Fruit, nut, ornamental nursery, horticultural and greenhouse industries are among the fastest-growing enterprises in US agriculture. Application of pesticides and other production strategies have ensured their high-quality products meet stringent market requirements. However, low-efficiency, decades-old spray technologies are commonly used to treat these specialty crops and have caused an enormous amount of pesticide waste, additional costs in crop production and concerns around worker safety. The pesticide waste has also caused environmental contamination and ecosystem damage because pesticide sprays indiscriminately kill both pests and beneficial insects. Spray drift and off-target loss will likely remain a major problem as long as pesticides are applied using indiscriminate spray equipment.

Need for Efficient Technologies

Pesticide application is the most complicated operation in crop production because there are many variables affecting spray strategies and practices. In many cases, when decisions must be made to apply chemicals within a very narrow time window in response to escalating pest pressure, a simple “best guess” practice is often under vague labeling of pesticide rates to control pests that may result in excessive application of pesticides.

Given constrained environments for specialty crop production, an ideal spray management program for pests and diseases should include improved delivery systems that are flexible for spraying the amount of chemicals to match tree structures instead of acreage base. Such spray application will also produce minimum spray drift and off-target loss of pesticide on the ground and in the air.

To achieve this goal, a new automated universal intelligent spray control system was developed as a retrofit kit to attach on existing sprayers. With the intelligent control system, the conventional spraying systems can determine the presence, size, shape, and foliage density of target plants such as trees and grape vines, and then automatically apply the amount of pesticides as needed according to plant architectures in real time. With the control system, growers themselves can upgrade their own sprayers to precision sprayers with intelligent functions rather than buying new sprayers, and sprayer manufacturers do not need to change their current sprayer designs. The primary requirement for the upgrade action is to connect a variable-flowrate solenoid valve to each nozzle, and all other components are attached to the sprayer body without changing the sprayer structure.

This new system is the product of a decade of research and development by engineers at USDA-ARS at Wooster, Ohio in collaboration with researchers at The Ohio State University, Oregon State University, University of Tennessee, Clemson University, Texas A&M University, Iowa State University, Washington State University, Penn State University, University of Queensland and USDA-ARS.

Since 2013, the system has been tested as a retrofit on different types of the air-blast sprayers for pest control effectiveness, reliability and repeatability on real farm fields. Comparative field biological tests were also conducted to evaluate insect and disease control for the sprayers with and without the intelligent-decision control capabilities in commercial nurseries, apple orchards, peach orchards, pecan orchards, vineyards and small fruit productions as well as university research farms in Ohio, Oregon, Tennessee, South Carolina, Texas, California and Washington.

These activities were voluntarily held by UCCE in Napa County and University of Queensland in Australia.

System Features

Spray deposition uniformity insidecanopies, chemical usage and off-target losses were investigated for the plants at different growth stages in ornamental nurseries, apple orchards, peach orchards and vineyards. Multi-year field tests have demonstrated the intelligent spray system is reliable and can reduce pesticide use in a range between 30% and 90%, reduce airborne spray drift between 60% and 90%, and reduce spray loss to the ground between 40% and 80%, resulting in chemical savings in a range of $56 to $812 per acre annually. At the same time, the insect and disease control efficiencies are comparable or even better than standard sprayer practices. Because it uses less spray volume, it can spray more acres with the same amount of tank mixtures, thus reducing tank refilling times and reducing labor and fuel costs.

As a result, Smart Guided Systems, LLC commercialized the intelligent spray system, and a commercial version of the product has been developed with joint efforts between USDA-ARS and Smart Guided Systems, LLC. The new control system (See Figure 1) includes a new laser sensor, an Android Samsung tablet, a GPS navigator, an automatic flow rate controller, air filtration unit, a toggle switch box and a universal mounting kit.

The laser sensor is mounted between the tractor and the sprayer to “see” plants on both sides of the sprayer. It releases 54,000 detection signals per second with a 270-degree and 164-ft radial detection range. The laser signals bounced back from the plant canopies is used to determine the presence of a plant canopy and measure the canopy height, width, foliage density and canopy foliage volume (Figure 2). The GPS navigation device (or the radar speed sensor mounted at the bottom of the sprayer) measures sprayer travel speeds and location of each plant in the field. Based on the plant canopy foliage volume and the sprayer ground speed, the amount of spray for each nozzle is determined and then discharged to different parts of each plant in real time. Each nozzle is connected to a 10 Hz pulse width modulation (PWM) solenoid valve, and the nozzle flow rates are controlled by manipulating the duty cycle of the PWM waveforms with the flow controller. The flow controller consists of microprocessors to generate flow rate commands for each nozzle to discharge variable spray rates. Field data collected and processed with the intelligent spray system are synchronized through the tablet WiFi to the cloud.

