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And How…

And How…
January 18th, 2019

In the middle of frigid January, I would say I am coming around to this idea of working inside at the desk and not out in the barn or the field! This week I have been learning and doing more cleaning of yield data.

Using a USB drive, the data can be taken straight from the combine or chopper cab monitor and read into the SMS Software. On SMS the yield data is sorted using geospatial data from GPS locating into the farmer’s set field boundaries, also made using GPS systems. Information about the crop, growers, fertilizers, field history, and almost any other field attributes can be added too.  Once the data is in manageable field-sized packages from fiddling around with it on SMS, the data can be sent into Yield Editor to be ‘cleaned’.  Yield Editor is where, by tinkering with and adjusting the settings of the machinery sensors, you can manually compensate for the error variables I mentioned last week (variable speeds, stops, wet/dry, flow delay, operators who get funky with it, etc.).

On Yield Editor, data fed in from SMS are laid out chromatically and sometimes vaguely discernible patterns of high vs. low values show up within the rainbows of color. Then, constants for the variables can be set so the patterns line up into more easily distinguishable features that can actually be attributed to something such as slope of the field, a wet/dry spot, a tile line, a common traffic path, etc.. The picture to the left shows some of the variables for which constants and limits can be added to manipulate the data. Below, an example from the NMSP Protocol “Processing/Cleaning Corn Silage and Grain Yield Monitor Data for Standardized Yield Maps across Farms, Fields, and Years”* shows the change in the data points when a flow delay is accounted for. A pattern of a low yielding zone becomes more linear, and perhaps lines up with a wet spot, different soil type, or tile line on the field.

This cleaned data from Yield Editor can then be read back into SMS, which can be used as an extremely beneficial tool for crop planning and management by the farmer. With cleaned data to work with, management practices can be even more targeted and precise.

This type of diagnostic can prove useful to a farm. If a low yielding zone, upon further investigation, is found to have a drainage or erosion issue, measures can be taken to fix the problem. Furthermore, if there is an issue like a soil type that perhaps needs to be fertilized/treated differently, it is easier for the farmer to make zone prescribed planting or fertilizer prescriptions to optimize production in each zone. Along the same lines, if the farmer sees that sections of his field year after year are extremely high yielding, they may change their population density to better utilize the area or reduce their fertilizer expenditure on that zone save money and be economical. By cleaning the data, it allows for accurate measurements and clearer boundaries that can lead to clearer management zones for the farmers to work with. I hope to explore this kind of management on the farm at Osterhoudt Farms this summer. The NMSP Lab has given me so much information to work with and explore on the farm!

*Official Reference:
Kharel, T., S.N. Swink, C. Youngerman, A. Maresma, K.J. Czymmek, Q.M. Ketterings, P. Kyveryga, J. Lory, T.A. Musket, and V. Hubbard (2018). Processing/Cleaning Corn Silage and Grain Yield Monitor Data for Standardized Yield Maps across Farms, Fields, and Years. Cornell University, Nutrient Management Spear Program, Department of Animal Science, Ithaca NY.

 

Getting Started With Some Data Crunching

Getting Started With Some Data Crunching
January 10th, 2019

Hi everyone! The first increment of my agricultural internship is off to a running start in the NMSP where I am learning more than I had ever imagined I would about data processing. Right off the bat, I would be the first person to shy away from A: simply sitting at a desk all day and B: the idea of crunching numbers through a computer. However, in this case, what the numbers have the potential to tell you is so incredibly interesting (but maybe that’s my personal bias towards any and all things agriculturally related talking)!

So, to break it down, many farms are equipped with harvesting machinery that has a wide variety of sensors to help keep track of and measure yield. GPS guidance and positioning, speedometers, crop moisture sensors, width of the section being harvested, flow or the thickness/amount of the crop being pushed through the feed rolls, and many other bells and whistles that give off readings.

