An analysis of leaf growth in sugar beet.

Milford, G. F. J.; Pocock, T. O.; Riley, Janet; Messem, A. B.

doi:10.1111/j.1744-7348.1985.tb03108.x

Cited by 75 publications

(25 citation statements)

References 21 publications

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“…J. Agron., 14 (3): 158-163, 2015Mildford et al (1985 reported that light interception is mainly influenced by leaf area index and Scott and Jaggard (1978) had earlier reported that dry matter yield was proportional to the total amount of radiation intercepted by the crop for growth. Total biomass production of a crop, without water limitations, is the product of solar radiation intercepted by the crop canopy over the duration of the cropping period and the efficiency at which the crop converts light energy into plant dry matter (Richards, 2000).…”

Section: Discussionmentioning

confidence: 99%

Character Association and Path Coefficient Analysis of Maize (Zea mays L.) Grown under Incorporated Legumes and Nitrogen

Adesoji¹,

Abubakar²,

Labe³

2015

J. of Agronomy

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to evaluate character association and path coefficient analysis of maize (Zea mays L.) grown under legume incorporation and nitrogen. The results of this study showed that maize grain yield correlated positively and significantly with all measured characters. Path coefficient analysis indicated that plant height, total dry matter per plant, crop growth rate, cob length, number of grains per cob, 100-seed weight and stover yield showed positive direct effects on grain yield. Plant height and total dry matter per plant and 100-seed weight and stover yield gave the largest combined contributions. In growth characters, the highest individual contributions to grain yield were made by total dry matter per plant and crop growth rate. In yield characters, the highest individual contributions to grain yield were made by 100-seed weight and stover yield. Conclusively, total dry matter per plant, crop growth rate, 100-seed weight and stover yield should be considered for selection criteria in improving these varieties for better yield.

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Section: Discussionmentioning

confidence: 99%

Character Association and Path Coefficient Analysis of Maize (Zea mays L.) Grown under Incorporated Legumes and Nitrogen

Adesoji¹,

Abubakar²,

Labe³

2015

J. of Agronomy

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“…5 shows an S-shaped relationship for leaf area with accumulated temperature above this base temperature. This is because final areas of individualleaves vary systematically with their position on the plant, increasing up to leaves 9 to 12 and then decreasing (Milford et al 1985b). …”

Section: Discussionmentioning

confidence: 99%

Radiation interception and growth of sugar beet at different sowing dates in Canterbury

Martin¹

1986

New Zealand Journal of Agricultural Research

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Measurements of photosynthetically active ra~iation above and below the canopy, and leaf area llldex were used to determine a radiation extinction coefficient for sugar beet from 4 sowing dat~s. This coefficient (0.613) was not affected by sOWlllg date. It was used to determine the relationship of total crop dry weight, root dry weight, and root sugar yield to intercepted radiation for these 4 so~ing dates and for similar sowing dates the preVIOUS season. The slopes of the regression lines were linear throughout the growing season, except for that of the total crop dry matter, which had a 2-stage linear regression in the second season. The efficiency of conversion of intercepted photosynth~tically active radiation averaged 2.6 (total dry weIght), 1.7 (root dry weight), and 1.3 g/MJ (sugar yield). There appeared to be little effect of sowing date in the first season. In the second season, the conversion efficiencies for root and sugar yields for the different sowing dates were related to the intensity of virus yellows infection. Maximum radiation interception was not achieved until January or February, irrespective of sowing date. Leaf area expansion in spring was restricted by low temperatures. It was concluded that increased sugar beet yields were most likely under managements which promote earlier leaf area expansion.

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“…Furthermore, sugar accumulation is inversely related to nitrogen uptake (Werker et al, 1999). On the other hand, nitrogen deficiency affects leaf expansion (Milford et al, 1985), thus decreasing photosynthetic assimilation and crop yield. Therefore, a compromise has to be reached.…”

Section: Introductionmentioning

confidence: 99%

Retrieving LAI, chlorophyll and nitrogen contents in sugar beet crops from multi-angular optical remote sensing: Comparison of vegetation indices and PROSAIL inversion for field phenotyping

Jay

Maupas

Bendoula³

et al. 2017

Field Crops Research

198

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Remote sensing has gained much attention for agronomic applications such as crop management or yield estimation. Crop phenotyping under field conditions has recently become another important application that requires specific needs: the considered remote-sensing method must be (1) as accurate as possible so that slight differences in phenotype can be detected and related to genotype, and (2) robust so that thousands of cultivars potentially quite different in terms of plant architecture can be characterized with a similar accuracy over different years and soil and weather conditions. In this study, the potential of nadir and off-nadir ground-based spectro-radiometric measurements to remotely sense five plant traits relevant for field phenotyping, namely, the leaf area index (LAI), leaf chlorophyll and nitrogen contents, and canopy chlorophyll and nitrogen contents, was evaluated over fourteen sugar beet (Beta vulgaris L.) cultivars, two years and three study sites. Among the diversity of existing remote-sensing methods, two popular approaches based on various selected Vegetation Indices (VI) and PROSAIL inversion were compared, especially in the perspective of using them for phenotyping applications.Overall, both approaches are promising to remotely estimate LAI and canopy chlorophyll content ( ≤ 10 %). In addition, VIs show a great potential to retrieve canopy nitrogen content ( = 10 %). On the other hand, the estimation of leaf-level quantities is less accurate, the best accuracy being obtained for leaf chlorophyll content estimation based on VIs ( = 17 %). As expectedAuthor-produced version of the article published in Field Crops Research, 2017, N°210, p.33-46. The original publication is available at http://www.sciencedirect.com Doi: 10.1016Doi: 10. /j.fcr.2017 when observing the relationship between leaf chlorophyll and nitrogen contents, poor correlations are found between VIs and mass-based or area-based leaf nitrogen content. Importantly, the estimation accuracy is strongly dependent on sun-sensor geometry, the structural and biochemical plant traits being generally better estimated based on nadir and off-nadir observations, respectively.Ultimately, a preliminary comparison tends to indicate that, providing that enough samples are included in the calibration set, (1) VIs provide slightly more accurate performances than PROSAIL inversion, (2) VIs and PROSAIL inversion do not show significant differences in robustness across the different cultivars and years. Even if more data are still necessary to draw definitive conclusions, the results obtained with VIs are promising in the perspective of high-throughput phenotyping using UAVembedded multispectral cameras, with which only a few wavebands are available.

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An analysis of leaf growth in sugar beet.

Cited by 75 publications

References 21 publications

Character Association and Path Coefficient Analysis of Maize (Zea mays L.) Grown under Incorporated Legumes and Nitrogen

Character Association and Path Coefficient Analysis of Maize (Zea mays L.) Grown under Incorporated Legumes and Nitrogen

Radiation interception and growth of sugar beet at different sowing dates in Canterbury

Retrieving LAI, chlorophyll and nitrogen contents in sugar beet crops from multi-angular optical remote sensing: Comparison of vegetation indices and PROSAIL inversion for field phenotyping

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