Month: October 2020

Soil Health in New York State: Establishing Aspirational Goals and Soil Organic Carbon Sequestration Opportunities

Joseph Amsili, Harold van Es, Robert Schindelbeck, Kirsten Kurtz, and David Wolfe
Soil and Crop Sciences and Horticulture Sections, Cornell University

The soil is a foundational resource for life on earth and its health is critical to the sustainability of agriculture and food systems. Healthy soils can lead to increased profitability and resilience to extreme weather for farmers, while also contributing to many off-farm benefits, including improved water quality and climate change mitigation. Defining realistic soil health targets and goals for farmers, professionals, and policymakers is a critical step to making progress towards New York State’s water quality and climate mitigation goals.

In order to establish aspirational soil health goals and assess soil organic carbon sequestration potential (for carbon farming programs), we summarized results from 542 soil samples from across New York State with both cropping system and soil texture information (Figure 1). Each composite soil sample went through the Standard Comprehensive Assessment of Soil Health (CASH) package at the Cornell Soil Health Laboratory.

Figure 1. Cropping system and soil texture groups used to establish aspirational soil health goals.

These reports include a first attempt at developing aspirational soil health goals for NYS by soil texture and cropping system. It is based on the 75th percentile of the distribution for each biological and physical soil health indicator in each cropping system and texture grouping (Figure 2). We’ve known that soil texture determines the amount of organic matter a soil can hold and needs to be considered when defining soil health goals. But our results also indicate that cropping systems should be considered when defining soil health goals. For example, it’s not realistic or useful to hold a 1,000-acre annual grain operation to the same standards as a five-acre organic vegetable farm. These aspirational soil health goals provide realistic targets for NYS farmers within the context of their own production environment.

Figure 2. Aspirational soil health goals for soil organic matter, active carbon, soil protein, soil respiration, and aggregate stability for different cropping systems on loam textured soils. The full table of aspirational soil health goals by soil texture and cropping system are available in the reports below.

Soil health practices, including reduced tillage, cover crops, organic amendments, and perennial crops, have the potential to build and maintain soil organic carbon levels, which can help remove some atmospheric carbon dioxide (CO2). An important consideration is that soils have a limited capacity to store soil organic carbon, mostly based on texture and mineralogy. As a soil approaches its saturation point, carbon inputs in the form of plant residues or organic amendments have decreased efficiency at further increasing soil organic carbon. Once this is saturated, soil organic carbon can only build up in more labile fractions that are less protected, more readily decomposed and returned to the atmosphere as carbon dioxide, i.e., the carbon gains in that case are not permanent.

Our results show that most fields under Annual Grain and Processing Vegetable cropping systems have less soil organic carbon than their capacities based on texture class in a grassland system (Figure 3). Therefore, these cropping systems have the greatest potential to stabilize additional soil organic carbon. Conversely, many fields in Pasture and Mixed Vegetable systems are closer to their saturation levels and therefore have less potential to sequester more carbon. Dairy Crop fields are intermediate. Annual Grain and Processing Vegetable systems can build soil organic carbon by incorporating the types of management practices that make Dairy Crop, Mixed Vegetable, and Pasture soils healthier. This includes applications of composts and manure, integration of livestock, better rotations, cover cropping and reduced tillage.

Figure 3. Soil organic carbon as a fraction of the saturation potential of the silt and clay fraction across different cropping systems (based on grassland systems). Carbon sequestration potential is greater at lower saturation levels.

The results of these reports will enable New York State policy makers, agricultural professionals, and farmers to set goals for improved soil health and carbon farming within the context of their soil type and cropping system. Additionally, relative carbon saturation metrics can be used to optimize carbon allocations for soil sequestration and thereby also improve soil health.

Figure 3. The Characterization of Soil Health in New York State Summary (left) and Technical Report (right) are now available.

For more information, please visit our website: newyorksoilhealth.org

2020 Corn Silage Overview

Joe Lawrence, Allison Kerwin – Cornell PRO-DAIRY

The growing season across much of the Northeast started out with below average temperatures. Despite the cool start, relatively dry conditions coupled with warmer temperatures as the month of May progressed provided generally good conditions for corn planting with all trial locations planted between May 5th and May 21st (Table 1). As the season progressed, all locations experienced below average precipitation and above average heat accumulation. Several locations were designated as abnormally dry to moderate drought throughout June and July; however, in most cases, the crop proved quite resilient and rainfall in mid-July was critical to generally successful pollination. It is worth noting that at several locations, seasonal rainfall totals were inflated by extreme rain events that generally pose greater risk (in terms of the potential for strong winds, runoff and other potential crop damage) than benefit to the crop.

