- Author: Michelle Leinfelder-Miles
(There was an error in the previous version of this blog post. The error has been corrected here and in the full report, available from my website.)
The purpose of this trial was to better understand optimal seeding rates for grain sorghum grown in the Sacramento-San Joaquin River Delta – a unique agricultural region known for its fertile, organic soils, shallow groundwater, and cooler climate conditions. The trial was planted in the Sacramento-San Joaquin Delta, on Tyler Island in Sacramento County. The soil is a Rindge mucky silt loam with approximately 20 percent organic matter in the top 15 inches of soil. The Rindge series is a mucky peat soil down to about 60 inches, and approximately 55,600 acres in the Delta are described by the Rindge classification. The plot was planted on May 20, 2016 using a John Deere cone planter. Seed was planted approximately 2 inches deep. The trial was a white sorghum variety, Eureka Seeds 3292, which was the grower's variety. The variety has 16,000 seeds/lb and 85 percent germination, according to the label. Five seeding rate treatments (5, 6, 9, 12, and 15 lbs/acre) were replicated over four blocks positioned down the rows. The seeding rates are expressed as plant populations in Table 1. (The number of sorghum seeds/lb is highly variable across varieties. For this reason, when determining seeding rates, growers should first determine their desired plant population. A worksheet for calculating seeding rate from desired plant population is available from the full report.) Each plot consisted of four rows (30-inch row spacing) that were 45 feet in length. The previous crop in the field was wheat. Subsurface irrigation by “spud ditch” sub-surface irrigation was employed twice. The field was fertilized at planting with 35 gallons/acre of 8-24-0 with ½ percent of zinc. The field was cultivated one time, and Maestro 4EC (8 oz/acre), AAtrex 4L (0.75 pint/acre), and Crosshair (4 oz/acre) were applied for post-emergence weed control in mid-June. The plot was harvested on November 14, 2016 using an Almaco research combine, harvesting the center two rows from the four-row plots.
Trial results are presented as plant establishment characteristics (Table 1), plant maturity characteristics (Table 2), and yield (Figure 1). The tables and figure present mean values for the four replicates. Tukey's range test was the statistical method used to compare the means. Varieties were considered statistically different if their P value was less than 0.05, or 5 percent. Differences between treatments are indicated by different letters following the mean.
The estimated plant populations for the treatment seeding rates were calculated using the number of seeds/lb and percent germination for this variety. Stand counts were made as the number of plants/10-foot row length on June 1st and June 16th, and these counts were scaled up to plants/acre. Stand counts were as expected - higher counts for the higher seeding rates. Stand counts for all treatments decreased from June 1st to June 16th, but stand counts remained on target with the estimated plant population for the 5 and 6-lb seeding rates. Weeds were also counted in the month after planting and in the month before harvest (data not shown), but overall weed pressure was very low at this location.
There were no differences in the number days to flowering among treatments; however, there were differences among treatments in the other maturity characteristics. The higher seeding rate plots had taller plants with longer panicle exsertion (the length of the stem from the top leaf to the bottom of the panicle), which may suggest that at these higher densities, plants were competing with each other and growing taller. Panicles were longest in the 5 lb seeding rate and statistically longer than the panicles in the 12-lb and 15-lb rates. There were no statistical differences in grain moisture at harvest.
The treatment yields do not provide a clear take-home message of the results, except perhaps to show that the highest seeding rate (15 lbs/acre) is not an optimum seeding rate. However, if the 9-lb treatment was ignored, there would be a trend for yield to decrease as the seeding rate increased. A possible explanation for the high yield of the 9-lb treatment is that there were three of these plots proximal to the sub-irrigation ditches, which were exterior to the experiment on both sides. The 9-lb treatment may have been inadvertently favored with better moisture conditions as a result of the experimental design. In hindsight, the experiment should have been blocked across the rows instead of down the rows to account for these field conditions which may have introduced variability in soil moisture. Blocking down the rows accounted for very little unexplained variability, and in future years, the experiment will be designed to account for the variability across the rows.
