scholarly journals Effect of Square Planting and Nitrogen Scheduling on Yield and Micrometeorological Parameters in Maize

2016 ◽  
Vol 8 (2) ◽  
pp. 141
Author(s):  
Dharmalingam Selvakumar ◽  
Kumaran Velayudham ◽  
Nallasamy Thavaprakaash
Keyword(s):  
Spatial Distribution ◽  
Grain Yield ◽  
Spatial Pattern ◽  
Tamil Nadu ◽  
Leaf Temperature ◽  
Light Extinction ◽  
Growth Stages ◽  
K Value ◽  
Rectangular Pattern ◽  
Plant Spatial Distribution

<p class="1">Altering plant spatial distribution induces changes in micro-meteorology of crop canopy and have cumulative effect on yield. Creation of suitable plant spatial distribution is indispensable to explore the beneficial effects of spatial pattern and it could be possible only through altering rectangular spatial distribution, which is commonly practiced in maize. Most of the nitrogen (N) scheduling approaches are growth stages based without considering crop demand and soil fertility status which may not yield better, warrants need based N management for better production in maize. The present study has investigated effects of spatial pattern and nitrogen scheduling on intercepted photosynthetically active radiation (IPAR), light extinction co-efficient (‘k’), leaf temperature (LT) and productivity of maize. The experiments were conducted during 2011 and 2012 at Tamil Nadu Agricultural University, Coimbatore. Treatments were laid out in split-plot design and replicated thrice. Treatments were: six levels of spatial pattern (60 × 25, 30 × 30, 35 × 35, 40 × 40, 45 × 45 and 50 × 50 cm). Growth stage based and need based approach of leaf color chart based (LCC) nitrogen scheduling were imposed. Field experimental results indicated that maize canopy under 30 × 30 and 35 × 35 cm spatial pattern intercepted 10 to 15% more light compared to rectangular pattern (60 × 25 cm). The ‘k’ value and leaf temperature were reduced under this pattern. Higher maize grain yield (GY) was recorded at 35 × 35 cm spatial distribution. The LCC based N scheduling recorded higher values of IPAR, LT and lower ‘k’ values. Square planting favored canopy micro-meterological parameters and which in turn enhanced grain yield of maize.</p>

THE SPATIAL DISTRIBUTION OF LIMOTHRIPS DENTICORNIS HALIDAY (THYSANOPTERA: THRIPIDAE) EGGS ON SPRING BARLEY

1991 ◽  
Vol 123 (1) ◽  
pp. 205-210 ◽  
Author(s):  
Barbara A. Bates ◽  
Michael J. Weiss
Keyword(s):  
Spatial Distribution ◽  
Hordeum Vulgare ◽  
North Dakota ◽  
Flag Leaf ◽  
Spring Barley ◽  
Leaf Sheath ◽  
Growth Stages ◽  
Growing Seasons ◽  
Plant Spatial Distribution

AbstractThe within-plant spatial distribution of Limothrips denticornis Haliday eggs on spring barley (Hordeum vulgare L.) in North Dakota was examined during the growing seasons of 1987 and 1988. In both years, most eggs were found during inflorescence emergence (growth stages 10–10.5 on the Feekes scale), although eggs were detected both prior to and after these growth stages. Once inflorescence emergence was initiated, over 8.5% of the eggs were found in the top two leaf sheaths, with the majority in the flag leaf sheath. Over all barley growth stages, significantly more eggs (P≤0.05) were found in the middle third than in either the top or bottom third of the flag leaf sheath. No difference (P≥0.05) in the within-sheath location of eggs on lower leaves was detected.

scholarly journals Coastal Mangrove Response to Marine Erosion: Evaluating the Impacts of Spatial Distribution and Vegetation Growth in Bangkok Bay from 1987 to 2017