The Android tablet provides the information for operators to communicate with the spray control system. The screen displays the sprayer travel speed, total discharged spray volume, spray width, and active nozzles. The operator can use the touch screen to modify the spray parameters as needed. The tablet allows the operator to activate the sprayer output on one or both sides in manual or automatic mode. All the electronic devices are powered by a 12V DC tractor battery. Another precaution includes the air filtration unit to discharge filtered air to prevent the laser sensor surface from getting dust and droplets. The toggle switches on the switch box are used to turn on/off main power, turn on/off the air filtration unit manually and override the automatic controller to activate nozzles as needed. Because sprayer travel speeds are automatically measured and included in the spray output control, applicators do not need to specify how fast they drive the tractor. However, travel speeds are not suggested to be higher than 5 MPH for orchard spray applications.

Features in the commercial system also include tree counting, tree size, foliage density heat map comparison capability, liquid volume sprayed per plant, maps of sprayed plant locations, ability to turn nozzles on/off independently through the tablet screen, cloud sync feature, web portal for configuration settings and spray coverage report view, system log files, five different languages (English, Spanish, French, German and Italian), and options for choosing metric or imperial units. The commercial products have been used by growers in the US and other countries with crops including citrus, nursery, pecan, blueberry, peach, almond, apple and pear with pesticide usage reductions in the range between 30% to 85% depending on crop types and growth stages. John Deere also established an agreement with Smart Guided Systems to sell the commercial intelligent spray control system for use in high-value crop applications through their dealer network.

The intelligent spray control system advances conventional standard pesticide application systems with the flexibility to spray specific positions on the plants. It reduces human involvement in decisions on how much spray volume is needed because the spray volume applied in the field is automatically controlled by the plant foliage volume instead of the antiquated gallons per acre.

The conventional air-blast spray system has been used from generation to generation for almost 80 years because of its robustness. Growers have accumulated extensive experience on using it to control pests in accommodation with their own crops. After being retrofitted with the intelligent spray control system, the conventional sprayers are able to turn on and off each nozzle and will stop spraying non-target areas such as gaps between trees, on the ground and above trees while their capabilities of spray penetration, spray range and spray deposition quality on plants remain the same. This new generation of spray technology is anticipated to be a primary precision spray technology for future decades to save chemicals for growers and provide a sustainable and environmentally responsible approach to protecting crops.

I never really understood what certification means until I heard it described by a psychometrician. I have been a Certified Crop Advisor (CCA) for nearly two decades and felt I knew what it means to be a certified professional. I recently attended the North American Certified Crop Advisors On-line Board Meeting. I listened to a presentation by Scott Thayn, Ph.D., CMS, a psychometrician, or a statistician specializing in distinguishing the differences between individuals. Thayn is the president of Certification Management Services, the third-party agency hired by the Agronomy Society to help develop and manage the testing required for certification. The presentation addressed a proposal to give rankings on how well a test taker did on the CCA exam. Board members were hearing from potential members who were unable to pass the exams and wanted more feedback to help them study for their next attempt. The proposal, and the way the statistician took it apart, were a revelation, and it got me thinking that the mechanics behind certification are not well understood.

Certification Exam Intricacies

The Home page for Certifications under the website Agronomy.org states, “Certification is the standard by which professionals are judged. The purpose of a certification program is to protect the public and the profession. It is a voluntary enhancement to a person’s career credentials. Being certified adds credibility and shows that you are serious about what you do.”

A prospective candidate digging deeper would find they need to meet certain criteria to be considered a CCA: academic, experience and examination. Simply speaking, certification indicates one has demonstrated the knowledge and experience to perform at a higher level than their peers.

Hearing the proposal to give test takers feedback on their performance was familiar to me as a board member who participates on the Exam Committee for the Western Region. I have heard from many colleagues who did not pass one or both certification exams and are frustrated by the lack of a score or indication where they underperformed. I struggled to explain to my friends why the exams were pass/fail and why they just had to keep trying. I believe the frustration lies in the expectations of an academic testing experience clashing with the reality of certification exams.

Data indicates most people who take the certification exams are recent college graduates. Having a college degree in agriculture is a requirement for becoming a certified crop advisor. College graduates have spent most of their lives with graded exams. Academic testing presents a broad range of questions to both examine a student’s proficiency and encourage them to improve. A student who gets a low grade on a test will hopefully review the questions marked incorrect and study the subject to raise their grade on the final exam. This familiar approach to testing is contrary to certification exams.

