Time of sowing and the yield of winter wheat

Green, C. F.; Ivins, J. D.

doi:10.1017/s0021859600043185

Cited by 26 publications

(11 citation statements)

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“…moisture meter; yields were then scaled to 14% moisture content and expressed in kg ha -1 . Normalization of yield, expressed as a proportion of the maximum measured yield within each year, followed the technique outlined by Green and Ivins (1985). Each trial had a randomized complete block design with four blocks.…”

Section: Methodsmentioning

confidence: 99%

Sowing date affects yield components of canarygrass seed

Bodega¹,

Dios²,

Iraola³

2003

Can. J. Plant Sci.

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Canarygrass (Phalaris canariensis L.) crops are sown from June to mid-September in the southeastern area of the province of Buenos Aires, Argentina. Sowing dates in this range result in different growing temperatures and photoperiods that affect the duration of developmental stages, biomass production, and seed yield and its components. For Argentina, there are no reported studies that address these effects. This study on the effects of sowing date was conducted during four growing seasons (1996–1999) at the Instituto Nacional de Tecnologí a Agropecuaria (INTA) Experimental Station at Balcarce, Argentina, using a population provided by Dr. Jaime Lloveras, University of Leyda, Spain. Different seeding dates were chosen from June to mid-September. The experiment was a randomized complete block design with four blocks. When the sowing date was delayed, total dry matter (DM) decreased. For early sowing dates seed yield was constant, but after 10 August it was reduced by 1.5% for each day of delay. Earlier sowing increased the duration of pre-anthesis development with greater uniformity in panicle size and the number of seeds. Seed yield was related lin early to the number of seeds and plant dry matter yield (DMY). The rate of progress from emergence to anthesis (1/days from emergence to anthesis) was proportional to the mean photoperiod. Under the environmental conditions in Balcarce, the accumulated required thermal units for anthesis was reduced when sowing was delayed from June to September. This reduction was related to the photoperiod and was estimated as –189.3 growing degree-days per hour of photoperiod increment. Key words: Canarygrass, seed yield, sowing date, yield components

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Section: Methodsmentioning

confidence: 99%

Sowing date affects yield components of canarygrass seed

Bodega¹,

Dios²,

Iraola³

2003

Can. J. Plant Sci.

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“…The values of A found with the rules described above were expected from the work of Green and Ivins (1985) to be related to the sowing date of the crop, t,, expressed as the number of days after August 31 st. However, no significant relationships were found, and so weather variates, viz, the mean daily rainfall and temperature for each month, were introduced with t s in multiple regressions.…”

Section: Using the Equation To Relate Crop Growth And N Uptake To Sowmentioning

confidence: 93%

A function for describing nitrogen uptake, dry matter production and rooting by wheat crops

Whitmore

Addiscott

1987

Plant Soil

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The quantities, Y, of nitrogen taken up, and dry matter produced, at various times during the growth of six winter wheat crops at Rothamsted were shown to be related to thermal time, x, based on soil temperature, by a simple equationwhere A is the ultimate maximum of Y, n a shape factor and k a rate constant that is related to A and n through x', the inflexion point of the function. The value of n was 1.5 for both N uptake and dry matter. The value of A for N uptake, Au, was well described by a multiple regression on sowing data, t,, expressed as the number of days after August 31 st, and rainfall, R~pr, in the April before harvest, but no such regression could be found for the value of A for dry matter, AD. The rate constants, ks and ko, for N-uptake and dry-matter production respectively, could be related to the date of sowing and the weather through the corresponding inflexion points,x'N and x'o. Highly significant regressions were found, for x'u on the time, ts:, between sowing and the return of the soil to field capacity and for x'o on the reciprocal of t~. The function was used to generate N uptake curves from values of Au and ku (obtained from x'u) given by inserting the appropriate values of RApt, t~ and t,:in the regressions. These fitted measured N uptakes satisfactorily for the six crops used to obtain the regressions, and four grown subsequently, at Rothamsted, and also for six crops at Woburn. Values of Ao had to be set arbitrarily because no regression had been found to predict them, but using these arbitrary values in the function gave dry matter curves that fitted the measurements satisfactorily for all ten Rothamsted crops and two of the Woburn crops. Tests for seasonal and site effects showed that Au was influenced more by differences between the two sites than by seasonal differences other than those in RApt, whereas Ao was strongly influenced by these seasonal differencess and very little by those between the sites.

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“…Apart from environmental factors, the crop management plan can be designed such that it minimises the lodging risk. Sowing date, for instance, can affect the risk of lodging in winter wheat (Green and Ivins, 1985). Early sowing is known to increase crop lodging risk as it increases the residual soil nitrogen uptake efficiency, which results in profuse vegetative growth (Kirby et al, 1985;Fischer and Stapper, 1987; Milford et al, 1993;Spink et al, 2000).…”

Section: Factors Affecting Crop Lodgingmentioning

confidence: 99%

Remote sensing-based crop lodging assessment: Current status and perspectives

Chauhan

Darvishzadeh

Boschetti

et al. 2019

ISPRS Journal of Photogrammetry and Remote Sensing

102

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Rapid and quantitative assessment of crop lodging is important for understanding the causes of the phenomena, improving crop management, making better production and supporting loss estimates in general. Accurate information on the location and timing of crop lodging is valuable for farmers, agronomists, insurance loss adjusters, and policymakers. Lodging studies can be performed to assess the impact of lodging events or to model the risk of occurrence, both of which rely on information that can be acquired by field observations, from meteorological data and from remote sensing (RS). While studies applying RS data to assess crop lodging dates back three decades, there has been no comprehensive review of the status, potential, current approaches, and challenges in this domain. In this position paper, we review the trends in field/lab-based and RS-based studies for crop lodging assessment and discuss the strengths and weaknesses of current approaches. Theoretical background on crop lodging is presented, and the scope of RS in assessing plant characteristics associated with lodging is reviewed and discussed. The review focuses on RS-based studies, grouping them according to the platform deployed (i.e., ground-based, airborne and spaceborne), with an emphasis on analyzing the pros and cons of the technology. Finally, the challenges, research gaps, perspectives for future research, and an outlook on new sensors and platforms are presented to provide state-of-the-art and future scenarios of RS in lodging assessment. Our review reveals that the use of RS techniques in crop lodging assessment is still in an experimental stage. However, there is increasing interest within the RS scientific community (based on the increased rate of publications over time) to investigate its use for crop lodging detection and risk mapping. The existing satellitebased lodging assessment studies are very few, and the operational application of the current approaches over large spatial extents seems to be the biggest challenge. We identify opportunities for future studies that can develop quantitative models for estimating lodging severity and mapping lodging risk using RS data. 1.2. The role of remote sensing The past few decades have witnessed considerable growth in the use of sensors on-board Earth-Observation (EO) systems for agricultural monitoring applications. Today, crop biophysical properties such as leaf

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Time of sowing and the yield of winter wheat

Cited by 26 publications

References 10 publications

Sowing date affects yield components of canarygrass seed

Sowing date affects yield components of canarygrass seed

A function for describing nitrogen uptake, dry matter production and rooting by wheat crops

Remote sensing-based crop lodging assessment: Current status and perspectives

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