Also you may have to get a docx file fix tool in advance in case your files just get corrupted. Thus it’s of high importance to fortify those files by taking regular backups or running anti-virus program on devices. That means you have hundreds of thousands of chances to have your file damaged due to internal or external factors. There are probably hundreds of thousands of valuable files stored on your computer. You can press “Alt+ F9” to check the field codes. Now you will find the field is invisible.Next put cursor right before “.jpg” and click “Insert Merge Field” and then choose right field.The “ C:\\test\\” refers to the picture location. Between the field brackets, enter IncludePicture “C:\\test\\.jpg”. Then place cursor at the positon for picture.Repeat from step 2 to 7 in method 1 to finish inserting other fields.This time in Excel file, you should place picture name instead its location there.First, place all picture in one file folder and make sure they are of the same file format, such as the “.jpg” file.Method 2: Place Picture Name into Excel File Next, click “OK” in “Merge to New Document” dialog box.Then choose “Edit Individual Documents”.After this, click “Finish& Merge” under “mailings” tab.However, you can still resize the picture. Press “Alt+ F9” to toggle field codes and you still can’t see the picture now.Then click “Insert Merge Field” and choose the right field.Select the “pic” you just input and click “Mailings” tab.Click on the picture and press “Alt+ F9” to toggle to field codes. Then in “Field properties” text box, enter anything, such as “pic” here.In “Field” dialog box, choose “IncludePicture” for field name.Next click “Quick Parts” and choose “Field”.Now place cursor at the position where picture should go and click “Insert” tab.Then in “Select Table” dialog box, select the right worksheet and click “OK”.Next, click “OK” in “Confirm Data Source” dialog box.
Now in the “Select Data Source” window, select the file and click “Open”.Then click “Select Recipients” and choose “Use Existing List”.Then open Word and finish all other editing.And remember to replace the “\” in file path with “\\”, such as below: First and foremost, in your source Excel file, insert a new column to put the location of your pictures.Method 1: Place Picture Location into Excel File To solve this issue, the following 2 methods are exactly what you will need. However, we can’t possibly insert pictures into Excel file directly, thus while using mail merge in Word, it’s unlikely to get the corresponding images. When create credentials, we often need to insert pictures. In summary, this research demonstrated and evaluated an approach to combine UAV and satellite sensor images to diagnose wheat growth and N status across large areas.In this article, there are 2 effectual ways for you to batch insert multiple pictures into your Word document via mail merge. Thereby, the NNI was used to map winter wheat N nutrition status at the county scale. The results indicated that the model derived from the S2 imagery performed well for predicting NNI (R2 = 0.46–0.54) at the jointing and booting stages. Meanwhile, an indirect diagnosis method was used to calculate the NNI. Amongst the four methods tested, the random forest (RF) achieved the greatest prediction accuracy for PDM (R2 = 0.69–0.93) and PNA (R2 = 0.60–0.77). Then, satellite-based prediction models were constructed by fitting four machine learning algorithms to the relationships between satellite spectral indices, upscaled PDM (PNA) and weather data. The farm-scale PDM (UAV-PDM) and PNA (UAV-PNA) maps can be derived from the UAV images at the four farms, which were further upscaled to grids to match the S2 image resolution using pixel aggregation method. A fixed-wing UAV sensing system and the Sentinel 2 (S2) satellite were used to collect wheat canopy multispectral images three growth variables (plant dry matter (PDM), plant N accumulation (PNA) and N nutrition index (NNI)) and weather data, synchronized with spectral imagery, were obtained at the jointing and booting stages. Seven wheat field experiments involving multi cultivars and different N applications were conducted at four farms of Xinghua county from 2017 to 2021. This research aimed to calibrate satellite remote sensing-derived models for crop growth estimation and N status diagnosis based on fine-resolution unmanned aerial vehicle (UAV) images, thus, map wheat growth and N status at the county scale. For this purpose, satellite sensor imaging can act as an effective tool for collecting crop growth information across large areas, but they can be challenging to calibrate with ground reference data. Real-time and non-destructive nitrogen (N) status diagnosis is needed to support in-season N management decision-making for modern wheat production.
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