The distribution of difficulty of certification exam questions is quite narrow compared to an academic exam (See Figure 1). The certification exam begins by defining competency areas, the major subjects that define the everyday work of the crop advisor. Performance objectives rest under the competency areas. Each performance objective spawns several possible exam questions. Each exam question must be tied to a performance objective to accurately test one’s comprehensive knowledge of agronomy.

Where an academic exam contains a large variation in question difficulty, certification exam questions ask, “What is the minimum knowledge a professional must have to be proficient in this area.” This is determined by groups of volunteer CCAs, with guidance by the Agronomy Society’s excellent statistician Dawn Gibas, Ph.D., who reviews the performance of each exam question. Questions that nearly everyone gets right are eliminated as well as those that almost no one answers correctly. A complete exam review process takes place every four to five years.

An illustration of the difference between academic and certification exams can be given with a sports analogy. An academic exam is comparable to a high school physical education track and field program, where everyone is expected and encouraged to participate. A certification exam, on the other hand, is like the selection process for the Olympic high jumping team. The high school physical education program sets the bar low and gradually raises it to help students practice their technique and jump higher. But when the world competition is jumping over seven feet, the US team would set the bar at a level near that to select the most competitive team. During the selection process, if the bar is set too high, then they don’t have a team, but set the bar too low and the team has a poor chance of winning. When the psychometrician used this example, the proposal to classify the specific abilities of test takers was withdrawn.

The complexity of 21st-century agriculture practiced in the Western Region of the US supports the need for the most qualified field people providing the best recommendations for our growers so we can continue to deliver the highest-quality, safest agricultural products in the world.

Crop biostimulants are many things. First, they are claimed to be multi-functional, including enhancement of soil and crop health, acceleration of soil nutrient cycling and improvement of crop productivity and fruit quality, among other benefits. Second, they are categorized by the active ingredient, application method, cost and target crops. Third, they are popular among ever-greater numbers of vegetable farmers regardless of production system, scale and commodity. Finally, some of their performance/efficacy is variable, while many others are unknown.

According to Grand View Research Inc., the global revenue generated by biostimulants was $1.74 billion in 2016, dominated by European and North American companies. Projections indicate that the market value will reach $4.14 billion by 2025.

Though it is difficult to obtain an exact number of biostimulant products currently on the market, the estimate is over 600 with more becoming available each year. However, this grand prosperity of crop biostimulants is not shared equally among people who use them. Particularly to vegetable growers who operate farming at every scale that differs widely in climates, production timing, marketable portion, planting techniques, field preparation and maturity, it can be extremely complex to choose the right product from the long list and use it at the right time in the right way. The first and maybe the foremost step toward a more effective use of crop biostimulants among vegetable growers is to understand their current use, experience, concerns and hopes. To accomplish the task, a survey was sent out to collect the specific information from vegetable growers mainly in the San Joaquin Valley and other counties in California.

The Survey and Respondent

The survey was sent to approximately 648 vegetable growers in late October 2020 with the help of other UCCE advisors and commodity boards. The survey was then closed about two months thereafter before the responses were summarized. The original survey can be found at cestanislaus.ucanr.edu/Agriculture/Vegetable_Crops/Biostimulant_Survey/. The survey contains eight questions with the first four asking growers how they farm and the last four related to their experience and opinions to crop biostimulants. By the end of December 2020, we received a total of 83 responses (12.8%), with 74 of them being valid responses (11.4%). Nine responses were not included because there were two replies without an answer to any of the question, five responses from oversea, and two responses from counties outside California. Details about the composition and production of the 74 respondents are included below and in Table 1.

By production, there were 10, 27 and 37 growers claiming organic only, conventional only and mix of both.

By scale, there were 31, 7 and 36 growers with vegetable production scale below 100 acres, 100 to 500 acres and over 500 acres.

By commodity, crops with more than 10 responses included tomato (46), pepper (23), melon (21), summer/winter squash (21), leafy greens/herbs (21), cole crops (16), watermelon (16) and onion (13).

By production location, the 74 growers claimed to have their vegetable fields in 21 counties across California. For details, see Table 1.

Responses Regarding Biostimulants

The responses indicated that over half of respondents (40) know some knowledge about biostimulants, of which 37 applied biostimulants to at least one or two of their vegetable crops. There were nine growers who claimed having the highest knowledge level (very well), but two of them did not use biostimulants to any of their vegetable crops. There is no surprise that the majority of growers who responded with just a little knowledge or not knowing anything about crop biostimulants did not apply any biostimulant to any of their vegetable crops. The respondents were almost equally distributed by the application level of biostimulants (Table 2). The survey also asked the previous experience or future impression regarding the efficacy of biostimulants on improving vegetable growth. From the results, 50 growers, representing 68% of total respondents, shared the experience or impression that biostimulants could conditionally confer their efficacy. Less than 20% of the respondents indicated a consistent, positive performance on improving their vegetable crops, while only 13% gave the negative impression on biostimulant efficacy (Figure 1).

