Effect of Within-field Variation in Soil Texture on Heterodera glycines and Soybean Yield

The influence of soil texture on Soybean yield in the presence of Heterodera glycines was investigated by comparing yields of susceptible cultivars with a resistant cultivar for 2 years. Soybean yield was negatively correlated with increasing sand content (P = 0.05). Yields of susceptible cultivars were suppressed with increasing sand content. Final nematode population densities were lowest in plots with greatest sand content. Soybean infection by SCN, as determined by the number of cysts 30 days after planting, was not consistently related to soil texture over 2 years. Initial nematode population density was positively related to soybean yield the first year and negatively related to soybean yield the second, probably a result of greater yield suppression by H. glycines in plots with greater sand content.     

The influence of food plant dispersion on caterpillar searching success

Abstract. 1. Collards (Brassica oleracea L.) grown in clumps were more difficult for unstarved, early instar cabbage white caterpillars (Pieris rapae L.) to find than collards spaced at regular intervals, although total plant densities were identical.
2. Early instar, unstarved larvae are less mobile than later instar larvae (our data) or starved larvae (Jones' 1977 data).
3. Starved larvae and late instar larvae tend to find plants more readily than do unstarved or younger larvae.
4. We contend that larval mobility governs the success of searching caterpillars and their sensitivity to variations in plant dispersion.
5. Our results show that the dispersion of targets can influence searching success even though target density is constant. This means that the degree of clumping in host plants is capable of influencing their availability to herbivores.     

The response of stream macroinvertebrates to substrate size and heterogeneity

Manipulations of substrate size and components of heterogeneity were designed to test their independent effects and interactions on the abundance and species richness of stream macroinvertebrates. Two components of substrate heterogeneity, variation in size class proportions and number of size classes, had no independent effect on abundance or richness; and in general did not interact with median particle size. Median particle size, stream current, and detritus accounted for most of the significant variation in macroinvertebrates colonizing the experimental substrates. Rocks with high surface heterogeneity (roughness) were colonized by more individuals (but not taxa) than rocks with low surface heterogeneity.     

Influence of root density on the critical soil water potential

Estimation of root water uptake in crops is important for making many other agricultural predictions. This estimation often involves two assumptions: (1) that a critical soil water potential exists which is constant for a given combination of soil and crop and which does not depend on root length density, and (2) that the local root water uptake at given soil water potential is proportional to root length density. Recent results of both mathematical modeling and computer tomography show that these assumptions may not be valid when the soil water potential is averaged over a volume of soil containing roots. We tested these assumptions for plants with distinctly different root systems. Root water uptake rates and the critical soil water potential values were determined in several adjacent soil layers for horse bean (Vicia faba) and oat (Avena sativa) grown in lysimeters, and for field-grown cotton (Gossypium L.), maize (Zea mays) and alfalfa (Medicago sativa L.) crops. Root water uptake was calculated from the water balance of each layer in lysimeters. Water uptake rate was proportional to root length density at high soil water potentials, for both horse bean and oat plants, but root water uptake did not depend on root density for horse bean at potentials lower than −25 kPa. We observed a linear dependency of a critical soil water potential on the logarithm of root length density for all plants studied. Soil texture modified the critical water potential values, but not the linearity of the relationship. B E Clothier Section editor     

Effect of soil acidity and saturating cation on adsorption of urea in soil

Summary Elevating the pH of two extremely acid tropical soils from an initial pH of 4 to 5 with Ca(OH)₂ and NaOH solutions resulted in a sharp decrease in urea adsorption. Further increases in pH to 9 caused only slight further decrease in urea adsorption. Ca treatment resulted in slightly higher adsorption than Na treatment over the full range of pH values studied for a clay soil with high smectite content, and for a loam with kaolinite mineralogy below pH 7. Above pH 7 a kaolinitic loamy soil gave slightly higher adsorption with Na treatment than with Ca.     

A helicoidal cell wall texture in root hairs ofLimnobium stoloniferum

Summary The cell wall of root hairs ofLimnobium stoloniferum is composed of two fibrillar layers: an outer layer with a dispersed texture and an inner layer with a helicoidal texture. In stained oblique sections the helicoidal layer appears as a series of bow-shaped structures. In sections which were shadow-casted after the embedding medium was removed, the following properties of the helicoidal layer can be directly observed. (1) It is build up of superimposed lamellae. (2) Each lamella consists of parallel oriented microfibrils. (3) Going into the helicoidal layer, there is a counter-clockwise discontinuous rotation of the microfibril orientation in successive lamellae. (4) Between adjacent lamellae the average angular displacement of the microfibril orientation is about 23 degrees. The dispersed outer layer is also polylamellated, but with randomly arranged microfibrils in each lamella. Both layers are present in the lateral wall as well as in the apical wall of the root hairs. Observations indicate that in the cell wall of the tip the parallel oriented microfibrils of the outermost helicoidal lamellae become distorted towards a dispersed arrangement. The suggestion is made that the dispersed outer layer is derived from the helicoidal layer.     

