Size-dependent reproductive effort in Amaranthus retroflexus: the influence of planting density and sowing date

2006 ◽  
Vol 84 (3) ◽  
pp. 485-492 ◽  
Author(s):  
Tianhui Wang ◽  
Daowei Zhou ◽  
Ping Wang ◽  
Hongxiang Zhang
Keyword(s):  
Reproductive Effort ◽  
Branch Length ◽  
Sowing Date ◽  
Amaranthus Retroflexus ◽  
Planting Density ◽  
Size Dependent ◽  
Sowing Dates ◽  
Wide Range ◽  
Total Branch Length ◽  
Reproductive Biomass

Size-dependent reproductive effort is an important component of plant fitness. The responses of reproductive effort to environmental factors in Amaranthus retroflexus L. were measured in two experiments. A wide range of selection pressures were generated by manipulating the sowing date (29 April, 23 May, 18 June, and 14 July) and planting density (13.4, 36, 121, and 441 plants·m–2). Allometric analysis between reproductive biomass and vegetative biomass across treatments showed that reproductive effort increased with size in response to different planting densities but decreased with size in sowing dates experiment. The allometric exponent between treatments was not influenced by planting densities but had significant variation with sowing date. Total branch length could explain most of the variation of reproductive accumulation and allocation in planting density experiments. For the plants with different sowing dates, total branch length was the main determinant of reproductive biomass, while reproductive effort mainly depended on the number of primary branches per unit stem mass. Architectural constraints with size result in size-dependent reproduction. Size-dependent reproduction in A. retroflexus was influenced by available resources and environmental conditions through the mechanisms of self-regulation of architectural traits.

Variation in branch length in Fagopyrum esculentum in response to density and emergence date: No evidence for true plasticity

Botany ◽  
2009 ◽  
Vol 87 (9) ◽  
pp. 888-892 ◽  
Author(s):  
Wisdom Japhet ◽  
Daowei Zhou ◽  
Ping Wang
Keyword(s):  
Branch Length ◽  
Sowing Date ◽  
Fagopyrum Esculentum ◽  
Planting Density ◽  
Total Biomass ◽  
Heterogeneous Environments ◽  
Sowing Dates ◽  
Allometric Analysis ◽  
Fagopyrum Esculentum Moench ◽  
Emergence Date

Plasticity is an important attribute that enables plants to maintain fitness in heterogeneous environments. The objective of this study was to investigate plasticity in branch length in Fagopyrum esculentum Moench. Seeds of the species were sown under two contrasting conditions through the manipulation of planting density (inter-planting distances at 20, 15, 10, and 5 cm) and sowing date (25 July, 1 August, 5 August, and 15 August). Allometric analysis of the relationships between branch length and total biomass showed a significant (p < 0.05) departure from isometry. This indicates that branch length increased linearly as a function of size. However, branch length was smaller in the group of plants sown at higher densities and at late sowing dates. True plasticity, which would have been indicated by significant differences in allometric exponents within treatments, was not observed in this study. Our results suggest that the differences observed in branch length were due to the direct effect of size rather than as a result of true plastic investment in branches.

scholarly journals Effective Seed Yield and Flowering Synchrony of Parents of CIMMYT Three-Way-Cross Tropical Maize Hybrids

Agriculture ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 161
Author(s):  
Alberto A. Chassaigne-Ricciulli ◽  
Leopoldo E. Mendoza-Onofre ◽  
Leobigildo Córdova-Téllez ◽  
Aquiles Carballo-Carballo ◽  
Félix M. San Vicente-García ◽  
...  
Keyword(s):  
Seed Production ◽  
Seed Yield ◽  
Grain Filling ◽  
Sowing Date ◽  
Planting Density ◽  
Planting Dates ◽  
Flowering Synchrony ◽  
Sowing Dates ◽  
Grain Filling Period ◽  
Hybrid Maize

Genotype, environmental temperature, and agronomic management of parents influence seed yield in three-way cross hybrid maize seed production. The objective of this research was to generate information on the seed production of six three-way cross hybrids and their progenitors, adapted to tropical lowlands. Data on days to—and duration of—flowering, distance to spike and stigmas, and seed yield of five female single crosses and five male inbred lines were recorded for different combinations of four planting densities and four sowing dates in Mexico. The effect of planting density was not significant. The male inbred line T10 was the earliest and highest seed yield and T31 the latest, occupying second place in yield. The single crosses T32/T10 and T13/T14 were the earliest and had the highest effective seed yield. At the earliest sowing date, the females were later in their flowering, accumulated fewer growing degree days (GDD), and obtained higher yields since the grain-filling period coincided with hot days and cool nights. To achieve greater floral synchronization and therefore greater production of hybrid seed, differential planting dates for parents are recommended based on information from the accumulated GDD of each parent. The three-way cross hybrids were classified according to the expected seed yield of the females and the complexity in the synchronization of flowering of their parents.