Concerns and Hopes

I have received numerous questions in the past years from vegetable growers, their advisors and colleagues regarding the biostimulant selection, effect evaluation, quality control and incompatibility with other field activities. “Going in blind”, “Unable to identify the benefits”, and “Snake oil” are common complaints. One of the main objectives for the survey is to identify the biggest concerns of using biostimulants on vegetable crops among growers. The survey results showed that about half of the respondents identified the difficulty of choosing a proper product as one of the main concerns followed by the risk of low or no return on investment. In addition, concerns of incomplete label and interference with fertilization and pesticide plans received 20 responses (Figure 2). Lastly, the survey asked growers their agreement level to future actions of improving the use of crop biostimulants. For all future measures, an average of 89% of the respondents agreed/strongly agreed that they will be helpful and important to improve future use of crop biostimulants (Table 3). These responses reflect the hopes from growers, and their voices should be heard by academia, industry, extension and other sectors to outline future efforts aiding a practical and profitable use of these biologics.

UCCE Biostimulant Testing Trials

The UCCE farm advisors from Stanislaus County are actively working with vegetable growers and biostimulant companies to conduct various testing trials each year. The main goal is to fill the data gap with more unbiased, statistically-viable product efficacy data on various vegetable commodities in the Central Valley. Since 2019, we have evaluated numerous biostimulants on processing tomato and watermelon productivity, fruit quality and plant health. Stay tuned to our newsletter and check for previous results (Veg Views: cestanislaus.ucanr.edu/news_102/Veg_Views/).

References

Biofertilizers Market Size, Share & Trends Analysis Report By Product, By Application, And Segment Forecasts, 2012 – 2022. grandviewresearch.com/industry-analysis/biofertilizers-industry.

When methyl bromide was banned in 2005, California strawberry growers lost an effective tool in their crop care toolbox to control weeds, soilborne diseases, nematodes and symphylans. Special-use permits allowed them to continue using the fumigant through 2016, but growers feared final loss of the powerful soil fumigant might be the end of profitable production.

The California Strawberry Commission agreed, noting that elimination of methyl bromide fumigation brought forth several soilborne diseases for which there is no post-plant control. Of particular concern were Fusarium wilt (Fusarium oxysporum f.sp. fragariae), Verticillium wilt (Verticillium dahlia) and charcoal rot (Macrophomina phaseolina), according to the California Strawberry Commission.

But once again, necessity proved to be the “mother of invention,” said independent agronomist and PCA Lee Stoeckle, owner of Stoeckle Agricultural Consulting in Ventura, Calif.

Stoeckle has advised strawberry and caneberry growers for more than 30 years, and he noted that effective alternative fumigants have taken up the methyl bromide void and are now widely and successfully used. While California strawberry acreage has fallen, total production has actually increased thanks to innovation and application of new technology.

Stoeckle’s family-owned business provides recommendations on 3,000 acres of strawberries and 100 acres of blackberries in Santa Barbara County and San Luis Obispo County and 2,000 acres of strawberries in Ventura County. In addition, he consults on production of 800 acres of strawberry and 250 acres of raspberries in Baja Mexico. While he is primarily responsible for above-ground insect and disease control, he doesn’t write fumigation recommendations but instead advises based on what he learns about weeds and soil pathogens.

A One-Two Punch

Top problem soilborne diseases, according to Stoeckle, are Fusarium, Macrophomina, Phytophthora, Anthracnose and Verticillium wilt. Top problem above-ground pests include two-spotted spider mites, Lygus bug, Botrytis fruit rot/gray mold and powdery mildew, depending on varietal susceptibility. Other pests necessary to watch include worms and aphids.

“The optimum disease and weed control program is a one-two punch,” Stoeckle says. “Hit it at the end of the season as a burndown and at the beginning before next planting via drip irrigation. The backbone of our control program is Pic-Chlor 60 EC (1,3-dichloropropene plus chloropicrin) at the max recommended rate (350 lbs/ac), going after the heavy hitting ‘big boys’ (soilborne diseases) when applied in August or September before planting.” He recommends Vapam or K-Pam to get the additional benefits to control these diseases (Fusarium, Verticillium, Macrophomina phacelia) and eliminate the inoculum reservoir in the crown.

