Effects of Music Acoustic Frequency on Indoleacetic Acid in Plants

[Objective] The aim was to study the effects of music acoustic frequency on the contents of indoleacetic acid（IAA） in 6 species of vegetables.[Method] Music acoustic frequency group and control group were designed to determine the related growth indicators of unified managed 6 species of vegetables regularly.The contents of indoleacetic acid were detected by the High Performance Liquid Chromatography（HPLC）.[Result] The music acoustic frequency had significantly increased the contents of indoleacetic acid in 6 species of vegetables,which were significantly higher than that in the control.[Conclusion] The music acoustic frequency could stimulate the IAA secretion in plants.

Developing crop specific area frame stratifications based on geospatial crop frequency and cultivation data layers

Area Sampling Frames （ASFs） are the basis of many statistical programs around the world. To improve the accuracy, objectivity and efficiency of crop survey estimates, an automated stratification method based on geospatial crop planting frequency and cultivation data is proposed. This paper investigates using 2008-2013 geospatial corn, soybean and wheat planting frequency data layers to create three corresponding single crop specific and one multi-crop specific South Dakota （SD） U.S. ASF stratifications. Corn, soybeans and wheat are three major crops in South Dakota. The crop specific ASF stratifications are developed based on crop frequency statistics derived at the primary sampling unit （PSU） level based on the Crop Frequency Data Layers. The SD corn, soybean and wheat mean planting frequency strata of the single crop stratifications are substratified by percent cultivation based on the 2013 Cultivation Layer. The three newly derived ASF stratifications provide more crop specific information when compared to the current National Agricultural Statistics Service （NASS） ASF based on percent cultivation alone. Further, a multi-crop stratification is developed based on the individual corn, soybean and wheat planting frequency data layers. It is observed that all four crop frequency based ASF stratifications consistently predict corn, soybean and wheat planting patterns well as verified by the 2014 Farm Service Agency （FSA） Common Land Unit （CLU） and 578 administrative data. This demonstrates that the new stratifications based on crop planting frequency and cultivation are crop type independent and applicable to all major crops. Further, these results indicate that the new crop specific ASF stratifications have great potential to improve ASF accuracy, efficiency and crop estimates.