Research Notes : United States : Evaluation of soybean germplasm for stress tolerance biological efficiency : To evaluate soybean germplasm and cultivars for stress tolerance toward : Moisture Stress

Seventeen soybean genotypes were screened in a laboratory and growth-chamber experiment for water-stress tolerance characteristics. Three osmotic concentrations (0, -0.3 and -0.5 MPa) were used in an 8-day germination test conducted in the laboratory at Alabama A&M University. The Promptness Index (PI) and Germination Stress Index (GSI) were calculated (Bouslama and Schapaugh, 1984)

Research Notes : United States : Evaluation of soybean germplasm for stress tolerance biological efficiency : To evaluate soybean germplasm and cultivars for stress tolerance toward : Diseases

Screening of improved soybean lines from Alabama A&M University for multiple resistance against bacterial blight, stem canker, and soybean cyst nematode in the greenhouse and in the field continued at Alabama A&M University. Lines obtained from Virginia State University in MG IV (PI 339984, PI 408039, PI 80837); MG V (PI 96089, PI 123440, PI L-76-0132, PI L-77-0049, \u27Hill\u27, \u27Essex\u27); MG VI (FC 31665, PI 407868C, PI 159322, PI 416937, PI 379621, PI 221713, PI 230978, \u27Lee\u27); MG VII (PI 423911, PI 229358); and MG VIII (PI 417134, PI 417063, PI 417061, PI 416893) were screened. Initial results indicated PI L76-0049 is resistant to bacterial blight, PI 159322 and PI 230978 are resistant to soybean cyst nematode (race 3 and 5), and PI 417061 has multiple resistance to bacterial blight and stem canker

Research Notes : United States : Evaluation of soybean germplasm for stress tolerance and biological efficiency towards : Diseases

A field study was conducted for screening and selection of improved soybean germplasm for disease resistance in 1986. The soybean crossing block consisted of 207 germplasm entries screened at flowering and at maturity. One hundred and one were resistant and moderately resistant to bacterial blight (BB)

Research Notes : United States : Evaluation of soybean germplasm for stress tolerance and biological efficiency toward : Moisture Stress

Three soybean cultivars, \u27Lee-74\u27, \u27Wright\u27, and \u27RA 401\u27, were subjected to 100% (control), 75%, and 50% of field capacity during vegetative (Vl), flowering (R2), and pod-filling (R4) stages in greenhouse and field studies. Stress applied at R2 significantly reduced the yield in the green-house, while in the field, the maximum reduction was observed when the plants were subjected to stress at R4. Stress during Vl reduced the yield components less than stress applied during R2 or R4 stages in both studies

Research Notes : United States : Influence of genotype and growth stage on nitrogen fixation in soybeans

One of the many characteristics that makes soybeans a desirable crop is their ability to fix nitrogen. In order to enhance this ability, it is ne-cessary to look at the variation among various cultivars throughout their life cycle. Genetic studies for Spanish clover (Desmodium sandwicense E. Mey) by Pinchbeck et al. (1980) showed a significant difference among genotypes in their ability to fix nitrogen

Research Notes : Evaluation of soybean germplasm for aluminum tolerance

A growth-chamber experiment was conducted in nutrient solution containing 0 or 8 ppm of aluminum as Al2K(S04)3 to study differential Al tolerance of soybean germplasm representing Maturity Groups V, VI and VII, supplied by Dr. E. E. Hartwig. Two soybean cultivars, one sensitive (\u27Chief\u27) and the other tolerant (\u27Perry\u27), were included as standard checks (Fig. 1). Soybean roots were affected by the presence of Al and showed discoloration, stunted and blackish root tips

Scenario Based Run-time Switching for Adaptive CNN-based Applications at the Edge

Convolutional Neural Networks (CNNs) are biologically inspired computational models that are at the heart of many modern computer vision and natural language processing applications. Some of the CNN-based applications are executed on mobile and embedded devices. Execution of CNNs on such devices places numerous demands on the CNNs, such as high accuracy, high throughput, low memory cost, and low energy consumption. These requirements are very difficult to satisfy at the same time, so CNN execution at the edge typically involves trade-offs (e.g., high CNN throughput is achieved at the cost of decreased CNN accuracy). In existing methodologies, such trade-offs are either chosen once and remain unchanged during a CNN-based application execution, or are adapted to the properties of the CNN input data. However, the application needs can also be significantly affected by the changes in the application environment, such as a change of the battery level in the edge device. Thus, CNN-based applications need a mechanism that allows to dynamically adapt their characteristics to the changes in the application environment at run-time. Therefore, in this article, we propose a scenario-based run-time switching (SBRS) methodology, that implements such a mechanism

On 'Optimal Bidding in a Uniform Price Auction with Multi-Unit Demand'

On 'Optimal Bidding in a Uniform Price Auction with Multi-Unit Demand

Research Notes : United States : Evaluation of soybean germplasm for stress tolerance and biological efficiency : To evaluate soybean germplasm for biological efficiency in - Nitrogen Fixation

Twenty commercial soybean cultivars from maturity groups IV through VIII were screened for nitrogen-fixation in a growth chamber using Rhizobium strains 3IlB 6,122 and combination of 6 and 122. The data on nodule number, nodule weight, shoot fresh weight, shoot dry weight, and acetylene reduction were recorded. Among twenty cultivars, \u27Lee 74\u27 (MG IV), \u27Bay\u27 (MG V), and \u27Essex\u27 (MG V) were identified as high N-fixers, based on more nodules and high acetylene reduction

Evolution of the electronic structure with size in II-VI semiconductor nanocrystals

In order to provide a quantitatively accurate description of the band gap variation with sizes in various II-VI semiconductor nanocrystals, we make use of the recently reported tight-binding parametrization of the corresponding bulk systems. Using the same tight-binding scheme and parameters, we calculate the electronic structure of II-VI nanocrystals in real space with sizes ranging between 5 and 80 {\AA} in diameter. A comparison with available experimental results from the literature shows an excellent agreement over the entire range of sizes.Comment: 17 pages, 4 figures, accepted in Phys. Rev.