Our Christmas Present this Year was more Cold and Wet

Christmas Morning Spray to Spinach-
the only forecasted dry morning to work!

It is now two days after Christmas and we are behind in many ways... plantings have been delayed by the regular rainfalls since Mid November.... about the time it gets close to being dry enough for real tractor work, we get another storm.

The crops we do have in the ground are SLOW!  At this point we are about 42 days behind our long term average for GDU's (Growing Degree Units) on the 50-86 scale... that is a bunch... most of them lost since mid September... our fall crops are way behind... so the double whammy... not getting much accomplished, and what we have gotten done is lamenting cold weather and not growing.  The bug pressure has been slow as well.  But we are anticipating lots of Mildew in the lettuce and spinach at this point.

In the summer, when we hit 115, we rationalize that it is a dry heat.... at the moment, we would love to be DRY, and everything around us would appreciate some HEAT... you never met a bigger bunch of whiners than desert people having to wait for things to dry out... A VP at one of the bigger lettuce companies I know was REALLY unhappy that one of their
growers missed 4 planting dates after Thanksgiving. Missing planting dates is a real sin in the produce game... Walmart et al want their 10,000 boxes a day whether you have weather problems or not... 

So here is hoping the New Year brings lots of GREAT weather, Productive Projects, and Fruitful Crops!  

Conference Report for American Seed Trade Corn Soy Sorghum Conference in Chicago Dec 10-12 2019

Back from our trip to ASTA in Chicago. Overall the conference was Solid!  Here are some of my takeaways and comments from some of the excellent presentations, conversations with others, and walking the trade exhibition:

·         The presentations on Wheat acreage reminded us that acreage is down to 46 million acres, a drop of 25% over the past few years, no end in sight.

o   I noticed in the list of attendees that several long-term folks I know in the wheat business were not there.

·         Rumors of perhaps 100 million acres of corn in 2020, perhaps 82 million acres of Soy... but who knows?

o   Lots of discussion on various breeding programs and the changes and cutbacks of various programs.

o   Consensus was that some powerhouses in breeding will fall behind due to lack of continued effort to stay ahead and that the rise of smaller, more niche / regional companies will become more important

·         The big boys in room are doing lots more investing and acquisitions of new technologies / fields of interest

o   Examples would be:

§  Monsanto buying much of Novozymes a few years back

§  BASF investing in Equinom for pulses

§  Corteva screening outside Biostimulants

o   This is a significant change from the “Not invented here” syndrome typical of the past and opens windows for more niche companies

·         Our Company (RD4AG) focus is small plot research and there were several reaffirmations and trends I noticed:

o   An excellent presentation by Alex Cochran with Corteva on challenges in field trials with Biologicals

o   His Key Points re-enforced what we believe

§  Field variability is the foundation of most evil in small plot work

§  Statistical design and trial layout are key

·         At RD4AG, we spend untold hours working on good layouts, spatial balance, proper block orientation for the suspected variability.  This has paid off big benefits in our programs, and there is more to do as we are always learning.

§  Objective assessments from remote sensing is where things have to go

·         I could not agree more!  We (RD4AG) are spending LOTS of effort here. 

o   In our work, Proximal sensing (a fancy way of saying we are close to the target with our cameras, heat sensors, etc by mounting them on a tractor or other field system) is more important that drones.  But the concept is the same 

·         Hard numbers from Objective Assessments are needed

·         Here is a list of what I see/or we are working on at RD4AG

o   Image analysis for canopy cover, color composition, etc,

o   NDVI, CWSI, NDWI and the whole alphabet soup of various spectral evaluations

o   Instrumental determined heights and biomass from LIDAR, Sonar, or multiple image analysis

o   High speed Canopy temperatures accurate to less than one tenth of a percent error form IR Radiometers, etc for moisture stress

o   The list goes on and on

·         Dr. Cochran showed some compelling data showing that trained visual observers are not nearly as accurate as remote sensing, which is no surprise.

o   But we still have to ground truth and get in the field to assure things make sense.(Pun intended)

o   Many new advances in Research Equipment to be seen

§  Smart Planters are on the way

·         Variable spacing,

·         Variable in furrow applications

·         Actual seed treating as it falls through the planter

§  Combines are getting more technical in the efficiency and data they will collect

§  Software will be able to handle the Geo tagged Objective assessments noted above and assist in the analysis of plots much more efficiently than current methods

§  Drone software and capabilities are racing ahead

o   When it comes to Research, we have to stay on track to be able to provide the best tool for the task--there are many tools, but not every task is for every tool, nor is every tool for all tasks!

