Applying acoustic emission and neural network to classify wheat seeds from weed seeds

In the present study,an expert weed seeds recognition system combining acoustic emissions analysis,Multilayer Feedforward Neural Network(MFNN)classifier was developed and tested for classifying wheat seeds.This experiment was performed for classifying two major important wheat varieties from five species of weed seeds.In order to produce sound signals,a 60o inclined glass plate was used.Fast Fourier Transform(FFT),Phase and Power Spectral Density(PSD)of impact signals were calculated.All features of sound signals are computed via a 1024-point FFT.After feature generation,60%of data sets were used for training,20%for validation,and remaining samples were selected for testing.The optimized MFNN model was found to have 500-12-2 and 500-10-2 architectures for“101”and“Shiroodi”wheat varieties,respectively.The selection of the optimal model was based on the evaluation of mean square error(MSE)and correct separation rate(CSR).The CSR percentages for two wheat varieties were 100%.Considering the overall aspects of the results,it can be stated that the developed system was successful enough to correlate the acoustic features with wheat seed type.

Effect of Exogenous Gibberellin on Wheat Seed Germination under Salt Stress

[Objectives]In this experiment,wheat seeds were treated with different concentrations of gibberellin and different concentrations of salt solution to study the change of germination index of wheat seeds.[Methods]The germination rate,germination potential and germination index of wheat seeds were measured by routine methods,and the effect of exogenous gibberellin on germination of wheat seeds under salt stress was observed.[Results]The germination rate,germination potential and germination index of wheat seeds under salt stress were significantly increased after exogenous treatment of 0.25 and 0.50 g/L gibberellin within the range of salt concentration gradient.However,when the concentration of gibberellin was too high,it would inhibit the germination of seeds.[Conclusions]Appropriate concentration of gibberellin can effectively alleviate the stress caused by salt on wheat seed germination.In this experiment,the best concentration of gibberellin to alleviate salt stress was 0.25 g/L.

Preparation of a Novel Highly Effective and Environmental Friendly Wheat Seed Coating Agent

A novel environmental friendly wheat seed coating agent was prepared from the natural polymer,biological pesticide,microfertilizer,microelements and other additives.The laboratory and field test results showed that it could enhance the yield up to 16% and reduce its input cost to 1/6 as compared with the conventional wheat seed coating agent.It is safe without causing any pollution and would have significant economic and environmental benefits.

Proteomic Analysis of Wheat Seed in Response to Drought Stress

Drought stress is one of the major factors affecting in wheat yield and grain quality. In order to investigate how drought stress might influence wheat quality during grain filling, three wheat cultivars Gaocheng 8901, Jagger and Nongda 3406 were subjected to drought stress during the grain filling stage. Neither globulin and glutenin, nor the relative percentage ofamylose significantly changed following drought treatments, whereas albumin and gliadin concentrations did. The SDS-sedimentation, which has a strong linear correlation with wheat baking quality was markedly decreased following drought stress. These results indicated that drought had an adverse effect on wheat qualit3,. In order to investigate the protein complexes in the wheat flour, the data from native PAGE and SDS-PAGE were combined and a total of 14 spots were successfully identified, and of these eight protein types were determined to be potential complex forming proteins.

Negative Association between Seed Dormancy and Seed Longevity in Bread Wheat

Many organisms have dormant stages with an extension of their life span to increase longevity, and deeper dormancy is usually related to greater longevity. In cereal crops, seed dormancy is significantly associated with pre-harvest sprouting tolerance during seed development, as seed longevity is a valuable trait for seed banks and providing reliable crop seeds to farmers. In this study, we evaluated both seed dormancy and longevity in bread wheat based on germination and artificial aging tests. According to phenotypic clustering analysis, relative germination rate/potential and relative seedling vigor index were more effective to indicate seed longevity than relative electrical conductivity in wheat, while all the four investigated phenotypes of relative germination potential, relative germination rate, germination index and degree of seed dormancy fit well as a reflex of wheat seed dormancy. In the correlation analysis, the germination level of newly harvested grain negatively reflected its degree of seed dormancy, while the germination ability of grain after artificial aging reflected its seed longevity. However, in contrast to the current opinion in plant, seed dormancy was significantly negatively correlated to seed longevity in our study, and it was not an accidental phenomenon, for that the majority of accessions with high degree of seed dormancy had short seed longevity. To our knowledge, this is the first to report the negative association between seed dormancy and longevity in cereal crops. It would lead to further concerns about how to breed wheat with both prolonged seed longevity and deep dormancy to avoid pre-harvest sprouting.

Differentiation of storage time of wheat seed based on near infrared hyperspectral imaging

Seed aging during storage is one of the main factors that influence the quality of wheat seed.Current detection methods based on NIR spectra were mostly for group seeds,they had poor stability for single seed detection because of sample uniformity.In this study,the characteristic changes of single wheat seed during storage procedure were measured through hyperspectral imaging technology.Firstly,hyperspectral imaging data of wheat grain including six years from 2007 to 2012 had been collected.The original spectra showed clear difference in the band of 1400-1600 nm,which may be caused by the decreasing of moisture and protein content during storage;principal component analysis(PCA)was applied to analyze the spectral data of wheat grain including six years,the clustering chart of the principal components indicated that the grain between same or similar year have an clustering characteristic,and the characteristic difference would become obviously with the increasing of storage time;soft independent modeling of class analogy(SIMCA)was applied to classify the grain of different years,results showed that the classification accuracy of the dichotomy between adjacent years could reach 97.05%,and the accuracy of the mixed classification of six years could also reach 82.5%.These results indicated that hyperspectral imaging technology could be used to differentiate the quality change of wheat seed during different storage time,which could provide support for the intelligent monitoring of stored wheat seeds.