Many variables go into just simply measuring yield. Take this idea for instance: a bushel of corn has been standardized to a weight of 56lbs, however as a unit of measurement a bushel is actually a volume of something in its dry capacity (8 gallons of that ‘something’ in imperial units). But corn can be dried to different moisture contents, and some corn kernels can be on average denser than others even at the same moisture capacity! Now, add in a giant machine rolling through a field of corn, speeding up and slowing down, flow delay (A.K.A. the time it takes for the crop to be cut and pass through the chopper/combine head to get the sensor and be measured, but now the chopper is 20 feet further down the pass!) missing the perfect swath, a wet vs dry spot, or any other number of crazy things the machine operators do, and you have a huge number of variables that can affect how much crop is actually coming off the ground as opposed to what yield the sensor is reading off the field in a given spot. Now you have a mess of numbers that are all jumbled around when all the poor farmer wants to know is a round-a-bout idea of how his land is producing, and maybe which spots on the fields are the good spots or the bad spots.

Using two kinds of software, the NMSP has been working on fine-tuning a way of “cleaning” all this data that is recorded by the machine sensors and turning the numbers into a usable data set that farmers can work with.

USDA ARS – Yield Editor

SMS by AgLeader

 

 

 

 

 

 

 

…And the ins-and-outs of those whole concepts was about as much as I could learn in one week! You’ve got the “why,” coming soon—the “how” data is moved around and cleaned.

Some Interesting Connections!

Some Interesting Connections!
December 27th, 2018

Hi everybody my name is Hannah! I am a sophomore, soon-to-be Junior (by the time I finish this blog), in the Agricultural Sciences Program at Cornell. My agricultural internship experience is a little unique as it has been split up between the winter of 2018-19 and the summer of 2019. Over the winter intercession, I will spend around three weeks in Dr. Quirine Ketterings’s lab in the Nutrient Management Spear Program (NMSP) learning about digital agriculture—specifically crop yield data information and data cleaning. This summer, I will be working at Osterhoudt Farms in my lovely hometown of Genoa, New York.

I am very excited to be spending the summer in my happy hometown!

Osterhoudt Farms is a custom planting/harvest operation of alfalfa and corn. These products are mainly sold to dairy farms in the area. Osterhoudt Farms has around 2,000 acres of privately-owned ground in production, and custom plants and harvests an additional approximate 4,000 acres of corn and 2,000 acres of alfalfa/grass hay for a grand total of worked ground falling around 10,000 acres spread throughout the entire county!

Working closely with Osterhoudt Farm’s on-staff crop consultant, Andy Miller, I hope to learn some of Andy’s roles and responsibilities in advising and helping manage a large farming operation, and will also be connecting the winter portion of my internship by observing some practical on-farm uses for digital agriculture and yield data information. We also hope to be doing some rather large-scale field trials to test some crop and nutrient variables, but more to come on that topic this summer! Hopefully, the unique in-lab to on-farm leap can provide some useful information to the farm as well as some feedback for the NMSP. 

Osterhoudt Custom Harvesting’s employee and fan favorite picture (from the 2014 Silage harvest)

Deer Fence

Only a little muddy in the field!

As the weather starts to change, and my internship draws closer to an end the lab is still keeping me on my toes with new and exciting tasks. After helping plant the plots, I was given the liberty to plan and construct a fence around our Legume Cover Crop Breeding experiments. Whitetail deer can be a big nuisance in Tompkins county and can commonly eat data! To prevent this we installed over 4000ft of double stranded fence

 

Finishing Planting!

 

First off, I did some research on what would be sufficient and went to Agway in downtown Ithaca and purchased all the materials necessary.  We used over 75 metal T-post stakes and bought a lot of poly tape fencing strand. The field was too wet to drive all the way to the plot so it took us a while to carry all the materials there.

Pounding Away!

 

 

I then used a stake pounder to put fencing posts every 25 to 30ft. I came to the quick realization that pounding stakes is much more challenging in rocky , however we ended up finishing the first fence in under 3hrs!

 

The following day we did the same process around the second plot and set up the fence chargers. Using a voltmeter we checked the charge and both were zapping with over 950 volts! It was a job well done, and now our precious hairy vetch and pea seedlings will be saved from the deer!

 

Kernza!

Above and belowground biomass of annual wheat(left) vs. Kernza(right) over a season. Image Credit: Lee DeHaan

One of my favorite projects from the summer that we are currently wrapping up harvesting, is intermediate wheatgrass (Thinopyrum intermedium) which goes by the tradename Kernza. Kernza is a perennial grain developed by breeders at the Land Institute. Kernza mimics a natural perennial system which does not require planting annually. Kernza also has the potential to be a dual purpose crop used for both grain and forage. It is very exciting to work with an idea as novel as this and I cannot wait to see where Kernza goes in the future.