These are exciting times!  What we do now, and how we do it in field research is MUCH different than 10 years ago, and I cannot really imagine what we will be doing 10 years from now!

Using NDVI for BioStimulant Assessment

By Fabian Sanchez

RD4AG is working to expand knowledge on the modes of action and effectiveness of biostimulants in agricultural crops. One of the tools we rely on is the Normalized Differential Vegetative Index (NDVI) to assess live green vegetation in our BioStimulant product performance trials.

With the advent of numerous innovations, there is more opportunity than ever to improve our ability to evaluate the health and well-being of plants in the field. Achieving accurate and useful field assessment data can be challenging and costly and the data is often fraught with background noise from human error and subjective variabilities.  NDVI measurements can help us monitor research plots more efficiently. These measurements can also lead to a larger analysis of vegetative properties to assess BioStimulant impact including; leaf area index, chlorophyll concentration, plant productivity, vigor, fractional vegetation cover, accumulated rainfall, basic nutrient response, crop condition (identify diseases), yield potential, stress, biomass, herbicide efficiency and the list could go on.

            NDVI uses the photosynthetically active radiation spectral region of plants in the near-infrared and red (visible) spectral region. The chlorophyll reflectance value needs to be determined in order to understand the NDVI readings which are based on the reflectance values from the plants using the two different wavelengths. Chlorophyll is known to strongly absorb visible light from 400nm to 700nm for use in photosynthesis therefore, NDVI functionally obtains the equivalence of simple infrared/red ratio as shown on the figure below.

NDVI is directly related to the photosynthetic capacity and thus energy absorption of plant canopies. Our instrumentation is the Greenseeker handheld crop sensor by Trimble (Fig. 2.) and its sensor displays the measured value in terms of an NDVI reading (ranging from 0.00 to 0.99) on its LCD display screen as described in their website. Therefore, the greener plant material there is the higher the NDVI reading is which complies with the principle of having low red-light absorbed by the chlorophyll in the plant and high near-infrared light reflectance.

The Greenseeker is an active light source optical sensor which means it provides its own light so that the time of the day will not be a factor affecting the measurement. There are some environmental variables that can have an impact on data quality.  If wind is blowing plants sufficiently to change which side of the leaves the sensor is reading, there can be substantial differences, especially in crops that may have small hairs or different textures on the undersides of foliage. Naturally, the sensor does not differentiate between weed and crop species so care must be taken when weeds are present to assure accurate data. 

Operational use after calibration and charging consists of holding the device with the sensor directed at the foliage, pressing the trigger button, and walking at a steady pace through the target plot areas maintaining a specific height range of 24” to 48” (60-120 cm) above the crop canopy (depending on the size and type of the crop).

 Above illustrates the sensor’s oval field of view showing how the size is proportional to height and approximates 10” (25cm) wide at 24” (60cm) above the ground and 20” (50cm) wide at 48” (120cm) above the ground, Trimble. An error message will be displayed on the screen if you are too high or too close to the crop.

The sensors on the instrumentation are emitting brief bursts of red and infrared light and automatically measuring each type of light that is reflected from the plant to obtain the NDVI reading. The device will display an NDVI value once per second during operation and reaches a maximum interval of 60 seconds, therefore, we want to record at least 10 seconds for each plot to collect a representative data set. After walking the desired area, release the button and the sensor will display the final average value of all the readings that were taken.

In order to establish favorable results, consistency in the plant population and agronomics are key components to success.  It is important that only the same crop and relative growth stage be compared.  In other words, taking a reading of one plot at 6 leaf and another at 30 leaf is not an accurate comparison.  Intuitively, comparing a wheat reading with a spinach reading does not provide useful information. The algorithms in these instruments require at least 50% of the field of view of the sensor to be covered by vegetation for accurate measure of “Greenness” that equates to productivity.  Bare ground typically reads 0.13, so less than 50% plant coverage of the soil in our experience is most useful in evaluating weed control if weeds are dying or breaking through the program.  If we want % ground cover with plants, we are now using imagery and color thresholding as discussed in RD4AG’s white paper on Canopy Coverage by Connor Osgood.  For plant productivity evaluations of crops, we tend to wait for the crop to grow a bit larger before we start the NDVI assessments in our trials.  Since NDVI also depends on the geometry of illumination and anisotropy of the target we continue to evaluate crops using the same standard procedure and hence maintain the position of the target of interest within the swath of the instrument at a specific range so we have consistency that can be relied upon to tease out subtle differences in crop performance.