Optimizing nitrogen loading of Picea mariana seedlings during nursery culture

2003 ◽  
Vol 33 (7) ◽  
pp. 1287-1294 ◽  
Author(s):  
K F Salifu ◽  
V R Timmer
Keyword(s):  
Plant Growth ◽  
Picea Mariana ◽  
Black Spruce ◽  
Nutrient Deficiency ◽  
Nitrogen Loading ◽  
Optimum Level ◽  
Luxury Consumption ◽  
N Content ◽  
Nursery Culture ◽  
Linear Relationships

Plant growth and nutrient uptake response to increased fertilization can be conceptually described by cur vi linear relationships depicting phases of nutrient deficiency, sufficiency, luxury consumption, and toxicity to rationalize fertilizer prescriptions and improve nutrient diagnosis. We validated this model to determine optimum nitrogen storage of young black spruce (Picea mariana (Mill.) BSP). Container seedlings were supplied with a mixed nitrogen–phosphorus–potassium (N–P–K) fertilizer at rates ranging from 0 to 80 mg N/seedling and reared in a greenhouse for one growing season. Plant growth and nutritional parameters of the plants exhibited classic responses of N deficiency, luxury consumption, and toxicity that were corroborated by vector diagnosis and appeared consistent with the conceptual model. Seedling biomass production was maximized at sufficiency (30 mg N/seedling), whereas N content of tissues peaked at the optimum loading rate (64 mg N/seedling). Toxicity occurred at the 80 mg N/seedling dose rate that increased plant N concentration (5%) but reduced growth (17%) and N content (14%) relative to the optimum level. Plant N content was raised 150% by optimum loading, exemplifying the effectiveness of this practice for building internal N reserves prior to planting. The newly validated model will help refine fertilizer recommendations and nutrient diagnosis for other species or cultural systems.

Growth and nitrogen retranslocation of nutrient loaded Picea mariana seedlings planted on boreal mixedwood sites

2001 ◽  
Vol 31 (8) ◽  
pp. 1357-1366 ◽  
Author(s):  
Moses Imo ◽  
Victor R Timmer
Keyword(s):  
Picea Mariana ◽  
Nutrient Loading ◽  
Black Spruce ◽  
N Uptake ◽  
Nutrient Mobilization ◽  
N Accumulation ◽  
Northern Ontario ◽  
Nursery Culture ◽  
Forest Sites ◽  
Seedling Biomass

Enhanced nutrient mobilization from old to current growth is a key mechanism that confers competitive ability to nutrient-loaded black spruce (Picea mariana (Mill.) BSP) seedlings planted on high-competition forest sites in northern Ontario. This study examines effects of nutrient loading and differing vegetation management (herbicide, fertilization, shading) on growth, partitioning, and net retranslocation of N between current and old shoots of newly planted black spruce seedlings on six contrasting boreal sites. Nutrient loading during nursery culture improved seedling growth and N uptake and retranslocation after transplanting. Herbicide application accelerated growth and N uptake only on the high-competition Alnus, hardwood, and mixedwood sites but had no effect on the less competitive feathermoss and Vaccinium sites. Weed removal on competitive sites reduced N retranslocation significantly. Field fertilization reduced N retranslocation in seedlings and promoting tree growth and N uptake on the less competitive feathermoss and Vaccinium sites. However, fertilization stimulated weeds on high-competition sites suppressing seedling biomass and N uptake. Factors that seem to affect net N retranslocation include the type and level of internal N reserves, biomass and N accumulation and partitioning, external N supply, and other stresses that limit plant growth such as competition.

Clonal and nonclonal genetic structure of subarctic black spruce (Picea mariana) populations in Yukon territory

Botany ◽  
2011 ◽  
Vol 89 (2) ◽  
pp. 133-140 ◽  
Author(s):  
Marios Viktora ◽  
Rodney A. Savidge ◽  
Om P. Rajora
Keyword(s):  
Genetic Structure ◽  
Picea Mariana ◽  
Black Spruce ◽  
A Priori ◽  
Nuclear Genome ◽  
Yukon Territory ◽  
Fire Disturbance ◽  
Clone Size ◽  
Flat Terrain ◽  
Individual Trees

Black spruce (Picea mariana) reproduces sexually from seeds and asexually by layering. There is a prevalent concept that clonal reproduction maintains populations of this species in the subarctic and arctic regions. We used microsatellite DNA markers of the nuclear genome to investigate the genetic structure of montane and subalpine black spruce populations from the Western Yukon Plateau in relation to this concept. Sixty individual trees at a minimum distance of 4 m from each other were sampled from each of four populations and individual trees were genotyped for eight microsatellite loci. Each of the 60 individuals from three montane pure black spruce populations growing on flat terrain at relatively low elevations had unique multilocus genotypes, indicating an absence of clonal structure in those populations. However, in an anthropologically undisturbed climax white spruce-dominated subalpine black spruce population on a northwest slope near Mount Nansen, the majority of the sampled individuals belonged to eight genetically distinct clones (genets). Clone size differed by altitude, the dominant genet being nearest the timberline–tundra ecotone. The results indicate that black spruce reproduction is variable and adaptive, being primarily sexual in flat-terrain montane populations previously subjected to fire disturbance, but mixed vegetative–sexual in the anthropogenically undisturbed subalpine population. This study is the first to employ molecular markers a priori to examine the mode of reproduction in natural black spruce populations.

scholarly journals Comparative Height Growth of Eastern Larch and Black Spruce in Northwestern Ontario

1978 ◽  
Vol 54 (6) ◽  
pp. 296-297 ◽  
Author(s):  
Douglas A. Mead
Keyword(s):  
Picea Mariana ◽  
Black Spruce ◽  
Height Growth ◽  
Larix Laricina ◽  
Stem Analysis ◽  
Northwestern Ontario ◽  
Analysis Methods ◽  
Spruce Stands

Height growth of eastern larch (Larix laricina (Du Roi) K. Koch) and black spruce (Picea mariana (Mill.) B.S.P.) was determined using standard stem analysis methods on trees from two sites in northwestern Ontario. The data were obtained from mixed larch-spruce stands which were relatively undisturbed. The larch exhibited substantially better height growth than the spruce through age 65.