Stoeckle says emulsified formulations of Telone® C-35 and chloropicrin can be applied with irrigation water through drip irrigation systems. Metam sodium is the active ingredient in Vapam® HL™ and metam potassium in the active ingredient in K-Pam® HL™. Both are AMVAC® soil fumigants, which give off methyl isothiocyanate (MITC) when combined with water via drip or otherwise. If drip fumigation is planned, good results have been obtained with a sequential application of chloropicrin or 1,3-dichloropropene plus chloropicrin, followed 7 days later with metam sodium or metam potassium.

Stoeckle considers fumigants essential and offers the math: “If we equate the value of every plant to be $2 each and you lose 10% of your plants, that’s 2,500 plants on a population of 25,000 per acre. Your choice is to fumigate or take a $5,000 loss. That’s an easy decision. The return on investment on fumigation is huge. We expect to see a 20% to 30% return on fumigant investment.”

He is quick to add there are other management decisions that help maximize production, noting, “I could go on and on about using the best plastic mulch or optimum fertilization practices.”

Best Practice Weed Control Reduces Production Costs

Fifth-generation Santa Barbara County grower Brett Ferini, owner of Rancho Laguna Farms, grows 400 acres of strawberries (300 fall plant, 100 summer plant) and 20 acres (adding another 20 for 40 total) of blackberries. Plus, he grows 35 acres of organic blackberries. He used Vapam on blackberries in February 2020.

“Vapam worked out really well in controlling nutgrass/nutsedge,” he said. “Pic-Clor 60 has no effect.”

For weed and disease control, “we hit everything at fall pre-plant with Pic-Clor 60 through drip tape and seven days after that we follow with Vapam,” he said. “It does a terrific job on nutsedge and other weeds, as well as the soilborne diseases including Verticillium, Phytophthora and, anecdotally, Macrophomina.”

Ferini says the operation plans to add a Vapam burndown at the end of the 2020 growing season

“We definitely [have] cut weeding by 60% on summer plant,” he says. “Labor is our highest cost. We saw $1,050 savings per acre vs. our normal costs of $1,800/acre. The big test will be on the fall plant when we get more rain. Our fall weeding cost normally runs $2,800 to $3,000 per acre. Using Pic-Clor 60 followed by Vapam treatment, I expect weeding cost savings of $1,000 to $1,500 per acre.”

Also seeing results with soil fumigants is Santa Barbara grower Josh Ford. He is COO of Ocean Breeze Ag Management LLC in Ventura, which grows 450 acres of strawberries, 50 acres of blackberries, and 25 acres of raspberries. Ford’s biggest soilborne pests are Macrophomina, Fusarium, and Phytophthora cactorum. Nutgrass is his most difficult weed to control.

“We’ve been using soil fumigants for many years,” he says. “We were using methyl bromide, but now we apply chloropicrin once a year and K-Pam once to twice a season. If nut grass is a bad problem, we will knock it down at the end of the season with K-Pam and also pre-plant K-Pam. Our ROI is good when you consider the increased cost of labor to manually remove nut grass.”

It is highly likely that growers, PCAs and other field professionals are familiar with the word “Pythium”. Pythium is the name of a soilborne, fungus-like organism that is notorious for primarily causing seedling diseases. Pythium is notable because many row crops are susceptible to it, the pathogen is very widely distributed and occurs in most cropped ground, and despite the use of IPM tools and strategies, Pythium problems can still show up in row crop production systems.

What is Pythium?

Pythium is a fungus-like organism. Previously considered to be a true fungus, molecular studies in recent years indicate that Pythium—as well as closely related organisms like Phytophthora and downy mildew—is more closely related to brown algae and diatoms. Formally, therefore, Pythium species are no longer part of the fungal taxonomic group but are classified in the kingdom Chromista, or Stramenopila. The Pythium genus contains over 200 species, most of which are not plant pathogens. There are Pythium species that are pathogens of animals (some of which can infect humans), and many species are saprophytes and only grow on dead and decaying organic material. Pythium species are mostly found in soil environments but are also present in aquatic habitats.

Plant pathogenic Pythium species are well equipped to cause problems on row crops. Most of these species form resilient, thick-walled sexual spores (oospores) that can withstand periods of unfavorable dry and warm conditions. These structures enable Pythium to persist in the soil for a long time. When favorable soil conditions are present, mostly in the form of abundant soil water, these Pythium organisms either produce hyphae that grow toward the roots or swimming spores (zoospores) that move through the soil water in search of susceptible plant tissues. Another feature that makes Pythium problematic for growers is the extremely fast growth rate of these organisms. Given suitable soil conditions, Pythium pathogens can rapidly grow from seed-to-seed, seedling-to-seedling and root-to-root.

