Analyzing Soy meal in transmittance (part 9)

In the case of the Soy meal, we have a validation sample set (from an Infratec Nova), and we get the predictions from a calibration sample set from an Infratec  1241. As we saw in "Analyzing Soy meal in transmittance (part 8)" , the predictions are fine, but we have a bias and the idea was to merge the samples from the Infratec Nova with the samples from the Infratec 1241 and to develop a calibration.

But before that we want to see another option, and for that we are going to use an option from Win ISI: "Select local samples from a product file".

With this option we project the validation samples in the PC space we got from the calibration samples, and we search for neighbors into a certain cutoff.

Those samples will be take them apart into a file, to develop an exclusive calibration for the validation samples.

In this case I am going to use a cutoff of 0,2 (Mahalanobis distance).

From the 657 samples, 527 were selected  and exported to R to develop the calibration. There are some clear outliers, but there is a high improve in the statistics.

Now we remove the samples with number in red, because they are out of the action limits and recalculate.

>soy_ift_prot_sel1_r1<-soy_ift_prot_sel1[-c(495,102,83,270,74),]

>Prot_plsr_sel_r1<-plsr(soy_ift_prot_sel1$Prot~soy_ift_prot_sel1   $Xsel_msc,ncomp=16,data=soy_ift_prot_sel1,validation = "LOO")

>predictions_sel_r1<-(Prot_plsr_sel_r1$fitted.values[,,9])
>soy_ift_prot_sel2_r1<-cbind(soy_ift_prot_sel1_r1$Sample,soy_ift_prot_sel1_r1$Prot,predictions_sel_r1)

>monitor_prot_sel<-monitor10c24xyplot(soy_ift_prot_sel2_r1)

 As you can see there is an improvement in the calibration statistics with this selection, but is it an improvement in the validation. We will see it in the next post.