There were a few primary experiments that I worked on during my time with the lab. Primarily, I assisted with assessing productivity in intermedium wheatgrass. Before I joined the lab, multiple timing and frequency of forage and grain harvest as well as N application rates were applied and monitored. I assisted with the measuring of total plot forage biomass removed through completing crop biomass cuts, weighing wet and dry samples to determine forage moisture, grinding the material so it can be sent to another lab for forage quality testing, and separating, counting and weighing seed heads to determine grain yield.

The other study I assisted with was exploring the potential of companion-planting red clover with intermediate wheatgrass. We wanted to know if a nitrogen-fixing crop such as red clover could supply sufficient nitrogen for Kernza, potentially abolishing the need for synthetic nitrogen fertilizers. In addition, I helped hand weed plots to determine the yield potential of Kernza in the absence of weeds.

Some perennial grains fields I helped manage and harvest were planted by local farmers to test growing on sloped and erodible land. Meeting the farmers over the course of the summer was very enjoyable because they all had great stories

Observed Difference in color between Kernza Clover Intercropping (Left) and Kernza Monoculture (right)

Developing Kernza Seed head

Vantage

CFX-750 with FieldIQ for controlling a sprayer.

After a very busy summer my internship has came to an end. I am very grateful for the opportunity I had over the past few months working at Vantage Northeast. This internship was a great learning experience getting a chance to work with many different aspects of precision agriculture as well as meeting a ton of new people along the way.

Quadrats, Quadrats and more Quadrats

Before Sampling “Haircut”

I made a lot of new friends this summer, but the one I got closest with was my quadrat. Since they were used so commonly in the lab I decided to focus this week’s blog on them.  A quadrat is a metal, rectangular frame used to assess a small area of habitat selected at random to quantify values such as the distribution of plants, weed pressure, yield or biomass. Our quadrats ranged from a size of .25 to .5 square meters. In most sampling events, forage or crop cuts were taken with the assistance of a quadrat for accurate results that can then be applied to a larger scale.

Using various random placement techniques, the quadrats were laid across a certain number of rows or in the vegetation perpendicular to a cardinal direction. Samples were then clipped at various heights depending on the experiment. The crop, or crops of interest were next placed in one bag and the weedy species would be identified and bagged separately. Identifying the weed species was my favorite part because it was both exciting to learn and memorize new species and in a way very relaxing when considered work. In some scenarios, we would also separate seed heads from stalks.

After Quadrat sample… “Bagged and Tagged”

Although it does not sound very exciting, I actually really enjoyed this lab task. It was gratifying to give the plots a haircut while sitting in the sun, listening to music, learning a lot and grilling my coworkers with conversation and questions.

Two Mountain Winery

My last two weeks in Washington were spent working at various vineyards that are managed by Two Mountain Winery in Zillah. The vineyards at Two Mountain and those that they manage are very unique because the majority of their vines do not need to be planted on grafted rootstock. The majority of the world’s Vitis vinifera varieties are planted on grafted rootstock that is more resistant to a root pest called phylloxera. Phylloxera can be very damaging to a vineyard especially when planted on original rootstock. However, this one particular area in Washington is one of the only places that is void of phylloxera, therefore allowing original rootstock to be planted.

Horizon at Two Mountain Vineyards

My purpose for working at Two Mountain was to utilize my IPM expertise and develop an IPM plan that they can use in future years so that they don’t have to hire someone to scout for them. I was able to put together a plan that focused on the most important pests and diseases found in this region’s vineyards, which included two-spotted spider mites, mealybugs, powdery mildew, red blotch, leaf roll, and botrytis. I developed scouting densities based on the sizing of each block and varied the number of leaves sampled depending on the layout of the block.

 

Leaf with Red Blotch Identified by Red Veins

                        Mealybug 

Along with the development of an IPM Guide, I took cluster counts to determine which blocks needed fruit cluster thinning. I also scouted one ten acre block, row by row, tagging all vines that had red blotch symptoms, so that they could be removed in the fall and replanted in the spring. Lastly, I learned to operate a forklift and helped sort harvest bins for each of the wineries to come and collect before harvest.

I truly am grateful for having this experience at Two Mountain and for spending the summer working with the hops at Perrault Farms. I discovered that I liked working in the hops a lot more than I anticipated to and that I really enjoyed scouting for pests and learning about the different pests and diseases. This summer is definitely one that is going to help shape my future career.