2020 ◽  
Vol 12 (2) ◽  
pp. 220 ◽  
Author(s):  
Han Xiao ◽  
Fenzhen Su ◽  
Dongjie Fu ◽  
Qi Wang ◽  
Chong Huang
Keyword(s):  
Spatial Distribution ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Mangrove Ecosystem ◽  
Early Growth ◽  
Growth Stages ◽  
Human Disturbances ◽  
Vegetation Growth ◽  
Two Parameters ◽  
The Impact

Long time-series monitoring of mangroves to marine erosion in the Bay of Bangkok, using Landsat data from 1987 to 2017, shows responses including landward retreat and seaward extension. Quantitative assessment of these responses with respect to spatial distribution and vegetation growth shows differing relationships depending on mangrove growth stage. Using transects perpendicular to the shoreline, we calculated the cross-shore mangrove extent (width) to represent spatial distribution, and the normalized difference vegetation index (NDVI) was used to represent vegetation growth. Correlations were then compared between mangrove seaside changes and the two parameters—mangrove width and NDVI—at yearly and 10-year scales. Both spatial distribution and vegetation growth display positive impacts on mangrove ecosystem stability: At early growth stages, mangrove stability is positively related to spatial distribution, whereas at mature growth the impact of vegetation growth is greater. Thus, we conclude that at early growth stages, planting width and area are more critical for stability, whereas for mature mangroves, management activities should focus on sustaining vegetation health and density. This study provides new rapid insights into monitoring and managing mangroves, based on analyses of parameters from historical satellite-derived information, which succinctly capture the net effect of complex environmental and human disturbances.

Spatial Patterns of Urban Innovation and Their Evolution from Perspectives of Capacity and Structure: Taking Shenzhen as an Example

2021 ◽  
Vol 11 (1) ◽  
pp. 7
Author(s):  
Erjie Hu ◽  
Di Hu ◽  
Handong He
Keyword(s):  
Spatial Distribution ◽  
Spatial Pattern ◽  
Distribution Pattern ◽  
Spatial Patterns ◽  
Spillover Effect ◽  
Tertiary Industry ◽  
Innovation Capacity ◽  
Structure Index ◽  
Secondary Industry ◽  
Spatial Spillover Effect

Innovation is a key factor for a country’s overall national strength and core competitiveness. The spatial pattern of innovation reflects the regional differences of innovation development, which can provide guidance for the regional allocation of innovation resources. Most studies on the spatial pattern of innovation are at urban and above spatial scale, but studies at urban internal scale are insufficient. The precision and index of the spatial pattern of innovation in the city needs to be improved. This study proposes to divide spatial units based on geographic coordinates of patents, designs the innovation capability and innovation structure index of a spatial unit and their calculation methods, and then reveals the spatial patterns of innovation and their evolutionary characteristics in Shenzhen during 2000–2018. The results show that: (1) The pattern of innovation capacity of secondary industry exhibited a pronounced spatial spillover effect with a positive spatial correlation. The innovation capacity and innovation structure index of the secondary industry evolved in a similar manner; i.e., they gradually extended from the southwest area to the north over time, forming a tree-like distribution pattern with the central part of the southwest area as the “root” and the northwest and northeast areas as the “canopy”. (2) The pattern of innovation capacity of tertiary industry also had a significant spatial spillover effect with a positive spatial correlation. There were differences between the evolutions of innovation capacity and innovation structure index of tertiary industry. Specifically, its innovation capacity presented a triangular spatial distribution pattern with three groups in the central and eastern parts of the southwest area and the south-eastern part of the northwest area as the vertices, while its innovative structure showed a radial spatial distribution pattern with the southwestern part of the southwest area as the source and a gradually sparse distribution toward the northeast. (3) There were differences between the evolution modes of secondary and tertiary industries. Areas with high innovation capacity in the secondary industry tended to be more balanced, while areas with high innovation capacity in the tertiary industry did not necessarily have a balanced innovation structure. Through the method designed in this paper, the spatial pattern of urban innovation can be more precise and comprehensive revealed, and provide useful references for the development of urban innovation.

