The influence of Triticum aestivum density, sowing pattern and nitrogen fertilization on leaf area index and its spatial variation

2007 ◽  
Vol 8 (3) ◽  
pp. 252-257 ◽  
Author(s):  
Jannie Olsen ◽  
Jacob Weiner
2017 ◽  
Vol 12 (9) ◽  
pp. 095002 ◽  
Author(s):  
Sari Juutinen ◽  
Tarmo Virtanen ◽  
Vladimir Kondratyev ◽  
Tuomas Laurila ◽  
Maiju Linkosalmi ◽  
...  

2017 ◽  
Vol 35 (2) ◽  
pp. 171-175 ◽  
Author(s):  
Pedro Manuel Villa ◽  
Lina Sarmiento ◽  
Fermín José Rada ◽  
Daniel Machado ◽  
Alice Cristina Rodrigues

Nitrogen fertilization has considerable effects on growth and yield of potato crop. Leaf expansion is one of the most important growth parameters that can be used to optimize nitrogen fertilization management in agroecological practices. We evaluated the effect of nitrogen fertilization on the leaf area index (LAI) of potato crop during different phenological stages by two different methods. Experimental plots were established in a randomized block design with the following treatments: no nitrogen supply (0-N), 133 kg N ha-1 (133-N), and 400 kg N ha-1 (400-N), using the Granola variety, at the Andes region, Merida city, Venezuela. We measured leaf area at the main phenological stages of the crop using a plant canopy analyzer. LAI showed significant differences among treatments and phenological stages, except during the emergence stage. The maximum LAI values were obtained 55 days after emergence: 400-N (1.42±0.16) > 133-N (0.92±0.21) > 0-N (0.34±0.08). Nitrogen fertilization had a significant effect on the development of LAI in potato crop along its different phenological stages.


2015 ◽  
Vol 12 (20) ◽  
pp. 16847-16884 ◽  
Author(s):  
S. Caldararu ◽  
D. W. Purves ◽  
M. J. Smith

Abstract. Leaf seasonality impacts a variety of important biological, chemical and physical Earth system processes, which makes it essential to represent leaf phenology in ecosystem and climate models. However, we are still lacking a general, robust parametrisation of phenology at global scales. In this study, we use a simple process-based model, which describes phenology as a strategy for carbon optimality, to test the effects of the common assumption in global modelling studies that plant species within the same plant functional type have the same parameter values, implying they are assumed to have the same species traits. In a previous study this model was shown to predict spatial and temporal dynamics of leaf area index (LAI) well across the entire global land surface provided local grid cell parameters were used, and is able to explain 96 % of the spatial variation in average LAI and 87 % of the variation in amplitude. In contrast, we find here that a PFT level parametrisation is unable to capture the spatial variability in seasonal cycles, explaining on average only 28 % of the spatial variation in mean leaf area index and 12 % of the variation in seasonal amplitude. However we also show that allowing only two parameters, light compensation point and leaf age, to be spatially variable dramatically improves the model predictions, increasing the model's capability of explaining spatial variations in leaf seasonality to 70 and 57 % of the variation in LAI average and amplitude respectively. This highlights the importance of identifying the spatial scale of variation of plant traits and the necessity to critically analyse the use of the plant functional type assumption in Earth system models.