Diverse Pythium Diseases

In contrast to many plant pathogens, Pythium causes several different types of problems on crops (Table 1). First, Pythium is a seed pathogen. Once placed in the ground, seed can be exposed to Pythium that is residing in the soil. If conditions are favorable for the pathogen, Pythium can invade and colonize the seed, causing it to rot before it can germinate. If the seed germinates, Pythium can cause a decay of the roots and shoots that just grew out of the seed. This early disease stage is often called damping-off. Damping-off is further divided into two phases. If the newly germinated seedling is infected so early and so severely that it dies before being able to break through the soil surface, this situation is called pre-emergent damping-off. However, post-emergent damping-off occurs if the diseased seedling is strong enough to emerge above the soil surface, only to succumb and collapse shortly afterwards. Collectively, seed decay, pre-emergent damping-off, and post-emergent damping-off can result in loss of plants very early in the production cycle, causing stand loss in the field.

Healthy seedlings that escape death at the seed and newly germinated stages remain vulnerable to this pathogen; established seedlings can still be infected and become stunted and die due to diseased roots and crowns. Older, established plants have escaped the damping-off phase that kills seedlings but can be subject to infections that prune back the roots, leading to reduced plant vigor and yield. For example, Pythium can cause late infections in cauliflower and result in weakened roots and poorly yielding plants. This soilborne pathogen can even cause a foliar blight of leaves and shoots, though this type of disease is not very common. Bits of soil carrying Pythium can be splashed or moved up onto foliage and cause blights on crops such as spinach and bean. Finally, the fleshy parts of some vegetable crops are subject to Pythium pathogens. If in contact with infested soil, cucurbit fruits, sweet potato storage roots and potato tubers can develop a soft, watery rot that will result in a non-marketable commodity.

Of the hundreds of Pythium species worldwide, relatively few species infect row crops. These plant pathogens can be conveniently placed into two categories. One group consists of Pythium species that have a relatively narrow host range and infect only a few crops, with those few crops tending to mostly be within a particular plant family. Examples are Pythium mastophorum, which primarily infects celery and parsley (Apiaceae family), and Pythium uncinulatum, which reportedly only causes significant disease on lettuce (Table 2). The second group contains Pythium organisms that have very large host ranges. The two main species, P. aphanidermatum and P. ultimum, both infect scores of plants, including dozens of vegetable and row crops.

Disease Development Development of Pythium diseases is straightforward. Initial inoculum is almost always linked with infested field soils and associated soil water. Pythium is a soilborne pathogen that resides in the soil primarily as dormant resting structures. Pythium inoculum is not seedborne or airborne. For Pythium to become active, grow, and produce those swimming zoospores, the soil must be wet for prolonged periods. Once susceptible seed, seedlings, and other plant parts are in close contact with Pythium inoculum, infection can take place and disease will be initiated. If wet soil conditions persist and temperatures are optimum for the pathogen, disease losses can be significant.

Diagnostic Considerations

Pythium is not the only soilborne pathogen that causes seedling damping-off and root rots of row crops. On spinach, damping-off and root rot can be caused by both Pythium and Fusarium; visually, one cannot distinguish between the symptoms caused by these two pathogens. Pythium and Phytophthora pathogens both cause dark, discolored roots of lettuce and cannot be differentiated in the field. Cauliflower transplants are susceptible to both Pythium and Rhizoctonia pathogens, both of which caused the roots to become discolored. Precise and accurate diagnosis of Pythium diseases will therefore require lab-based tests and assays.

Managing Pythium

Controlling diseases caused by Pythium requires the implementation of IPM practices.

Site selection: Choose to plant in fields that do not have a history of Pythium problems and have well-draining soils.

Crop rotation: If Pythium is an issue, avoid planting the same susceptible crop in the infested field. Rotate to crops that are not known to be susceptible to the Pythium species present at that location. However, remember that some Pythium species have very broad host ranges (Table 2).

Irrigation management: Because the Pythium pathogen is so strongly dependent on wet soil conditions, carefully schedule and limit irrigations to prevent overwatered, saturated soils.

Time of planting: In some cases, moving the planting date to a different time of year may help reduce losses to Pythium. For example, depending on the Pythium species of concern, planting the crop in the warmer, drier summer may be preferred to seeding the crop in the cooler, wetter spring.

