Irrigated pinto bean crop stress and yield assessment using ground based low altitude remote sensing technology

The pinto bean is one of widely consumed legume crop that constitutes over 42%of the U.S dry bean production.However,limited studies have been conducted in past to assess its quantitative and qualitative yield potentials.Emerging remote sensing technologies can help in such assessment.Therefore,this study evaluates the role of ground-based multispectral imagery derived vegetation indices(VIs)for irrigated the pinto bean stress and yield assessments.Studied were eight cultivars of the pinto bean grown under conventional and strip tillage treatments and irrigated at 52%and 100%of required evapotranspiration.Imagery data was acquired using a five-band multispectral imager at early,mid and late growth stages.Commonly used 25 broadband VIs were derived to capture crop stress traits and yield potential.Principal component analysis and Spearman’s rank correlation tests were conducted to identify key VIs and their correlation(rs)with abiotic stress at each growth stage.Transformed difference vegetation index,nonlinear vegetation index(NLI),modified NLI and infrared percentage vegetation index(IPVI)were consistent in accounting the stress response and crop yield at all growth stages(rs>0.60,coefficient of determination(R2):0.50–0.56,P<0.05).Ten other VIs significantly accounted for crop stress at early and late stages.Overall,identified key VIs may be helpful to growers for precise crop management decision making and breeders for crop stress response and yield assessments.

Research of Step-down Stress Accelerated Degradation Data Assessment Method of a Certain Type of Missile Tank

The performance degradation rates of the missile tank are generally time-varying functions uneasily evaluated by general classical evaluation methods. This paper develops a segmented nonlinear accelerated degradation model （SNADM） based on the equivalent method of accumulative damage theory, which tackles the problem that product life is difficult to be determined with degradation rate being a function of the variable of time. A segmented expression of the function of population accumulative degradation is derived. And combined with nonlinear function, an accelerated degradation function, i.e., SNADM is obtained. The parameters of the SNADM are identified by numerical iteration, and the statistical function of degradation track is extrapolated. The reliability function is determined through the type of random process of the degradation distribution. Then an evaluation of product storage life is undertaken by combining the statistical function of degradation track, reliability function and threshold. An example of a missile tank undergoes a step-down stress accelerated degradation test （SDSADT）, in which the results with the SNADM and the classical method are evaluated and compared. The technology introduced is validated with the resultant coincidence of both evaluated and field storage lives.