Author(s):  
Ranjana Jaiswal ◽  
S. C. Gaur ◽  
Sunil K. Jaiswal ◽  
Anil Kumar

Problem: Wheat (Triticum aestivum L.) is one of the principal cereal crops grown worldwide and one of the important staples of nearly 2.5 billion of world population. India ranks second position in terms of both in area and production after china. The substantial improvement in production is utmost necessary to feed the growing population. Objective: In India, wheat requirement by 2030 has been estimated at 100 million metric tons and to achieve this target, wheat production can be increased either through horizontal approach i.e. by the increasing area under cultivation or through vertical approach i.e. varietal/ hybrid improvement. For effective selection and utilization of superior genotype in the germplasm lines, knowledge of genetic parameters such as genetic variability, heritability and genetic advance is essential. Materials and Methods: The experimental material comprised of ten parents, their 45 F1s and 45 F2s developed by the crossing of 10 parents viz. HUW 510, HUW 234, HUW 468, UP 2338, HD 2402, RAJ 1972, HD 2329, LOK-1, SONALIKA and K 65 in half-diallel programme to study the fourteen characters. The final trial of F1, F2 including parents was conducted during Rabi 2014-15 with three replications employing Randomized Complete Block Design at Research Farm, BRDPG College, Deoria, Uttar Pradesh, India. Result: Wider range of phenotypic coefficient of variation (PCV) was observed for all the traits in F1 generation ranged from 2.19 (days to 50% flowering) to 13.47 (leaf area index) while, genotypic coefficient of variation (GCV) ranged from 1.50 (days to 50% flowering) to 11.28 (leaf area index). High heritability was observed in both F1 and F2 generation for leaf area index and day to maturity while, moderate to low level of heritability was recorded for other characters. The high value of genetic advance was not recorded in both F1 and F2 generation. Only moderate to the low value of genetic advance was observed for all the fourteen characters under study. Conclusion: Estimate of phenotypic and genotypic coefficient of variation of fourteen characters in both generations reveals sufficient variability indicating ample scope for genetic improvement of these traits through selection. Moderate level of heritability accompanied with a moderate level of genetic advance was observed for plant height, leaf area index, days to maturity and grain yield per plant in both F1 and F2 generation indicates additive gene effect and selection may be effective.


2000 ◽  
Vol 134 (1-3) ◽  
pp. 71-81 ◽  
Author(s):  
Valérie Le Dantec ◽  
Eric Dufrêne ◽  
Bernard Saugier

2017 ◽  
Vol 9 (4) ◽  
pp. 2410-2413
Author(s):  
Kamla Dhyani ◽  
Alok Shukla ◽  
R.S. Verma

High temperature stress during grain-filling period is one of the major environmental constraints limiting the grain yield of wheat in India. Crop growth response and relative performance of yield components of 12 wheat (Triticum aestivum) genotypes were studied in two date of sowing in crop research center (Pantnagar) to identify the causes of yield reduction in wheat particularly Leaf Area Index and its impact in yield loss and other tolerance mech-anism and comparative study of LAI and yield attributes to identify the genotype for high temperature tolerance in late sown condition. The higher temperature enhanced plant growth, flowering, and maturation which ultimately effects the crop performance in case of yield (Leaf Area Index, grain weight/spike and test weight were drastically reduced in time under high temperature. Out of 12 diverse genotypes namely HI 1539, DBW 14, HW 5021, HS 240, PBW-574, Raj 4101, Lok 54, Raj 3765, WH 1021, K-0-307, HW 2045 and HI1544,four were (Lok54, Raj3765, HI1539 and HI1544 ) were characterized as high temperature tolerant based on their relative performance in leaf area index, grain yield and heat susceptibility index. Leaf area Index studies in context to heat stress in wheat is least studied area in heat tolerance research in wheat (Triticum aestivum), in the present study LAI is used as a screening tool for heat tolerance and effect of LAI in wheat yield.


2016 ◽  
Vol 13 (4) ◽  
pp. 925-941
Author(s):  
Silvia Caldararu ◽  
Drew W. Purves ◽  
Matthew J. Smith

Abstract. Leaf seasonality impacts a variety of important biological, chemical, and physical Earth system processes, which makes it essential to represent leaf phenology in ecosystem and climate models. However, we are still lacking a general, robust parametrisation of phenology at global scales. In this study, we use a simple process-based model, which describes phenology as a strategy for carbon optimality, to test the effects of the common simplification in global modelling studies that plant species within the same plant functional type (PFT) have the same parameter values, implying they are assumed to have the same species traits. In a previous study this model was shown to predict spatial and temporal dynamics of leaf area index (LAI) well across the entire global land surface provided local grid cell parameters were used, and is able to explain 96 % of the spatial variation in average LAI and 87 % of the variation in amplitude. In contrast, we find here that a PFT level parametrisation is unable to capture the spatial variability in seasonal cycles, explaining on average only 28 % of the spatial variation in mean leaf area index and 12 % of the variation in seasonal amplitude. However, we also show that allowing only two parameters, light compensation point and leaf age, to be spatially variable dramatically improves the model predictions, increasing the model's capability of explaining spatial variations in leaf seasonality to 70 and 57 % of the variation in LAI average and amplitude, respectively. This highlights the importance of identifying the spatial scale of variation of plant traits and the necessity to critically analyse the use of the plant functional type assumption in Earth system models.


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