Evaluation of the APSIM-Wheat model in terms of different cultivars, management regimes and environmental conditions

2012 ◽  
Vol 92 (5) ◽  
pp. 937-949 ◽  
Author(s):  
Yi Zhang ◽  
Liping Feng ◽  
Enli Wang ◽  
Jing Wang ◽  
Baoguo Li
Keyword(s):  
Root Mean Square ◽  
Environmental Conditions ◽  
Field Experiments ◽  
Growth And Yield ◽  
Planting Density ◽  
Mean Square ◽  
Sowing Dates ◽  
Wide Range ◽  
Management Regimes ◽  
Mean Square Errors

Zhang, Y., Feng, L., Wang, E., Wang, J. and Li, B. 2012. Evaluation of the APSIM-Wheat model in terms of different cultivars, management regimes and environmental conditions. Can. J. Plant Sci. 92: 937–949. Wheat is one of the most important crops in the world, and wheat models have been widely used to study yield responses to changes in management and climate. However, less information is available on how a wheat model performs in simulation of wheat response to changes in varieties, sowing dates and planting densities across space. This study presents an evaluation of the APSIM-Wheat model using data from field experiments consisting of three sowing dates, two and three crop varieties and three planting densities in a split-split plot design at three ecological sites from 2008 to 2010 in the North China Plain. The results show that the APSIM-Wheat model could capture a large part of the variation in phenology, biomass and yield for the same variety across sites. However, errors of simulation in phenology and yield were increased with delay in sowing date, with the average absolute root mean square errors of 2 d, 3 d, and 3–4 d in phenology, and the normalized root mean square error (RMSEn) of 7–12%, 11–16%, 16–22% in yield at early, medium, and late sowing dates, respectively. Simulation of yield achieved poor results with decreased planting density, with average RMSEn of 9–12%, 11–12%, and 16–19% at high, medium, and low density, respectively. Additionally, the simulation behaved in a complex manner, and the errors varied greatly with different combinations of sowing dates and planting densities. These alerted us that the model should be used cautiously to simulate growth and yield over a wide range of sowing dates and planting densities. Improved modeling of the responses of wheat growth to extreme temperatures during winter and spring periods, and to varying planting densities is needed for better future prediction. Other areas of model improvements are also discussed.

Predicting phenological development for Australian wheats

1987 ◽  
Vol 38 (5) ◽  
pp. 809
Author(s):  
MW Perry ◽  
KHM Siddique ◽  
JF Wallace
Keyword(s):  
Field Experiments ◽  
Simulation Models ◽  
Sowing Date ◽  
Development Rate ◽  
Regression Equations ◽  
Wheat Cultivars ◽  
Rate Of Development ◽  
Mean Temperature ◽  
Sowing Dates ◽  
Wide Range

Dates of ear initation and anthesis were recorded for 16 wheat cultivars at a wide range of sowing dates in four field experiments conducted over four years.In general for the majority of cultivars number of days from sowing to ear initiation increased as sowing was delayed through May and then declined with sowings after June. The effects of sowing date and cultivar on anthesis were similar to those observed for ear initiation. Maximum time to anthesis was observed from sowings in early May.A linear regression model relating rate of development to mean temperature and photoperiod accounted for 47-98% of the variation in rate of development from sowing to ear initiation and from 68 to 98% of the variation from ear initiation to anthesis. A five-parameter non-linear model was also tested but was not superior. Observations in a single year were sufficient to characterize a cultivar provided the range of mean temperature and photoperiod was large.Comparison with data from other field sites of ear initiation and anthesis showed that the regression equations gave a good fit to the occurrence of these events when used in the incremental sense, that is, by summing increments of development rate calculated from daily temperature and photoperiod.The prediction model is discussed in relation to its application in simulation models of crop growth, analysis of cultivar adaptation to environments and in day-to-day crop management.