Fungicides: Plant seed treated with a fungicide that is active against Pythium. Note that the fungicides used to control Rhizoctonia or Fusarium have no effect on Pythium. For some crops, applying fungicides to the emergent crop may provide additional protection. The repeated use of products having the same mode of action can result in Pythium isolates that are insensitive (=resistant) to those products; therefore, IPM strategies will require that thought be given to deploying different fungicides.

Resistant or tolerant cultivars: Unfortunately, there do not appear to be any row crop cultivars that have genetic resistance to Pythium.

Over the last year, a team from UCCE has been working with California small grains growers on practices that can improve nitrogen (N) use efficiency. At demonstration sites, we have implemented practices that UC Grain Cropping Systems Specialist Mark Lundy has been investigating for several years, namely N-rich reference zones, a soil nitrate quick test, handheld reflectance devices and aerial imagery. We demonstrate how to use these tools to manage N fertilizers in small grain crops across variable soil and climatic conditions in the Sacramento Valley, Delta, San Joaquin Valley and Intermountain Region.

The demonstrations are funded by the CDFA Fertilizer Research and Education Program and a USDA-NRCS California Conservation Innovation Grant. Our goal is to help growers and consultants learn and implement these practices to guide N fertilization in small grains, thereby increasing crop productivity and N use efficiency while reducing potential for N loss to the environment.

What are “N-Rich Reference Zones”?

Reference zones are most useful to growers who can apply the majority of their seasonal N budget during or after the tillering stage of growth. Previous work has shown that N fertilizer applied during the season−between the tillering and heading stages of small grain development−results in higher yields, higher protein and increased fertilizer use efficiency compared to pre-plant applications. The reference zone is a relatively small area within the field where extra N fertilizer is added at the beginning of the season. This extra fertilizer ensures that the reference zone will not be N-limited from planting until an in-season fertilizer decision is made. When a grower is determining whether and how much N fertilizer to add in-season, measurements from both the reference zone and the broader field are compared to understand whether the broader field is sufficient in plant-available N.

Fertilizer N Rate and Field Variability

Fertilizer N rate and field variability are two important considerations when creating N-rich reference zones. The amount of N to apply in the N-rich zone will depend on several factors such as yield goal, protein goal and when the expected in-season fertilizer application will take place. There should be sufficient N applied to the reference zone at planting to ensure that the plants in the zone are not limited by N at the stages of growth when the in-season fertilizer is applied. Table 1 gives some examples of how much N fertilizer to apply to the N-rich zone for a range of potential yields.

It is important to establish the N-rich zones in representative parts of the field. Areas of the field that are unique (i.e. low areas, high areas, gravel strips, etc.) should be avoided. It is also important that the zones capture field variability. If certain areas have distinct soil types or known patterns of yield or management differences, a grower should establish multiple zones to account for these sources of spatial variability if they represent large areas in the field. Soil maps (available from casoilresource.lawr.ucdavis.edu/soilweb-apps/) and historical aerial imagery can often help in identifying field patterns and good location(s) for reference zones.

How and When to Apply the N-Rich Zone Fertilizer

A grower can establish N-rich zones during the pre-plant fertilizer application. For example, a grower may apply 50 pounds N per acre across the field and then make another pass or two in the zone to apply an additional 50 to 100 pounds N per acre (depending on what the grower calculates is necessary, as described above.) This method might be most easily adopted by growers. We have observed, however, that if the fertilizer is placed too deep in the soil profile, the N may not be readily available to the seedling crop early in the season because it is below the root zone. Therefore, N-rich zones established by this method may not provide a reliable early-season point of comparison. Instead, we have found that broadcasting urea is the most effective way to establish N-rich zones. At our demonstration sites, we broadcasted urea after tillage or shortly after planting, but always ahead of a storm or irrigation event that could incorporate the fertilizer. Orienting the zones perpendicular to the rows or tractor passes also helps to capture field variability. When the zones are too narrow and run in the same direction as the field work, it can be hard to differentiate between a field pattern associated with equipment passes and a N effect, particularly early in the season.

Monitoring the Field

Once the crop begins to grow, the field should be monitored periodically to assess whether the crop is likely to respond to a N fertilizer application. A combination of the soil nitrate quick test (SNQT) and plant reflectance measurements taken from both the N-rich zones and the broader field can indicate when a top-dress fertilizer application may be beneficial. The soil nitrate quick test and plant reflectance measurements complement other important information like current crop growth stage, crop yield and protein goals, and local weather records to inform a site-specific N fertilizer recommendation.

