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2019 Interns

Week Six:

This week I got to help out with some soil sampling in corn fields. NMSP is working with farmers to do trials on N-rich strips, which are sections of a field that are given so much pre-plant nitrogen that sidedressing is unlikely to be necessary. These plots help farmers to estimate how much nitrogen they need in certain areas and guess whether or not larger applications of nitrogen would make sense economically across certain management zones.

Field technicians use soil probes to take core samples from two soil depths, 8″ and 12″. The 8″ samples are used for general soil fertility tests, while the 12″ samples are tested in-house for soil nitrate levels. Although the 12″ cores can be very difficult to take in rocky soils, it’s important for researchers to know how much nitrate is present throughout the entire rooting zone.

Bagged soil sample

NMSP uses a double bagging method to keep soil samples secured and organized. The outer bag contains a small ID tag with replication and treatment info, along with the inner bag which contains the actual sample.

Soil samples in a dryer

The bags are opened up back in the lab, where the soil samples and ID tags are placed into individual cups for further processing. Soil cups are then loaded into the 50 °C dryer in order to remove most soil moisture. Processing wet soils would be very messy and lead to less reliable data.

Edgewood Farms, LLC Internship

Hello, my name is Bryce Schuster and I am a soon to be senior, studying agricultural science.  This summer I am completing my internship at Edgewood Farms, LLC in Groveland, New York.  Edgewood Farms is primarily a crop farm, but also operates a small feedlot, and is an authorized reseller of drainage tile, bunk covers and bags, fencing supplies and agricultural GPS systems.  The main crops grown are corn and soybeans, however they also grow wheat, green beans, kidney beans, and black beans.  The mission at Edgewood Farms, LLC is to provide quality products and service to their customers, while maintaining the integrity of the land, animals and environmental resources.  My duties this summer consist mostly of crop scouting, tissue sampling, and field agronomic problem-solving.

This spring and the beginning of summer have made farming difficult to say the least here in Western New York.  It has rained constantly and been cooler than normal until a couple of weeks ago.  When I started the internship at the end of May, corn planting was just getting under way.  This meant all hands-on deck to get fields prepped and seed in the ground.  Without any crops for me to scout this meant I also got the opportunity to assist with field work in equipment that is much larger than I am used to on my farm.

My first week on the job consisted of learning the names and location of over 200 fields, making up almost 4,000 acres, spread over 3 townships; and running a Case IH 9180 with a chisel plow to fill in ruts made by the farms sprayer that was applying pre-emerge herbicide.  Edgewood Farms has made the transition to an almost entirely strip tillage or no-till cropping system so it is rare to see conventional tillage performed, such as chisel plowing.  However, when last fall and this spring saw excessive rainfall, it is inevitable that a 35,000 lbs. sprayer with narrow tires is going to sink into the ground more than is ideal.  I also got the chance to use their 40-foot-wide roller to roll fields that are planted to beans, making the ground as flat as possible to optimize yield by allowing the combine header to be run closer to the ground without risking damage by picking up a rock.

Soil erosion on a conventionally tilled corn field.

Now that crops are finally starting to germinate and emerge, I can begin my scouting.  When the crops were still in the VE stage my main focus was on taking stand counts and checking for insect damage.  With all the moisture, one problem associated with strip or no-till cropping systems became apparent.  While the residue on the ground from last years crop is good for soil moisture retention in dry periods and weed suppression, it also creates a great environment for slugs.  I never knew slugs could do so much damage to crops and unfortunately it is not an easy problem to control.  Slug bait is extremely expensive so purchasing enough to treat every field is not practical.  The best way to end the problem is for things to dry out a little bit.  I am looking forward to how the summer progresses and what knew things I can learn!

Slug damage.