Corrigendum - Predicting phenological development for Australian wheats

1987 ◽  
Vol 38 (5) ◽  
pp. 809
Author(s):  
MW Perry ◽  
KHM Siddique ◽  
JF Wallace
Keyword(s):  
Field Experiments ◽  
Simulation Models ◽  
Sowing Date ◽  
Development Rate ◽  
Regression Equations ◽  
Wheat Cultivars ◽  
Rate Of Development ◽  
Mean Temperature ◽  
Sowing Dates ◽  
Wide Range

Dates of ear initation and anthesis were recorded for 16 wheat cultivars at a wide range of sowing dates in four field experiments conducted over four years.In general for the majority of cultivars number of days from sowing to ear initiation increased as sowing was delayed through May and then declined with sowings after June. The effects of sowing date and cultivar on anthesis were similar to those observed for ear initiation. Maximum time to anthesis was observed from sowings in early May.A linear regression model relating rate of development to mean temperature and photoperiod accounted for 47-98% of the variation in rate of development from sowing to ear initiation and from 68 to 98% of the variation from ear initiation to anthesis. A five-parameter non-linear model was also tested but was not superior. Observations in a single year were sufficient to characterize a cultivar provided the range of mean temperature and photoperiod was large.Comparison with data from other field sites of ear initiation and anthesis showed that the regression equations gave a good fit to the occurrence of these events when used in the incremental sense, that is, by summing increments of development rate calculated from daily temperature and photoperiod.The prediction model is discussed in relation to its application in simulation models of crop growth, analysis of cultivar adaptation to environments and in day-to-day crop management.

Genotype, sowing date and plant spacing influence on high-yielding irrigated wheat in southern New South Wales. I. Phasic development, canopy growth and spike production

1990 ◽  
Vol 41 (6) ◽  
pp. 997 ◽  
Author(s):  
M Stapper ◽  
RA Fischer
Keyword(s):  
Management Practices ◽  
Plant Density ◽  
Sowing Date ◽  
Light Interception ◽  
Leaf Number ◽  
Initial Development ◽  
Node Number ◽  
Sowing Dates ◽  
Wide Range ◽  
Irrigated Wheat

Sowing date, sowing rate and row spacing effects were studied on high input crops at Griffith, N.S.W., between 1983 and 1985 using 25 bread wheats (Triticum aestivum L.) and 3 triticales (X Triticosecale Wittmack). The aim was to identify improved management practices and genotypes through a better understanding of development and growth of irrigated wheat grown under high-yielding conditions. The genotypes were chosen to represent a wide range in genetic background, maturity and stature. Growing period durations were between 208 days and 100 days for early April and mid-August sowings, respectively, with differences in anthesis dates within sowing dates of up to 45 days. Genotypes were classified into six major maturity groups. There was no maturity type that could flower close to 1 October from a wide range of sowing dates since anthesis was delayed by 0.3 to 0.5 days per 1-day delay in sowing. Increased daylength sensitivity tended to delay anthesis relative to the timing of floral initiation and terminal spikelet formation. The end of tillering was generally associated with the attainment of 50-60% light interception rather than a given development stage of the inflorescence. Spike density was not closely related to maximum tiller number but depended on genotype, environment and plant density. Leaf appearance rate was influenced by environment and genotype, but was independent of spike development. For a given final leaf number, internode elongation started at a later leaf number for later sowing dates, resulting in reductions in both node number and height. Crop height decreased by up to 5 cm per 1-week delay in anthesis date. The period of full light interception decreased from 133 days to 43 days between April and August sowings, respectively. The timing of reproductive development determined the green area duration, but the initial development and size of the canopy was less affected by it, because of adjustments in number and type of tillers, and size and thickness of leaves. The development and maintenance of an adequate canopy was not restricted by earliness, shortness or low sowing rates (50 kg seed/ha) for April-July sowing dates.

EFFECT OF SOWING DATE ON GRAIN YIELD OF CRAB GRASS

2001 ◽  
Vol 49 (3) ◽  
pp. 293-297
Author(s):  
S. O. Bakare ◽  
M. G. M. Kolo ◽  
J. A. Oladiran
Keyword(s):  
Grain Yield ◽  
Interaction Effect ◽  
Significant Interaction ◽  
Sowing Date ◽  
Yield Data ◽  
Significant Interaction Effect ◽  
Sowing Dates

There was a significant interaction effect between the variety and the sowing date for the number of productive tillers, indicating that the response to sowing date varied with the variety. A significant reduction in the number of productive tillers became evident when sowing was delayed till 26 June in the straggling variety as compared to sowing dates in May. Lower numbers of productive tillers were also recorded when the sowing of the erect variety was further delayed till 10 July. The grain yield data showed that it is not advisable to sow the straggling variety later than 12 June, while sowing may continue till about 26 June for the erect variety in the study area.