The SNQT is a simple and low-cost test that provides a ballpark estimate of the soil nitrate-N concentration in the root zone. Nitrate is a highly plant-available form of N. Using the SNQT when N fertilizer decisions are being made will help to narrow a range of fertilizer rates appropriate for that field. More information on using the SNQT in small grains, including a sample protocol and demonstration video, is available at smallgrains.ucanr.edu/Nutrient_Management/snqt/. Over the past several years, UCCE agronomists have developed a strong relationship between the value measured using the SNQT and an estimate of fertilizer N equivalence.

Crop reflectance can be measured using a number of tools, including handheld devices, drones and satellite imagery. Common indices that result from measurements of canopy reflectance are normalized difference vegetation index (NDVI) and normalized difference red edge index (NDRE). These indices represent measurements of light reflected from the crop canopy at key wavelengths indicative of plant vigor. Relative differences in vigor among plants in the same field can be captured by comparing canopy reflectance measurements like NDVI and NDRE. We have been using handheld devices, drones and satellite imagery at our demonstration sites to compare crop reflectance values in the N-rich zones and the broader field.

One of the tools we are using is the GreenSeeker by Trimble Agriculture. This is a hand-held NDVI meter (See Figure 1) that emits light and detects how much is reflected from the crop canopy in the red and infrared wavelengths. The GreenSeeker’s canopy measurement indicates how well the plants are growing and covering the soil with greenness. This information about vigor is important early in the crop’s growth because it indicates the ability of plants to support grain production and yield potential.

We are obtaining similar information as from the GreenSeeker by measuring NDRE with a five-band multispectral camera (MicaSense RedEdge-MX) mounted on a drone (DJI Matrice M200 V2). NDRE is similar to NDVI but replaces the reflectance from the red wavelength with reflectance from the red edge wavelength. Because the drone is able to capture data from hundreds of feet above the ground, it allows us to measure a large area quickly and under conditions when entering the field is not possible. Figure 2 depicts side-by-side images from a field in Solano County where N-rich reference zones were implemented during the 2019-20 season.

Another device we are using to monitor plant N is the atLEAF CHL by FT Green LLC, which is a chlorophyll meter that measures light absorbed by a single leaf (Figure 3). Like the GreenSeeker, it also emits and detects light. The atLEAF CHL, however, measures how much light passes through a single leaf instead of measuring reflected light. This information becomes increasingly valuable as an indicator of whether or not the crop has sufficient N as it begins heading out and filling grain.

Step-by-step instructions for using both the GreenSeeker and atLEAF CHL in small grains are available at ucanr.edu/blogs/blogcore/postdetail.cfm?postnum=42903.

Since plant N is strongly related to plant greenness and chlorophyll content, measurements of NDVI, NDRE and leaf chlorophyll can serve as proxies for relative plant N status within a field. Many factors can affect absolute greenness or chlorophyll values, including variety, crop injury and environmental factors. Because of this, it is important to remember that the absolute values given by these devices are only meaningful when compared to a reference zone like the N-rich zone.

What do the Readings Mean?

Plant reflectance and transmittance measurements are best interpreted by expressing values measured in the broader field relative to the N-rich reference zones, according to the following equation:

Relative value= (Production area value)/(N-rich zone value)

The relative value is sometimes referred to as a Sufficiency Index (SI) and will usually result in a decimal value between 0 and 1. When the SI is below a certain threshold, it indicates that the production area is experiencing detectable N deficiency relative to the N-rich zone. Table 2 shows SI ranges for proximal and remotely-sensed data and the associated plant N status.

When it comes to deciding on N fertilization in California small grains, a N fertilizer response is almost certain when plant N status is “Highly Deficient”, very likely when the status is “Deficient” and uncertain when the status is “Sufficient”. The SNQT supplements the plant measurements with information about the current nitrate concentration in the root zone.

If a grower decides that a N fertilizer application is warranted based on the combination of plant and soil measurements, the next step is to figure how much N is necessary. This can be determined using a crop growth and N uptake model in conjunction with yield and protein goals. As part of our larger demonstration project, we will be releasing an online decision support tool in 2021 that integrates these components and provides customized predictions of crop response to in-season N fertilizer.

Summary

California farmers are under pressure to increase N use efficiency and reduce the potential for N loss to the environment. N-rich reference zones are a tool that can assist in these goals while considering and managing the risk of reduced yields. By implementing N-rich reference zones, using a suite of tools to monitor them during the season and comparing results to the broader field, a grower gets real-time knowledge to inform N fertilizer management in small grains. The information gained from implementing N-rich reference zones can help growers make fertilizer applications when increased yield and/or protein benefits are likely and avoid them when they are not. These improvements in N fertilizer decision-making can yield better economic and environmental outcomes in California small grain systems.