scholarly journals Nail-Board Method of Root Sampling

1964 ◽  
Vol 17 (2) ◽  
pp. 85 ◽  
Author(s):  
J. L. Schuster ◽  
C. H. Wasser
Keyword(s):  
Root Sampling

scholarly journals USEFULNESS OF EARLY DIAGNOSTIC METHODS FOR EFFECTIVE MANAGEMENT OF BASAL STEM ROT (GANODERMA) DISEASE OF COCONUT

CORD ◽  
2002 ◽  
Vol 18 (01) ◽  
pp. 34
Author(s):  
A. Karthikeyan ◽  
S. Mohan ◽  
R. Bhaskaran
Keyword(s):  
Disease Index ◽  
Diagnostic Methods ◽  
Stem Rot ◽  
Symptom Expression ◽  
Effective Management ◽  
Visual Symptom ◽  
Basal Stem Rot ◽  
Relative Water ◽  
Root Sampling ◽  
Rot Disease

Chemodiagnostic methos EDTA and TTC  tests and physiological parameters electrical conductivity and relative water content are useful to detect the basal stem rot disease in coconut palms, 4 - 14 months before visual symptom expression.  The critical values of these tests  for symptom expression have been fixed.  In coconut trees, root sampling from  any directions at 15 - 30 cm depth is optimum for early detection tests.  Coconut palms without symptoms but showing higher values in diagnostic tests responded well to treatments by registering lesser disease index and higher  nut yield than the treated palms with  external symptoms.

scholarly journals A Large Root Phenome Dataset Wide-Opened the Potential for Underground Breeding in Soybean

2021 ◽  
Vol 12 ◽  
Author(s):  
Ki-Seung Kim ◽  
Se-Hun Kim ◽  
Jaeyoung Kim ◽  
Pooja Tripathi ◽  
Jeong-Dong Lee ◽  
...  
Keyword(s):  
Morphological Traits ◽  
Principal Component ◽  
Average Diameter ◽  
Wild Plants ◽  
Cultivated Plants ◽  
Plant Organ ◽  
In The Wild ◽  
Root Sampling ◽  
Highly Correlated ◽  
Cultivated Soybean

The root is the most critical plant organ for water and nutrient acquisition. Although the root is vital for water and nutrient uptake, the diverse root characters of soybean still need to be identified owing to the difficulty of root sampling. In this study, we used 150 wild and 50 cultivated soybean varieties to collect root image samples. We analyzed root morphological traits using acquired-image. Except for the main total length (MTL), the root morphological traits for most cultivated and wild plants were significantly different. According to correlation analysis, the wild and cultivated plants showed a significant correlation among total root length (TRL), projected area (PA), forks, total lateral length (TLL), link average diameter, and MTL. In particular, TRL was highly correlated with PA in both cultivated (0.92) and wild (0.82) plants compared with between MTL (0.43 for cultivated and 0.27 for wild) and TLL (0.82 for cultivated and 0.52 for wild). According to principal component analysis results, both plants could be separated; however, there was some overlap of the traits among the wild and cultivated individuals from some regions. Nevertheless, variation among the cultivated plants was higher than that found in the wild plants. Furthermore, three groups, including MTL, TLL, and the remaining traits, could explain all the variances.

An optimized fine root sampling methodology balancing accuracy and time investment

2012 ◽  
Vol 366 (1-2) ◽  
pp. 351-361 ◽  
Author(s):  
G. Berhongaray ◽  
J. S. King ◽  
I. A. Janssens ◽  
R. Ceulemans
Keyword(s):  
Fine Root ◽  
Sampling Methodology ◽  
Time Investment ◽  
Root Sampling

Spatial distribution of roots, nematode populations and root necrosis in highland banana in Uganda

Nematology ◽  
2004 ◽  
Vol 6 (1) ◽  
pp. 7-12 ◽  
Author(s):  
Imelda Kashaija ◽  
Beverley McIntyre ◽  
Henry Ssali ◽  
Fred Kizito
Keyword(s):  
Spatial Distribution ◽  
Damage Assessment ◽  
Root Biomass ◽  
Management Practices ◽  
Nematode Species ◽  
Horizontal Distribution ◽  
Radopholus Similis ◽  
Root Necrosis ◽  
Root Sampling ◽  
Distribution Of Roots