scholarly journals Occurrence of tuberculosis cases in Crato, Ceará, from 2002 to 2011: a spatial analisys of specific standards

2015 ◽  
Vol 18 (2) ◽  
pp. 313-325 ◽  
Author(s):  
Mayrla Lima Pinto ◽  
Talina Carla da Silva ◽  
Lidiane Cristina Félix Gomes ◽  
Maria Rita Bertolozzi ◽  
Lourdes Milagros Mendoza Villavicencio ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Spatial Pattern ◽  
Urban Area ◽  
Temporal Trend ◽  
Kernel Method ◽  
Quantitative Approach ◽  
Point Pattern ◽  
Hybrid Design ◽  
Population Densities ◽  
Population Groups

OBJECTIVE: to analyze the spatial distribution of tuberculosis in Crato, Ceará, Brazil, from 2002 to 2011, aiming to check for a point pattern. METHODS: This is an ecological, temporal trend and hybrid design study, with a quantitative approach. A total of 261 cases of tuberculosis were geo-referenced and 20 (7.1%) were considered as losses due to the lack of address. The profile of patients in 10 years of study was in accordance with the following pattern: men aged between 20 and 59 years, with low schooling, affected by the pulmonary form of tuberculosis and who were cured from the disease. RESULTS: The analysis of the spatial distribution of tuberculosis points out that in the period of study, new cases of the disease were not distributed on a regular basis, indicating a clustered spatial pattern, confirmed by the L-function. The map with the density of new cases estimated by the Kernel method showed that the "hot" areas are more concentrated in the vicinity of the central urban area. CONCLUSION: The study allowed pointing out areas of higher and lower concentration of tuberculosis, identifying the spatial pattern, but it also recognized that the disease has not reached all of the population groups with the same intensity. Those who were most vulnerable were the ones who lived in regions with higher population densities, precarious living conditions, and with intense flow of people.

Potential contact statistics for measuring scale-dependent spatial pattern and association: an example of northern cod (Gadus morhua) and capelin (Mallotus villosus)

2000 ◽  
Vol 57 (7) ◽  
pp. 1355-1368 ◽  
Author(s):  
Richard L O'Driscoll ◽  
David C Schneider ◽  
George A Rose ◽  
George R Lilly
Keyword(s):  
Spatial Distribution ◽  
Spatial Pattern ◽  
Gadus Morhua ◽  
Atlantic Cod ◽  
Simulated Data ◽  
Point Pattern Analysis ◽  
Point Pattern ◽  
Mallotus Villosus ◽  
Capelin Mallotus Villosus ◽  
Potential Contact

Analysis of simulated data showed that potential contact statistics could be used to describe spatial pattern in sample density data. Potential contact is a new method, analogous to Ripley's K function for mapped point pattern analysis. Potential contact can be used to describe spatial pattern and association over a range of scales without grouping data and is robust against the presence of zeros. The statistical output is ecologically interpretable, as a measure of the degree of contact between individuals. This new technique was applied to examine changes in the spatial distribution of Atlantic cod (Gadus morhua) off Newfoundland, Canada, from 1985 to 1994, a period that encompassed a collapse of the cod stock. Sample data from bottom-trawl surveys indicated that cod were aggregated in patches with dimensions of 100-250 km. During the period of cod decline in the 1990s, spatial structure changed in three ways: the number of patches decreased, patch size shrank, and contact with conspecifics at small (10-20 km) scales fell. Cod were broadly associated with capelin (Mallotus villosus), a major prey species. Spatial distribution of capelin changed over the same time period as changes in cod distribution, and there was no evidence that contact between cod and capelin decreased.

scholarly journals Intra-plant spatial distribution of Thaumastocoris peregrinus Carpintero & Dellapé (Hemiptera: Thaumastocoridae) on Eucalyptus grandis plants

