The best plans never rely on the weather

many an outdoor event due to high winds, and we’ve certainly been chased in by sudden summer storms, but the idea that we might not be able to hold a concert because of a slow, steady evening-long rain in August?

Well, it only occurred to us as a thing to crack jokes about, as in, “At least we don’t have to worry about rain, hahahahahahaha …” nothing but more blue for miles in every direction. Flash floods were the last crisis I could possibly imagine.

Yes, August may bring an abundance of grasshoppers, flies or on a bad year garden-crushing hail, but never, ever the kind of rain shower that would require cancellation of an outdoor event.

We were planning to film the concert, and that meant we really needed good sound — even a tiny bit of wind can wreck a live recording. After the unusually temperate summer, it seemed we were overdue for the kind of extremes that usually characterize our weather patterns here.

At the last minute, we decided to move the concert from a relatively open area to our yard, where we’d have more staging options if we needed them.

Unexpected. And then sometime last week our cellphones started warning us of flash floods.

“It’s for tomorrow,” he said. “It’s supposed to start raining and not stop for a couple days.” Well. So much for ‘it never, ever rains in August in Western South Dakota.’

“Don’t worry,” my husband said, I’m sure noticing the fear that had sprung into my eyes. “It will stop way before the show.” ensure the show can go on regardless of changes in the forecast, but what about the audience? Navigating the sloppy, mud-fest of our yard after another day of ceaseless rain will be interesting. While the manure rivers that flow from the barnyard after an epic rain event are great for the grass, they might be less great for folks who don’t think to wear tall mud boots to a concert.

When The Kithship Collective, an arts organization I help run, started planning for a pasture concert on the ranch in early August, the last thing on our mind was coming up with an alternate location in case of rain.

I have, unfortunately, had to cancel

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The end of July brought a few days with temperatures in the triple digits, which is exactly what one would expect for our part of the prairie. Most of July had been unusually cool; however, and it’s been a surprisingly un-windy summer as well, so I was starting to get nervous. Surely, we couldn’t expect things to remain calm and pleasant.

“Flash floods?” I said to my husband, looking down at my phone, then staring up at the white, blazing sun. I’d just gotten done painting a wall in the outbuilding we’d decided to use as the makeshift stage for the concert, and my paint-splattered shirt was soaked with sweat. Above our heads, there wasn’t a single cloud in the bright blue sky, and there was

Fingers crossed. Tomorrow is the concert. By the time this goes to print, the show will be over, and it will hopefully have gone well. As I type this, a hard, steady rain is beating against the window over my desk. The forecast has remained steadfast in its conviction that the rains will indeed cease in plenty of time for us to set up the stage and equipment, and there isn’t predicted to be a breath of wind. Is it possible we will actually get that lucky?

Thankfully, the outbuilding will

Meanwhile, all this rain means the prairie will probably stay green until snow flies, and no one will be sad about that. I am, however, once again considering how hilarious it is that we humans ever attempt to make any plans at all.

(Eliza Blue is a shepherd, folk musician and writer residing in western South Dakota. In addition to writing her weekly column, “Little Pasture on the Prairie,” she writes and produces audio postcards from her ranch and just released her first book, “Accidental Rancher.” She also has a weekly show, “Live from the Home Farm,” that broadcasts on social media every Saturday night from her ranch.)

Precision tech allows early diagnosis of calf pneumonia

UNIVERSITY PARK, Pa. —

Monitoring dairy calves with precision technologies based on the “internet of things,” or IoT, leads to the earlier diagnosis of calf-killing bovine respiratory disease, according to a new study.

The novel approach — a result of crosscutting collaboration by a team of researchers from Penn State, the University of Kentucky and the University of Vermont — will offer dairy producers an opportunity to improve the economies of their farms, according to researchers.

Not the norm. This is not your grandfather’s dairy farming strategy, notes lead researcher Melissa Cantor, assistant professor of precision dairy science at Penn State’s College of Agricultural Sciences.

Cantor noted that new technology is becoming increasingly affordable, offering farmers opportunities to detect animal health problems soon enough to intervene, saving the calves and the investment they represent.

Data collectors. IoT refers to embedded devices equipped with sensors, processing and communication abilities, software, and other technologies to connect and exchange data with other devices over the internet.

In this study, Cantor explained, IoT technologies such as wearable sensors and automatic feeders were used to closely watch and analyze the condition of calves.

Such IoT devices generate a huge amount of data by closely monitoring the cows’ behavior.

To make such data easier to interpret, and provide clues to calf health problems, the researchers adopted machine learning — a branch of artificial intelligence that learns the hidden patterns in the data to discriminate between sick and healthy calves, given the input from the IoT devices.

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“We put leg bands on the calves, which record activity behavior data in dairy cattle, such as the number of steps and lying time,” Cantor said.

“And we used automatic feeders, which dispense milk and grain and record feeding behaviors, such as the number of visits and liters of consumed milk. Information from those sources signaled when a calf’s condition was on the verge of deteriorating,” she continued.

Bovine respiratory disease is an infection of the respiratory tract that is the leading reason for an- timicrobial use in dairy calves and represents 22% of calf mortalities. The costs and effects of the ailment can severely damage a farm’s economy since raising dairy calves is one of the largest economic investments.

Study results. In the study, data was collected from 159 dairy calves using precision livestock technologies and by researchers who performed daily physical health exams on the calves at the University of Kentucky.

Researchers recorded both automatic data-collection results and manual data-collection results and compared the two.

In findings recently published in IEEE Access, a peer-reviewed open-access scientific journal published by the Institute of Electrical and Electronics Engineers, the researchers reported that the proposed approach is able to identify calves that developed bovine respiratory disease sooner.

Numerically, the system achieved an accuracy of 88% for labeling sick and healthy calves. Seventy percent of sick calves were predicted four days prior to diagnosis, and 80% of calves that developed a chronic case of the disease were detected within the first five days of sickness.

“We were really surprised to find out that the relationship with the behavioral changes in those animals was very different than animals that got better with one treatment,” she said. “And nobody had ever looked at that before. We came up with the concept that if these animals actually behave differently, then there’s probably a chance that IoT technologies empowered with machine learning inference techniques could actually identify them sooner before anybody can with the naked eye. That offers producers options.”

Contributing to the research were Enrico Casella, Department of Animal and Dairy Science, University of Wisconsin-Madison; Melissa Cantor, Department of Animal Science, Penn State University; Megan Woodrum Setser, Department of Animal and Food Sciences, University of Kentucky; Simone Silvestri, Department of Computer Science, University of Kentucky; and Joao Costa, Department of Animal and Veterinary Sciences, University of Vermont.

This work was supported by the U.S. Department of Agriculture and the National Science Foundation.