On dose cube pixel spacing pre-processing for features extraction stability in dosiomic studies

PurposeDosiomics allows to parameterize regions of interest (ROIs) and to produce quantitative dose features encoding the spatial and statistical distribution of radiotherapy dose. The stability of dosiomics features extraction on dose cube pixel spacing variation has been investigated in this study.Material and MethodsBased on 17 clinical delivered dose distributions (P_n), dataset has been generated considering all the possible combinations of four dose grid resolutions and two calculation algorithms. Each dose voxel cube has been post-processed considering 4 different dose cube pixel spacing values: 1x1x1, 2x2x2, 3x3x3 mm³ and the one equal to the planning CT. Dosiomics features extraction has been performed from four different ROIs. The stability of each extracted dosiomic feature has been analyzed in terms of coefficient of variation (CV) intraclass correlation coefficient (ICC).ResultsThe highest CV mean values were observed for PTV ROI and for the grey level size zone matrix features family. On the other hand, the lowest CV mean values have been found for RING ROI for the grey level co-occurrence matrix features family. P₃ showed the highest percentage of CV >1 (1.14%) followed by P₁₅ (0.41%), P₁ (0.29%) and P13 (0.19%). ICC analysis leads to identify features with an ICC >0.95 that could be considered stable to use in dosiomic studies when different dose cube pixel spacing are considered, especially the features in common among the seventeen plans.ConclusionConsidering the observed variability, dosiomic studies should always provide a report not only on grid resolution and algorithm dose calculation, but also on dose cube pixel spacing.     

Soil nitrous oxide emissions following crop residue addition: a meta‐analysis

Annual production of crop residues has reached nearly 4 billion metric tons globally. Retention of this large amount of residues on agricultural land can be beneficial to soil C sequestration. Such potential impacts, however, may be offset if residue retention substantially increases soil emissions of N₂O, a potent greenhouse gas and ozone depletion substance. Residue effects on soil N₂O emissions have gained considerable attention since early 1990s; yet, it is still a great challenge to predict the magnitude and direction of soil N₂O emissions following residue amendment. Here, we used a meta‐analysis to assess residue impacts on soil N₂O emissions in relation to soil and residue attributes, i.e., soil pH, soil texture, soil water content, residue C and N input, and residue C : N ratio. Residue effects were negatively associated with C : N ratios, but generally residue amendment could not reduce soil N₂O emissions, even for C : N ratios well above ca. 30, the threshold for net N immobilization. Residue effects were also comparable to, if not greater than, those of synthetic N fertilizers. In addition, residue effects on soil N₂O emissions were positively related to the amounts of residue C input as well as residue effects on soil CO₂ respiration. Furthermore, most significant and stimulatory effects occurred at 60–90% soil water‐filled pore space and soil pH 7.1–7.8. Stimulatory effects were also present for all soil textures except sand or clay content ≤10%. However, inhibitory effects were found for soils with >90% water‐filled pore space. Altogether, our meta‐analysis suggests that crop residues played roles beyond N supply for N₂O production. Perhaps, by stimulating microbial respiration, crop residues enhanced oxygen depletion and therefore promoted anaerobic conditions for denitrification and N₂O production. Our meta‐analysis highlights the necessity to connect the quantity and quality of crop residues with soil properties for predicting soil N₂O emissions.     

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

We demonstrate methods for the detection of architectural distortion in prior mammograms of interval-cancer cases based on analysis of the orientation of breast tissue patterns in mammograms. We hypothesize that architectural distortion modifies the normal orientation of breast tissue patterns in mammographic images before the formation of masses or tumors. In the initial steps of our methods, the oriented structures in a given mammogram are analyzed using Gabor filters and phase portraits to detect node-like sites of radiating or intersecting tissue patterns. Each detected site is then characterized using the node value, fractal dimension, and a measure of angular dispersion specifically designed to represent spiculating patterns associated with architectural distortion.Our methods were tested with a database of 106 prior mammograms of 56 interval-cancer cases and 52 mammograms of 13 normal cases using the features developed for the characterization of architectural distortion, pattern classification via quadratic discriminant analysis, and validation with the leave-one-patient out procedure. According to the results of free-response receiver operating characteristic analysis, our methods have demonstrated the capability to detect architectural distortion in prior mammograms, taken 15 months (on the average) before clinical diagnosis of breast cancer, with a sensitivity of 80% at about five false positives per patient.