Modelling genotypic and environmental control of leaf area dynamics in grain sorghum. I. Whole plant level

Hammer, Graeme; Carberry, P. S.; Muchow, R.C.

doi:10.1016/0378-4290(93)90087-4

Cited by 130 publications

(94 citation statements)

References 20 publications

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“…Vyas et al (2010) calculated LAI for teak and bamboo based on canopy width, and reported RMSE 0.38 to 1.15 m 2 m -2 for calculated vs. measured LAI. Carberry et al (1993) calculated LAI for sorghum using main culm leaf number (as established by Hammer et al, 1993), resulting in r 2 = 0.86 and RMSE = 0.54 m 2 m -2 . In the present study (Table 7), the LAPPCH model resulted in comparable r 2 (0.63-0.84) and RMSE (0.80-0.92 m 2 m -2 ).…”

Section: Discussionmentioning

confidence: 99%

Allometric Method to Estimate Leaf Area Index for Row Crops

et al. 2017

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Core Ideas A new allometric method was developed to estimate LAI for row crops. Good agreement resulted for four crops over multiple seasons. Best agreement resulted using GDD, plant population, and canopy height. Leaf area index (LAI) is critical for predicting plant metabolism, biomass production, evapotranspiration, and greenhouse gas sequestration, but direct LAI measurements are difficult and labor intensive. Several methods are available to measure LAI indirectly or calculate LAI using allometric methods (i.e., exploiting relationships between LAI and more easily measured plant variables), but these depend on other measurements not widely available, and have limited transferability to different seasons. A new allometric method using a log normal function was developed to calculate LAI. Input variables were normalized cumulative growing degree days (CGDD), canopy height (CH), and plant population (PP), which were usually more widely available in crop production datasets. Destructive LAI measurements were obtained over multiple growing seasons for corn (Zea mays L.), cotton (Gossypium hirsutum L.), sorghum (Sorghum bicolor L.), and soybean [Glycine max (L.) Merr.] at USDA‐ARS, Bushland, TX. Log normal functions were calibrated to LAI measurements from a single season of each crop, and tested using independent LAI measurements from all remaining crop seasons. For all crops, discrepancies between calculated and measured LAI resulted in coefficients of determination from 0.23 to 0.85, model indices of agreement from 0.52 to 0.84, root mean square errors from 0.76 to 1.4, mean absolute errors from 0.57 to 1.2, and mean bias errors from ‐0.46 to 0.60. The new allometric method can mitigate missing or sparse LAI data, which will enhance the value of large ecological datasets.

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Section: Discussionmentioning

confidence: 99%

Allometric Method to Estimate Leaf Area Index for Row Crops

et al. 2017

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“…Daily radiation, minimum and maximum temperature, and rainfall were obtained from a weather station located in close proximity to each of the experiments. Thermal time was calculated using 11, 30, and 42 °C for the base, optimum, and maximum temperature and using linear interpolations between these temperatures (Hammer et al 1993). …”

Section: Methodsmentioning

confidence: 99%

“…Depending on plant density, fertile tillers may account for up to 60 % of total plant leaf area and contribute from 5 to 80 % of grain yield (Lafarge and Hammer 2002). However, a trade-off between main shoot and tillers can reduce grain yield in response to certain E × M combinations (Lafarge and Hammer 2002), as fertile tiller number of sorghum depends on the E × M conditions in which the crop is grown (Hammer et al 1993;Kouressy et al 2008). In general, it is thought that high tillering genotypes tend to be more suitable for environments with ample available water and high resource availability, because fertile tillers increase grain number per unit area, resulting in maximal conversion of available resources into grain.…”

Section: Introductionmentioning

confidence: 99%

QTL analysis in multiple sorghum populations facilitates the dissection of the genetic and physiological control of tillering

Alam

Mace²,

Oosterom

et al. 2014

Theor Appl Genet

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target environments. The aims of this study were to identify QTL for tillering and component traits associated with the S/D balance or PTT, to develop a framework model for the genetic control of tillering in sorghum. Four mapping populations were grown in a number of experiments in south east Queensland, Australia. The QTL analysis suggested that the contribution of traits associated with either the S/D balance or PTT to the genotypic differences in tillering differed among populations. Thirty-four tillering QTL were identified across the populations, of which 15 were novel to this study. Additionally, half of the tillering QTL co-located with QTL for component traits. A comparison of tillering QTL and candidate gene locations identified numerous coincident QTL and gene locations across populations, including the identification of common non-synonymous SNPs in the parental genotypes of two mapping populations in a sorghum homologue of MAX1, a gene involved in the control of tiller bud outgrowth through the production of strigolactones. Combined with a framework for crop physiological processes that underpin genotypic differences in tillering, the co-location of QTL for tillering and component traits and candidate genes allowed the development of a framework QTL model for the genetic control of tillering in sorghum.

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“…Sorghum, being a C4 plant as maize, has its optimum range of air temperature during the vegetative period between 26 to 34°C (Hammer et al, 1993); and during the reproductive period between 25 to 28°C (Prasad et al, 2006(Prasad et al, , 2008. Decreases in pollen viability and consequently fewer pollen grains are a result of high temperature stress during pre-anthesis (sporogenesis), resulting in decreased seed set in sorghum grain (Prasad et al, 2008).…”

Section: Resultsmentioning

confidence: 99%

Viability of maize pollen grains in vitro collected at different times of the day

Kaefer¹,

Chiapetti²,

FogaÃ§a³

et al. 2016

Afr. J. Agric. Res.

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The viability of pollen grains is the essential precondition for obtaining enhanced or hybrid vigor genotypes and a good fixation of the fruit. It is a matter of great importance, especially for genetic improvement programs, which are used in various types of controlled pollination. This study aimed to evaluate the viability of the maize pollen grain through in vitro germination and stainability tests, collected at different times. The experimental design was a randomized block with factorial 2x5, two days of pollination at five times (9:00 a.m., 11:00 a.m., 1:00 p.m., 3:00 p.m. and 5:00 p.m.) with four replications. Each treatment consisted of 12 plants, which were taken randomly within each plot. The parameters evaluated were: germination percentage, the percentage of pollen grain stainability, the stigma receptivity and the best time for pollination. Through the analysis of variance, it was noted and interaction between the days and times of collection and highly significant differences for the following parameters: temperature percentage, humidity, germination and viability of the pollen grain, indicating that the days and times influenced the viability of pollen grains. We could observe that the best results of viable pollen grains were obtained at 09.00 a.m. regardless of the day. It was also noted that the ambient temperature and relative humidity were the main influencing factors on pollen viability, and not the collection times.

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Modelling genotypic and environmental control of leaf area dynamics in grain sorghum. I. Whole plant level

Cited by 130 publications

References 20 publications

Allometric Method to Estimate Leaf Area Index for Row Crops

Allometric Method to Estimate Leaf Area Index for Row Crops

QTL analysis in multiple sorghum populations facilitates the dissection of the genetic and physiological control of tillering

Viability of maize pollen grains in vitro collected at different times of the day

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