Week Five:

This week was very exciting! I continued working with R and several yield cleaning projects, but also got to join Greg for a couple of rounds of field work. This meant getting to see two of NMSP’s drones complete NDVI scans of corn fields. NDVI scans are able to measure the vigor of plants in the field, either to estimate yield or to help farmers more accurately place sidedress fertilizer. The latter seems very interesting but also very challenging. NDVI works on a scale of 0 to 1, with 1 being very green and 0 being not green at all.

Quantix drone

Drones are the quickest way for farmers to accurately take NDVI readings over a full field.


The greener sections of the field are assumed to not be nitrogen deficient, and the less green sections are given extra nitrogen to address lower vigor. However, lower vigor could also be due to other factors like a wet spot in the field or a deficiency of nutrients other than nitrogen. As precision ag technology continues to evolve, it will be cool to see how companies and farmers address these issues. Looking for patterns in individual leaves is one solution, but it would require very high resolution cameras and advanced imagery technology. I will be excited to learn more about this quickly moving ag sector as the summer goes on!

Week Four:

With the improved weather over the weekend, we were able to get into the field and place some stakes for nitrogen fertilizer trials this week! I attached a picture of the stakes below. They will be used as a reference for field treatments along with GPS coordinates to be taken at a later date. To place stakes, Greg and I followed a map indicating where each plot was located in the field. Plots have randomized locations over several trials in order to avoid environmental impacts from certain field sections influencing the final results.

Fertilizer stake and label

Top: Plot or treatment number
Middle: Pre-plant nitrogen treatment in pounds per acre
Bottom: Sidedress nitrogen treatment in pounds per acre


The trial features rye terminated at several different stages along with different volumes of both pre-plant and sidedress nitrogen fertilizer. Cover crops like these are important because they can improve soil health and increase soil organic matter, both of which provide a ton of value to New York State farmers. It was really cool to see the corn poking out from under the rye stubble, especially considering the difficult planting and field work conditions that farmers have faced this year.

Week Three:

This week, several technicians from a NYS digital agriculture company came in for a yield cleaning training session. This was the first time that I have had a major role in a training session so I was a bit nervous. Using Yield Editor, I walked one technician through the initial settings selection process. There are 4 distinct settings used by Yield Editor to clean harvest maps. Flow delay (as pictured above) is caused by the gap in time between the actual harvest of the crop and the moment when the crop is massed by a sensor. Moisture delay is caused by a similar issue, and is especially important when cleaning silage data (as the moisture of silage is significantly higher and more variable than corn grain moisture). Start Pass Delay and End Pass Delay are both caused by the slowing down and speeding up of the harvester at the edge of the field, which often leads to unreliable yield data.

This is an image pulled from a PowerPoint presentation that I created to help farm consultants learn the data cleaning process. As more and more farms in New York State get yield monitors on their corn harvesters, it will become increasingly important for consultants to feel confident working with that data.

This is an image pulled from a PowerPoint presentation that I created to help farm consultants learn the data cleaning process. As more and more farms in New York State get yield monitors on their corn harvesters, it will become increasingly important for consultants to feel confident working with that data.


By using both the Automated Yield Cleaning Expert (a Yield Editor feature that estimates the proper delay settings) and a more guess-and-check method, yield cleaning technicians are able to determine the proper initial settings after manually examining only 10 fields from each farm annually. After finding the proper settings for the farm, technicians are able to use low-level programming to automatically clean the harvest data from the remaining fields. This saves farmers a lot of time working with data and still provides the high level of accuracy needed for yield estimation.

Week Two:

This week, I spent a couple of days working with Dilip to learn the process for creating farm reports from yield data sets. This is the way that NMSP shows farmers what the program does with donated harvest data and makes it easier to understand the impact of the data cleaning process. Using RStudio (pictured below) and the R programming language, I am now able to take cleaned yield data files from Yield Editor and quickly create graphs that illustrate which parts of the field contained the best data and which sections had to be removed (commonly called headlands). The reports also contain several interesting pieces of analysis. The average yield for each soil type in each field is listed on one page, with the average yield for each soil type across the whole farm listed later in the report. This information helps farmers to better understand why certain fields are high yielding and other fields continually underperform compared to the whole farm average.