Geneva Apple Collection

One of my favorite parts of this internship has been going to the National Apple Collection at Cornell AgriTech (formerly the Agricultural Experiment Station) in Geneva, NY. Cornell Orchards do have a variety of apples with their own interesting characteristics (like the Golden Russet’s flesh and Honey-crisp’s coloring when nutrient deficiency arises) however, these trees have been selected due to beneficial characteristics to dessert, cooking, and cider apples. Some apple varieties are not as economically important, but could have unknown traits or simply have morphological features that make them interesting to look at. My internship at Cornell Orchards gave me the opportunity to view apple varieties that might not make the cut to many orchard sites, and test unknown varieties that may work well for hard cider production.  Before this internship, when I pictured an apple tree, I pictured a common gala  or red delicious apple tree, but now I think of apples as a variety of colors, shapes, sizes, heights, tastes, and more. I had no idea the AgriTech collection was so close to Cornell, but it is very interesting to see each variety progress and ripen.

Here’s a peek at just a few different traits I saw when I was searching for the latest and greatest hard cider varieties.

 

This apple variety dropped all its fruit before July 26. This is much earlier than when growers often desire fruit to ripen. The optimal season is around September-October.

 

 

 

 

 

 

 

This variety has serious sunburning. This variety would not be suited for dessert purposes, as consumers would likely not tolerate this flaw.

 

 

 

 

 

 

This variety had cherry sized fruit. This variety would be difficult to juice and probably not desirable to eat due to volatile levels.

 

 

 

 

 

 

 

This apple has water core. Some varieties develop water core due to environmental conditions. Water core can be seen as a disorder or a benefit–if stored or used as dessert apples, water core can develop an off aroma and might look undesirable to consumers. However, in cider apples, it could be beneficial as it increases sorbitol content, increasing the taste of sweetness.  In certain parts of the world, this trait is considered a delicacy, but many consumers in the US would shy away from apples with water core due to lack of familiarity.

 

 

 

 

 

These are some of the apples we brought back to test starch content, firmness of the flesh, and to juice to create cider. Each is unique and could bring different characteristics to our cider tests!

The 2018 NEWSS Weeds Contest

Cornell 2018 Weeds Team

Recently this summer, 11 other Cornell students and I traveled to Smithfield North Carolina to compete in the 2018 North Eastern Weed Science Society annual weeds competition. The contest was hosted by BASF Corporation who is the second largest producer and marketer of agricultural chemicals and related products in North America. It was very exciting to meet people involved in the industry as well as professors and students from other agricultural universities. There were just under 100 students from Guelph, Clemson, NC State, Penn State, The Ohio State University, Virginia Tech and Rutgers at both the undergrad and graduate levels.

Thinking Very Hard on a Practice Sprayer Calibration

The contest consisted of 4 main components, the first being Weed Identification. Of the 105 weeds we had to memorize, there were 25 in total to ID. There were both mature plants and juvenile weeds consisting of only cotyledons, as well as 5 different weed seeds. Next we moved on to Herbicide Identification which consisted of 10 plots that had been sprayed with 1 of 25 herbicides two weeks prior to the event. Using the symptomologies present, we had to identify the Herbicide as well as the family, WSSA group number, mode of action and site of action. This was the most challenging part of the competition, but in the end I managed to score decently well. Next we took a written examination on sprayer calibrations and conversion as well as performed a random practice calibration with a backpack sprayer as a team. Finally, we had two “farmer problems.” This was my favorite part of the competition. We were presented with a common problem and had to identify it as well as provide solutions for the present and future. We acted as the consultant in each situation, however it was a little stressful because some farmers were acting mad and the questions were very inquisitive. I enjoyed it so much because I thought it was a great representation of common problems faced in the industry, which I have never had the chance to experienced firsthand. BASF then provided us with a great dinner at a local winery where we got to talk with people of the industry and awards were given.

Overall the competition was very exciting and I gained a lot of knowledge I can now apply during my fieldwork at The Sustainable Cropping Systems Lab. For not having a weed science concentration or major like many of the other schools, Cornell placed very well! Our coaches Toni Ditimasso and Eugene Law helped out a lot in the learning process. I highly recommend that anyone staying in Ithaca next year checks out the team!

Maria talking to Colonel Corn

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