Solvent-Ligand Interactions in Colloidal Nanocrystals

2018 ◽  
Author(s):  
Jonathan De Roo ◽  
Nuri Yazdani ◽  
Emile Drijvers ◽  
Alessandro Lauria ◽  
Jorick Maes ◽  
...  
Keyword(s):  
Direct Method ◽  
Line Broadening ◽  
H Nmr ◽  
Size Dependent ◽  
Line Shape Analysis ◽  
Wide Range ◽  
Nanocrystal Synthesis ◽  
Ligand Interactions ◽  
Indispensable Tool ◽  
Theoretical Evidence

<p>Although solvent-ligand interactions play a major role in nanocrystal synthesis, dispersion formulation and assembly, there is currently no direct method to study this. Here we examine the broadening of <sup>1</sup>H NMR resonances associated with bound ligands, and turn this poorly understood descriptor into a tool to assess solvent-ligand interactions. We show that the line broadening has both a homogeneous and a heterogeneous component. The former is nanocrystal-size dependent and the latter results from solvent-ligand interactions. Our model is supported by experimental and theoretical evidence that correlates broad NMR lines with poor ligand solvation. This correlation is found across a wide range of solvents, extending from water to hexane, for both hydrophobic and hydrophilic ligand types, and for a multitude of oxide, sulfide and selenide nanocrystals. Our findings thus put forward NMR line shape analysis as an indispensable tool to form, investigate and manipulate nanocolloids.</p>

Application of physiological understanding in soybean improvement. I. Understanding phenological constraints to adaptation and yield potential

2011 ◽  
Vol 62 (1) ◽  
pp. 1 ◽  
Author(s):  
R. J. Lawn ◽  
A. T. James
Keyword(s):  
Seed Yield ◽  
Environmental Control ◽  
Thermal Environment ◽  
Sowing Date ◽  
Companion Paper ◽  
Interaction Effects ◽  
Yield Potential ◽  
Environment Interaction ◽  
Sowing Dates ◽  
Eastern Australia

The purpose of this paper and its companion1 is to describe how, in eastern Australia, soybean improvement, in terms of both breeding and agronomy, has been informed and influenced over the past four decades by physiological understanding of the environmental control of phenology. This first paper describes how initial attempts to grow soybean in eastern Australia, using varieties and production practices from the southern USA, met with limited success due to large variety × environment interaction effects on seed yield. In particular, there were large variety × location, variety × sowing date, and variety × sowing date × density effects. These various interaction effects were ultimately explained in terms of the effects of photo-thermal environment on the phenology of different varieties, and the consequences for radiation interception, dry matter production, harvest index, and seed yield. This knowledge enabled the formulation of agronomic practices to optimise sowing date and planting arrangement to suit particular varieties, and underpinned the establishment of commercial production in south-eastern Queensland in the early 1970s. It also influenced the establishment and operation over the next three decades of several separate breeding programs, each targeting phenological adaptation to specific latitudinal regions of eastern Australia. This paper also describes how physiological developments internationally, particularly the discovery of the long juvenile trait and to a lesser extent the semi-dwarf ideotype, subsequently enabled an approach to be conceived for broadening the phenological adaptation of soybeans across latitudes and sowing dates. The application of this approach, and its outcomes in terms of varietal improvement, agronomic management, and the structure of the breeding program, are described in the companion paper.

Analysis of high yielding maize production - a study based on a commercial crop

2008 ◽  
Vol 48 (3) ◽  
pp. 296 ◽  
Author(s):  
C. J. Birch ◽  
G. McLean ◽  
A. Sawers
Keyword(s):  
Retrospective Analysis ◽  
Environmental Conditions ◽  
Sowing Date ◽  
Plant Population ◽  
Higher Plant ◽  
Maize Crop ◽  
Wide Range ◽  
Commercial Crop ◽  
Reduced Temperature

This paper reports on the use of APSIM – Maize for retrospective analysis of performance of a high input, high yielding maize crop and analysis of predicted performance of maize grown with high inputs over the long-term (>100 years) for specified scenarios of environmental conditions (temperature and radiation) and agronomic inputs (sowing date, plant population, nitrogen fertiliser and irrigation) at Boort, Victoria, Australia. It uses a high yielding (17 400 kg/ha dry grain, 20 500 kg/ha at 15% water) commercial crop grown in 2004–05 as the basis of the study. Yield for the agronomic and environmental conditions of 2004–05 was predicted accurately, giving confidence that the model could be used for the detailed analyses undertaken. The analysis showed that the yield achieved was close to that possible with the conditions and agronomic inputs of 2004–05. Sowing dates during 21 September to 26 October had little effect on predicted yield, except when combined with reduced temperature. Single year and long-term analyses concluded that a higher plant population (11 plants/m2) is needed to optimise yield, but that slightly lower N and irrigation inputs are appropriate for the plant population used commercially (8.4 plants/m2). Also, compared with changes in agronomic inputs increases in temperature and/or radiation had relatively minor effects, except that reduced temperature reduces predicted yield substantially. This study provides an approach for the use of models for both retrospective analysis of crop performance and assessment of long-term variability of crop yield under a wide range of agronomic and environmental conditions.

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