY AND NITROGEN FERTILIZATION ON COMMON BEAN NUTRITION AND YIELD

2017 ◽  
Vol 30 (3) ◽  
pp. 670-678 ◽  
Author(s):  
ROGÉRIO PERES SORATTO ◽  
TIAGO ARANDA CATUCHI ◽  
EMERSON DE FREITAS CORDOVA DE SOUZA ◽  
JADER LUIS NANTES GARCIA
Keyword(s):  
Grain Yield ◽  
Common Bean ◽  
Nitrogen Fertilization ◽  
Dry Matter ◽  
Plant Density ◽  
N Fertilization ◽  
N Concentration ◽  
Plant Densities ◽  
N Rates ◽  
Lower Plant

ABSTRACT The objective of this work was to evaluate the effect of plant densities and sidedressed nitrogen (N) rates on nutrition and productive performance of the common bean cultivars IPR 139 and Pérola. For each cultivar, a randomized complete block experimental design was used in a split-plot arrangement, with three replicates. Plots consisted of three plant densities (5, 7, and 9 plants ha-1) and subplots of five N rates (0, 30, 60, 120, and 180 kg ha-1). Aboveground dry matter, leaf macro- and micronutrient concentrations, yield components, grain yield, and protein concentration in grains were evaluated. Lower plant densities (5 and 7 plants m-1) increased aboveground dry matter production and the number of pods per plant and did not reduce grain yield. In the absence of N fertilization, reduction of plant density decreased N concentration in common bean leaves. Nitrogen fertilization linearly increased dry matter and leaf N concentration, mainly at lower plant densities. Regardless of plant density, the N supply linearly increased grain yield of cultivars IPR 139 and Pérola by 17.3 and 52.2%, respectively.

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