2016 ◽  
Vol 44 (3) ◽  
pp. 411-418 ◽  
Author(s):  
A. C. V. Lima ◽  
C. F. Wilcken ◽  
P. J. Ferreira-Filho ◽  
J. E. Serrão ◽  
J. C. Zanuncio
Keyword(s):  
Spatial Distribution ◽  
Eucalyptus Grandis ◽  
Plant Spatial Distribution

scholarly journals Geospatial characterizing of Under-Five Mortality in Alexandria, Egypt

2021 ◽  
Author(s):  
Mahmoud Adel Hassan ◽  
Ahmed Mohamed Ramadan ◽  
Mohamed Mostafa Tahoun ◽  
Abdelrahman Omran ◽  
Shimaa Gad El-karim Ali ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Spatial Distribution ◽  
Cardiovascular Diseases ◽  
Population Density ◽  
Spatial Pattern ◽  
Under Five ◽  
Size Population ◽  
Access To Water ◽  
Alexandria City ◽  
Low Incidence

This study aimed to identify geo-spatial pattern of under-five mortality (U5M) in Alexandria and its key determinants. We analyzed the geospatial distribution of 3064 deaths registered at 24 health offices reported from January 2018 to June 2019. The localities of Alexandria city were clustered into high and low incidence areas. Neonates represented 58.7% of U5M, while post-neonates and children were 31.1%, 10.2% respectively. Male deaths were significantly higher (P=0.036). The main leading causes of U5M were prematurity (28.32%), pneumonia (11.01%), cardiac arrest (10.57%), congenital malformation (9.95%), and childhood cardiovascular diseases (9.20%). Spatial distribution of U5M (including the most common three causes) tend to be clustered in western parts of Alexandria (El Hawaria, Bahig, Hamlis and Ketaa Maryiut). Another 9 clusters are at risk of being hotspots. Illiteracy, divorce, and poor locality characteristics (household size, population density, and access to water supply and sanitation), were statistically significant predictors of U5M.

scholarly journals Delineation of Genotype × Environment Interaction for Identification of Stable Genotypes to Grain Yield in Mungbean

2020 ◽  
Vol 2 ◽  
Author(s):  
Santhi Madhavan Samyuktha ◽  
Devarajan Malarvizhi ◽  
Adhimoolam Karthikeyan ◽  
Manickam Dhasarathan ◽  
Arumugam Thanga Hemavathy ◽  
...  
Keyword(s):  
Grain Yield ◽  
Tamil Nadu ◽  
Stability Index ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Genotype Environment Interaction ◽  
South Indian ◽  
Indian State ◽  
Wide Adaptation ◽  
High Yields

In the present study, fifty-two mungbean (Vigna radiata) genotypes were evaluated for seven morphological traits at three different environments in South Indian state Tamil Nadu, namely Virinjipuram (E1), Eachangkottai (E2), and Bhavanisagar (E3) during Kharif 2017, 2018, and 2019, respectively. The data collected were subjected to variability and correlation analyses, followed by stability analysis using additive main effects and multiplicative interaction (AMMI) model, genotype and genotype × environment interaction effects (GGE) biplot. Variablility was observed among the genotypes for the following traits viz., plant height, days to fifty per cent flowering, number of pods per plant, pod length, number of seeds per pod, hundred seed weight and grain yield. Correlation analysis showed that the trait number of pods per plant was significantly associated with grain yield. The G × E was smaller than the genetic variation of grain yield as it portrayed the maximum contribution of genotypic effects (61.07%). GGE biplot showed E3 as a highly discriminating and representative environment. It also identified environment-specific genotypes viz., EC 396111 for E1, EC 396125 for E2 and EC 396101 for E3 environments. The genotypes with minimum genotype stability index (GSI) viz., V2802BG (7), HG 22 (13), and EC 396098 (13) were observed with wide adaptation and high yields across all the three environments. In summary, we identified stable genotypes adapted across environments for grain yield. These genotypes can be used as parent/pre-breeding materials in future mungbean breeding programs.

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