The effects of grain texture and phenotypic traits on the thin-layer drying rate in maize(Zea mays L.) inbred lines

To explore the relation of maize grain texture and phenotypic traits with grain thin-layer drying rate,we observed the ultra-structure of maize grain,and tested three traits about the maize grain texture and four phenotypic traits.The vitreous part percentage was different（P〈0.05） among different maize inbred lines.There was a significant relationship between the drying rate with grain texture and phenotypic traits.Main factors that influenced the drying rate were different during different drying stages.New results observed that empirical constants（k and N） in drying equation were different for seed of the 30 inbred lines of maize.The k of simplified diffusion equation and N of page equation were significantly influenced by both grain texture and phenotypic traits.These results could be used as guideline parameters for drying maize seeds having different grain characteristics during different drying stages.

Rapid estimation of apple phenotypic parameters based on 3D reconstruction

In order to obtain the phenotypic parameters of apple quickly and accurately,which were commonly used as the basis of fruit sorting,a fast estimation method of apple phenotypic parameters based on three-dimensional(3D)reconstruction was proposed in this study.In this study,a three-dimensional model was constructed to estimate the phenotypic parameters of apple,such as volume,height,diameter,and fruit shape index.Firstly,an image acquisition system was built to capture sequence images of fruit with a binocular stereo vision system,and the images were extracted and matched using the Accelerated-KAZE algorithm to create the point cloud data.Secondly,the point cloud data were matched with the algorithm of Iterative Closest Point to establish a whole model of apple,and the surface reconstruction model of fruit was obtained by constructing irregular triangulation network.Finally,the apple phenotypic parameters were calculated by means of segmentation,surface complement and integral of the fruit model.Total of 200 apples were used as samples in the experiment.By this method,the phenotypic parameters of the apples were estimated based on their 3D reconstruction model,and the linear regression analysis was carried out between the estimated values and the real values.The results showed that R2 of the linear regression fitting of each parameter was higher than 0.90.Among them,the fitting of volume was the best with R2 of 0.97.In addition,the average errors of apple volume,height,fruit shape index,maximum diameter D and minimum diameter d were 8.73 cm3,1.43 mm,1.28%,0.90 mm,and 1.23 mm,respectively.According to the Chinese national standard of“fresh Apple”,the average error of the estimated result is within the range of allowable error.It indicates that the method of apple phenotypic parameter estimation based on 3D reconstruction has a high accuracy and practicability,and it can be used as the support for fruit sorting.

Measurement of the banana pseudo-stem phenotypic parameters based on ellipse model

The measurement of banana pseudo-stem phenotypic parameters is a critical way to evaluate the growth status of bananas,and it can provide essential data support for mechanized cultivation operations such as fertilization and pesticide application.Existing studies mainly measure the diameter of banana pseudo-stem as its phenotypic parameter.The banana pseudo-stem cross section was closer to an ellipse other than a standard circle,so the diameter parameter cannot adequately represent the phenotypic characteristics of the banana plant.In this study,an automatic measuring device for banana pseudo-stem phenotypic parameters was developed.The device,which integrates three different types of sensors:a laser ranging sensor,a rotary encoder,and a digital camera,were used to obtain the point cloud and image data of banana pseudo-stem.A K-means point clouds clustering algorithm based on Euclidean distance was proposed.The point cloud of banana pseudo-stem was identified and extracted.A three-dimensional reconstruction algorithm based on the ellipse model was also proposed.The three-dimensional contour of the pseudo-stem was calculated to obtain three types of phenotypic parameters:the long axis length,the short axis length,and the perimeter.Further,a synchronous trigger image acquisition mechanism was used to take pictures of pseudo-stems during measurement.It can be utilized for manual assessment of the growth status of the banana.Field experimental results showed that the three banana phenotypic parameters had a high correlation with the manual measurement results,and R^(2)is always more significant than 0.95,the total average measurement error and relative error were only 6.16 mm and 4.38%,respectively,both are within the acceptable agronomy range.In general,this method has good universality for plant stem detection,and the stem phenotypic parameters can be obtained by means of non-contact test,which is of great significance to the mechanized cultivation of the forest and fruit industry.