Example of R code

This is an example of R code. I also went to a free R coding workshop put on by the Cornell Statistical Consulting Unit this week which was very helpful. There are a lot of good resources to start learning R, but practice is key!

So Much FRECin’ Fruit

Hey y’all, my name’s Bethany and I will be a junior this fall. I am from Biglerville, Pennsylvania and I have a background in fruit trees, but specifically apples. This summer I am an intern at FREC, Penn State Extension’s Fruit Research and Extension Center, conveniently located also in Biglerville, PA. At FREC, there are 5 lead scientists, each conducting research on horticulture, plant pathology, agricultural engineering, or entomology. I am working as an intern for Dr. Schupp, the horticulturalist there. He works specifically with apples, pears, and peaches, but mainly with apples because they are popular in the surrounding area. Within apples, I noticed that he has mainly been working with different types of thinning, pruning, and tree training to produce the most amount of apples. Additionally, he is also working on some interesting projects with the agricultural engineers for automated pruning and picking.

I spend most of my days outside, tending to the trees or modifying them to the produce the desired result. Recently, I have been thinning and pruning a lot of peach trees, thinning apple trees to define a strong terminal bud, and clipping up the recently planted Ever Crisp and Premiere Honey Crisp apples.


Pictured above is the NBlosi, a scissor lift with a shifting platform that allows us to easily reach into the trees. On the right are the Gala apple trees that we trained.

Further, I have also become fascinated by the different bugs around the orchard; I usually take a picture of them and show them to the entomology interns during lunch. I’ll post some of my favorites below:

Pictured above on the left is a leather wing, also known as a soldier beetle. In the middle is a common leaf beetle that caught be by surprise. On the right is a praying mantis nest that I found pruning.

Every year, Dr. Schupp hands his summer interns their own project to take charge of. This year, we get to run a project that deals with a new club variety of apple called Sweet Cheeks. However, it has many fruit finish issues. Our job is to determine whether the russetting is early or late onset and suggest ways to prevent it. I am excited to explain about it more in my next post!

Week One:

My first week was a bit of a rush! I started out using Yield Editor (a free software published by USDA-ARS) to clean corn data from a farm that works with NMSP on a couple of projects. Cleaning harvest data is important because it allows farmers to know exactly how much they are able to produce in certain fields. It is also important to have very accurate data for making decisions about which fertilizers to use and how much of each nutrient to apply in different sections of the farm.

Example of flow delay correction in Yield Editor

Left: Raw corn harvest data. Right: Data cleaned following the Kharel et al. protocol


Data technicians at NMSP follow the yield cleaning protocol written by Dr. Tulsi Kharel, one of my supervisors at the lab. The manual is very helpful because it’s easy to forget steps in the yield data cleaning process if you are just working from memory. Following the protocol also ensures that data sets cleaned by different technicians will still be consistent and highly accurate. Tulsi is leaving for a position with the USDA in Arkansas soon which will be sad but he has already taught me a lot about working with agronomic data. Dilip, the lead data analyst in the lab, has also been very generous with his time and has started to teach me how to use the programming language R. This will hopefully allow me to start creating farm reports based off of the cleaned yield data, which would be a new and exciting skill!

Applied Precision Ag – Data that Works for Farmers

Ben Lehman – CCE 2019 Precision Ag Intern

Hi, my name is Ben! I’m a rising junior in Agricultural Sciences at Cornell. This summer I ‘ll be keeping a blog of my experience interning with the Nutrient Management Spear Program (NMSP). Dr. Quirine Ketterings leads the lab and has already assigned a few cool new projects for me to work on this summer! A lot of my work will be processing corn harvest data, using AgLeader SMS for pre-processing, Yield Editor for correcting errors and delays in yield data, and RStudio to create reports and graphs for farmers. I’ll also be doing some field work and getting a better understanding of the lab’s mission as a whole.


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