SEASONAL DAMAGE BY INSECTS AND SQUIRRELS TO FEMALE REPRODUCTIVE STRUCTURES OF BLACK SPRUCE, PICEA MARIANA (MILL.) B.S.P.

1988 ◽  
Vol 120 (12) ◽  
pp. 1113-1121 ◽  
Author(s):  
Y.H. Prévost ◽  
J.E. Laing ◽  
V.F. Haavisto
Keyword(s):  
Picea Mariana ◽  
Black Spruce ◽  
Choristoneura Fumiferana ◽  
Tamiasciurus Hudsonicus ◽  
Red Squirrel ◽  
Red Squirrels ◽  
Reproductive Structures ◽  
Cone Axis ◽  
Viable Seeds ◽  
Cone Growth

AbstractThe seasonal damage to female reproductive structures (buds, flowers, and cones) of black spruce, Picea mariana (Mill.) B.S.P., was assessed during 1983 and 1984. Nineteen insects (five Orders) and the red squirrel, Tamiasciurus hudsonicus (Erxleben), were found feeding on these reproductive structures. Collectively, these organisms damaged 88.9 and 53.5% of the cones in 1983 and 1984, respectively. In the 2 years, Lepidoptera damaged 61.8% of the cones in 1983 and 44.4% of the cones in 1984. The spruce budworm, Choristoneura fumiferana (Clem.), and the spruce coneworm, Dioryctria reniculelloides Mut. and Mun., were the most important pests. Cones damaged by Lepidoptera could be classed into three categories: (a) severe, yielding no seeds; (b) moderate, yielding 22.3 seeds per cone; and (c) light, yielding 37.5 seeds per cone. Undamaged cones yielded on average 39.9 seeds per cone. Red squirrels removed 18.8% of the cones in 1983 and none in 1984. The spruce cone axis midge, Dasineura rachiphaga Tripp, and the spruce cone maggot, Lasiomma anthracinum (Czerny), caused minor damage in both years. Feeding by spruce cone axis midge did not reduce cone growth significantly or the number of viable seeds per cone, but feeding by the spruce cone maggot did. During both years new damage by insects to the female reproductive structures of the experimental trees was not observed after mid-July. In 1983 damage by red squirrels occurred from early to late September. In 1984 damage to cones on trees treated with dimethoate was 15.6% compared with 53.5% for untreated trees, without an increase in the number of aborted cones.

Prediction and evaluation of borate distribution in Eastern black spruce (Picea mariana var. mariana) wood products

2015 ◽  
Vol 49 (3) ◽  
pp. 457-473 ◽  
Author(s):  
Thierry Koumbi-Mounanga ◽  
Paul I. Morris ◽  
Myung J. Lee ◽  
Nasmus M. Saadat ◽  
Brigitte Leblon ◽  
...  
Keyword(s):  
Picea Mariana ◽  
Black Spruce ◽  
Wood Products

scholarly journals A Study of Factors Influencing Plant Growth by WSN Approach and Plant Nutrient Deficiency Classification in Tomato Using SVM

2021 ◽  
Vol 23 (06) ◽  
pp. 36-46
Author(s):  
Vrunda Kusanur ◽  
◽  
Veena S Chakravarthi ◽  
Keyword(s):  
Machine Learning ◽  
Plant Growth ◽  
Nutrient Deficiency ◽  
Learning Model ◽  
Plant Nutrients ◽  
Polynomial Kernel ◽  
Second Phase ◽  
Nutrient Deficiencies ◽  
Deficiency Symptoms ◽  
Machine Learning Model

Soil temperature and humidity straight away influence plant growth and the availability of plant nutrients. In this work, we carried out experiments to identify the relationship between climatic parameters and plant nutrients. When the relative humidity was very high, deficiency symptoms were shown on plant leaves and fruits. But, recognizing and managing these plant nutrients manually would become difficult. However, no much research has been done in this field. The main objective of this research was to propose a machine learning model to manage nutrient deficiencies in the plant. There were two main phases in the proposed research. In the first phase, the humidity, temperature, and soil moisture in the greenhouse environment were collected using WSN and the influence of these parameters on the growth of plants was studied. During experimentation, it was investigated that the transpiration rate decreased significantly and the macronutrient contents in the plant leave decreased when the humidity was 95%. In the second phase, a machine learning model was developed to identify and classify nutrient deficiency symptoms in a tomato plant. A total of 880 images were collected from Bingo images to form a dataset. Among all these images, 80% (704 images) of the dataset were used to train the machine learning model and 20% (176 images) of the dataset were used for testing the model performance. In this study, we selected K-means Clustering for key points detection and SVM for classification and prediction of nutrient stress in the plant. SVM using linear kernel performed better with the accuracy rates of 89.77 % as compared to SVM using a polynomial kernel.

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