In summary, it is important to study sorghum cultural practices in the Sacramento-San Joaquin Delta region because crop acreage appears to be increasing, and the Delta is a unique growing region of California. Sorghum seeding rates as a function of plant population were studied to assist growers with determining optimum rates for the Delta environment. While results are somewhat inconclusive, there appears to be a trend for the lower seeding rates to yield the highest. If this trend is shown in future years, then Delta growers could have higher productivity with lower seed costs.
- Author: Michelle Leinfelder-Miles
UC Cooperative Extension will host the SJC and Delta Field Crops Meeting on Friday, January 6, 2017 from 8:00am to 12:00pm. The meeting location is the Cabral Agricultural Center in Stockton (2101 E.Earhart Ave., Stockton, CA 95206).
The agenda is as follows:
8:00am Doors Open, Sign In, and Welcome
8:10am Sorghum Seeding Rates for Optimum Productivity, Michelle Leinfelder-Miles, UCCE, San Joaquin/Delta Counties
8:35m New Pest Advisory: Sugarcane Aphid in California Sorghum, Larry Godfrey, UC Davis
9:05am The Do's and Don'ts of Planting Grain and Forage Sorghum – Why Sorghum is not Corn!, Jeff Dahlberg, UC Kearney Research and Education Center, Parlier
9:30am Update on New Herbicide Options for Established Alfalfa, Mick Canevari, UCCE, San Joaquin County
10:00am BREAK
10:10am Tools for Selecting Small Grain Varieties from UCCE Statewide Trials, Mark Lundy, UC Davis
10:35am Comparing Methods for Estimating Crop Consumptive Water Use in the Delta: Background and Preliminary Results, Kyaw Tha Paw U, Eric Kent, Jenae' Clay, UC Davis
11:00am Nitrogen Mineralization in Soils from the Delta and the Valley, Daniel Geisseler, UC Davis
11:25am Managing Gophers in Alfalfa Fields, Roger Baldwin, UC Davis
11:55am Wrap-up and evaluations
Continuing education (DPR and CCA) will be available. Our programs are open to all potential participants. If you require special accommodations, please contact UCCE San Joaquin County at 209-953-6100. Thank you, and hope to see you at the meeting.
- Author: Michelle Leinfelder-Miles
UC IPM Advisor, Pete Goodell, requests your assistance with an alfalfa IPM survey.
How much IPM is being used in alfalfa in California? A new survey tool wants to help answer that question and we need your help.
If you are interested in participating in developing measures of progress in alfalfa IPM, please volunteer to take the on-line survey. This survey will be used to gauge the level of IPM utilized by California alfalfa growers, similar to surveys conducted in almonds and cotton over the years.
Your participation in this survey will support your Extension and research professionals in getting a better picture of alfalfa pest management practices in California and help identify areas where additional IPM information may be useful.
The survey will take about 20 minutes to complete. All answers are completely confidential and will be grouped for analysis purposes. Survey results will be compiled by the Center for Urban Affairs and Community Services at NC State University. If you have questions about the survey, please contact Dr. Jean-Jacques Dubois, at jbdubois@ncsu.edu.
Thank you for your consideration in responding to this alfalfa IPM survey.
- Author: Michelle Leinfelder-Miles
Table 1 shows the results of the 2016 UCCE Delta field corn variety trial, located on Tyler Island. Three replicate blocks of eighteen varieties were planted on April 27th by air planter. The eighteen varieties included 16 varieties submitted by seed companies and two varieties submitted by the grower. All varieties supplied by the seed companies were glyphosate-tolerant varieties. Each plot consisted of four 30-inch beds on an average row length of 1158 feet. Seed was planted approximately two inches deep and six inches apart down the row. The soil is a Rindge mucky silt loam with approximately 20 percent organic matter in the top 15 inches of soil. The Rindge series is a mucky peat soil down to about 60 inches, and approximately 55,600 acres in the Delta are described by the Rindge classification. The previous crop in the field was wheat. Subsurface irrigation by “spud ditch” was employed three times. Nitrogen was applied preplant (125 units/acre as NH3), and 34 gallons/acre of 8-24-6 with ½% of zinc was knifed in at planting. Weed control was by cultivation and herbicide application (Steadfast, Shark, and No Foam A adjuvant). Zeal miticide was applied. The field was harvested on October 10th.