Abstract Banana root distribution, nematodes, and necrosis were assessed in banana (Musa AAA) monoculture and banana-legume intercrops in Uganda, with the aim of establishing their relationship in order to enhance decision making with regard to management practices and sampling for nematode population and damage assessment. The intercrops had no effect on the vertical or the horizontal distribution of banana roots and nematodes. Approximately 90% of the root biomass was in the upper 0.3 m and none was below 0.7 m. Within 0.5 m of the banana mat, the majority of root mass was in the surface 0.15 m, but outside this radius more were found from 0.15-0.3 m. This spatial distribution suggests that fertiliser applications would be most effectively applied within a 0.5 m radius of the banana mat. Nematode species and root necrosis were uniformly distributed horizontally on the roots; vertical distribution differed among species. Significantly larger populations of Radopholus similis were found in the upper 0.3 m; none was present below 0.5 m. Helicotylenchus multicinctus and Pratylenchus goodeyi were found throughout the rooting profile; H. multicinctus density being high in the upper 0.5 m, while P.goodeyi was generally low throughout. More root necrosis was noted in the upper 0.3 m, coinciding with the greatest population density of R. similis and the greatest amount of root biomass. The spatial distribution of nematodes indicates that root sampling and nematicide application should be concentrated within 0.5 m of the banana mat.

Seasonal variations in a Douglas fir stand in total and soluble nitrogen in inner bark and root and in total and mineralizable nitrogen in soil

1977 ◽  
Vol 7 (4) ◽  
pp. 641-647 ◽  
Author(s):  
R. van den Driessche ◽  
J. E. Webber
Keyword(s):  
Mineral Soil ◽  
Douglas Fir ◽  
Soluble Nitrogen ◽  
Total N ◽  
Inner Bark ◽  
Root Sampling ◽  
Mineralizable Nitrogen ◽  
Proline Concentration ◽  
Arginine Concentration ◽  
Urea Fertilization

Monthly sampling of stem inner bark, roots, litter, humus, and mineral soil was carried out in six 0.1-ha plots in a 47-year-old Douglas fir (Pseudotsugamenziesii (Mirb.) Franco) stand for 1 year. Pairs of plots had received urea fertilization at the rates of 0, 224, and 448 kg nitrogen (N)/ha 4 years previously. Inner bark and roots were chemically analysed to determine concentrations of total N, soluble N, ninhydrin-positive compounds, monosubstituted guanidino amino compounds, arginine, and proline. Concentration of total N was determined in litter, humus, and mineral soil samples, and concentration of mineralizable N was also determined in humus and mineral soil.All sets of data showed an effect of season, but analysis of root soluble N, root guanidino compounds, root arginine, and litter total N were the most satisfactory for distinguishing differences in N level due to fertilizer treatments. For this purpose root sampling was best done in June and July, and litter sampling between January and May. Soluble N concentration was higher in inner bark than in roots, but arginine concentration was higher in roots than in inner bark. Root arginine concentration was high in winter and decreased to a low level in October before starting to accumulate again, suggesting it behaves as a N storage compound. Litter total N showed a decrease in concentration in July and August, followed by a recovery.

scholarly journals Adaptive planning in human search

2018 ◽  
Author(s):  
Moritz J. F. Krusche ◽  
Eric Schulz ◽  
Arthur Guez ◽  
Maarten Speekenbrink
Keyword(s):  
Test Problems ◽  
Two Dimensional ◽  
Complex Environments ◽  
Adaptive Planning ◽  
Restricted Movement ◽  
Planning Algorithm ◽  
Complex Models ◽  
Root Sampling ◽  
Foraging Task

AbstractHow do people plan ahead when searching for rewards? We investigate planning in a foraging task in which participants search for rewards on an infinite two-dimensional grid. Our results show that their search is best-described by a model which searches at least 3 steps ahead. Furthermore, participants do not seem to update their beliefs during planning, but rather treat their initial beliefs as given, a strategy similar to a heuristic called root-sampling. This planning algorithm corresponds well with participants’ behavior in test problems with restricted movement and varying degrees of information, outperforming more complex models. These results enrich our understanding of adaptive planning in complex environments.

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