The table presents mean values for the three replicates. When interpreting the results, keep the following in mind. The mean is equal to the sum of values divided by the number of values, in this case, three replicates. The statistical method used to compare the means, called Tukey's range test, compares all means against each other. Varieties were considered statistically different if their P value was less than 0.05, or 5 percent. What this means is that when differences between varieties exist, we are 95% certain that the two varieties are actually different; the results are not due to random chance. Differences between varieties are indicated by different letters following the mean. For example, a variety that has only the letter “a” after the mean yield value is different from a variety that is followed by only the letter “b”, but it is not different from a variety whose mean value is followed by both letters (“ab”). Similarly, a variety whose mean yield is followed by the letters “ab” is not different from a variety whose mean yield is followed by the letters “bc”. Seven varieties have a letter “a” following their mean yield, which means that those seven varieties all performed similarly in the trial. The numerical values of these seven varieties differ, but based on this research, we cannot attribute those numerical differences to variety differences. Among varieties, there were also differences in stand count, bloom date, fusarium ear rot presence, ear height, grain moisture, and bushel weight.
The CV, or coefficient of variation, is the standard deviation divided by the mean, or a measure of variability in relation to the mean. For some measures, particularly the disease percentage, the variability between the three replicates was very high.
Special thanks go to grower cooperators, Steve and Gary Mello, and participating seed companies. The report is available in an easy-to-print version from my website.
- Author: Michelle Leinfelder-Miles
- Author: Brenna Aegerter
Blue-green algae, or cyanobacteria, is a photosynthetic organism that can proliferate, or “bloom”, in waters that are warm and stagnant. It is a concern for human and animal health because it can produce toxins that cause nerve and liver damage. Blue-green algae has been in the news recently. In mid-July, residents of Discovery Bay reported seeing it in the waters of that community. More recently, it has been observed in other Delta waters. While the presence of blue-green algae does not guarantee the presence of toxins, the water around Discovery Bay was tested and confirmed to have the toxin microcystin, and the public has been advised not to enter waters where blue-green algae blooms are observed. Blue-green algae affected waters appear as olive-colored, have surface scums or the appearance of oil slicks, or have green flecks of material. The waters may also have a musty odor.
I was recently asked by a grower if irrigating with water having blue-green algae can damage crops. I have not been able to find much local or statewide knowledge on this, but I have found some pamphlets out of Australia that address this question. I have attached those documents below. Both documents indicate that there is more to learn about whether irrigation water having blue-green algae will affect plants. If there are detrimental effects, they would mostly likely reduce germination or seedling growth, which could ultimately reduce productivity. Another concern for growers is that the blue-green algae could clog irrigation equipment and reduce its efficiency. Because blue-green algae toxins are heat-stabile, it is advised not to use overhead irrigation on crops that are eaten directly, and it is advised that animals not be put on grazed crops (where irrigation water may have touched foliage) for at least seven days after irrigating. The toxins are water soluble, so advice for consumers is to thoroughly wash produce with clean water before consuming, whether eating it raw or cooked.
Luckily, the blue-green algae population should decrease as winter approaches and the weather (and waters) cool down. In the meantime, the State Water Resources Control Board has developed a website (http://www.mywaterquality.ca.gov/habs/index.html ) where the public can see where blue-green algae blooms have been verified and report a bloom that has been encountered. In addition to the website, bloom reporting and information is available by phone (916-341-5357 or toll free at 844-729-6466) or email (CyanoHAB.Reports@waterboards.ca.gov).
Blue-Green Algae and Irrigation Water
Irrigating with Blue-green Algae Affected Water