It should also be recognized that some areas of the state experienced more severe drought conditions than these locations leading to more significant negative impacts on yield and forage quality. In these areas greater shifts in management strategies will be needed to make adjustments in feeding programs.

Table 1
Maturity Group Location Planting Date Harvest Date Seasonal GDD (86/50) Seasonal Rainfall (inches)
 

80 – 95 day RM

38 entries

 Willsboro, NY

Albion, NY

Alburgh, VT

 May 21

May 20

May 13

 September 1

September 4

September 9

 2073

2163

2099

 10.54

12.63

15.47
 

96 – 110 day RM

52 entries

 Madrid, NY

Aurora, NY

Alburgh, VT

 May 5

May 13

May 14

 September 15

August 31

September 21

 2231

2144

2198

 10.44

11.43

15.68

As 2020 corn silage sits in storage, hopefully fermenting for the next few months before being fed out, it is helpful to understand how this crop might feed compared to previous years. Using the trial results as an indicator of corn silage performance gives us an idea of average performance. Data for the detailed hybrid specific report of the trials is still being processed, but we do have enough information to look at overall performance trends.

Keep in mind this is an average of certain locations and your conditions may vary. On your own farm, it is helpful to take samples of your forage at harvest and again prior to feed out to understand the opportunities and challenges as you begin to feed this year’s crop. We also need to remember that while fresh samples can be a helpful indicator, some characteristics of the forage will change during fermentation, particularly starch digestibility.

As additional years of data are collected, patterns begin to form. As the 2020 season progressed, there were many similarities to the 2018 growing season (Figure 1a &1b). While total rainfall varied from 2018 at several locations, the rainfall totals are a bit misleading as the pattern and timing of this rainfall led to abnormally dry to drought conditions at all locations at different points in the season.

Fig. 1a
Fig. 1b

The influence of weather on key forage quality parameters, such as fiber digestibility, has been an area of focus in this work. As the season progressed, the similarities to 2018 suggested the potential for a highly digestible crop.  This projection was validated as the 2020 trial data shows a crop with high fiber digestibility as well as high starch levels (Figure 2a & Figure 2b).

Another way to look at these key parameters and to compare with previous years is to look at the sample spread across a range of values for these parameters. Table 2 and Figures 2a and 2b show the differences in undigested neutral detergent fiber after 240 hours of digestion (uNDF240) and starch content, respectively. The data in Figure 2 represents the last four growing seasons (2017 – 2020) with results combined from all locations (Albion, Willsboro, Aurora, Madrid and Alburgh) by year.

Fig. 2a
Fig. 2b

Each year brings its own challenges and opportunities. Given the variation in growing conditions across the region, it is critical to test your own forages to understand the site-specific impacts of the growing season.

It is important to evaluate this data in the context of your farm when selecting hybrids. The top performing hybrid at any one location or in any one category may not be a good fit for your feeding program. Factors that influence this vary by farm but include land base, soil resources, forage inventory, quality of available hay crops, access and cost of supplemental ingredients, and expectations of cow performance.

The trial results and location averages serve as a means to calibrate hybrid performance to a particular growing season. These averages can be used in conjunction with a company’s data on hybrids in their lineup, including hybrids not entered into these trials, to understand how a hybrid performed relative to what is realistic for a given growing season. For example, in Figure 2, we see that the highest percentage of samples have an uNDF240, %DM value in the 9-10% category and over 50% of samples having a starch content of 50% or greater. This can be used to evaluate how close or far away from these values other hybrids performed in 2020.

It is important to recognize the companies that make these trials possible through their entry of hybrids.  The following companies participated in the 2020 trials.

Albert Lea – Viking, Blue River Organic, Brevant, Channel, Dekalb, Growmark FS, Hubner, King Fisher (King’s Agri-seed), Local Seed Company, Masters Choice, Nutrien Ag Solutions – Dyna-Gro, Pioneer, Redtail (King’s Agri-seed), Schlessman (Gold Star Feed & Grain), Seed Consultants, Seedway, Syngenta – NK

 

Headlands often reduce overall field yield. Are they worth fixing?

S. Sunoja, Dilip Kharela, Tulsi Kharela, Jason Choa, Karl J. Czymmeka,b, Quirine M. Ketteringsa
aNutrient Management Spear Program, bPRODAIRY, Department of Animal Science, Cornell University

Introduction

Headland areas are defined as the outer edges of the field where farm equipment turns during field operations such as planting, sidedressing and harvest and where hedgerows or other physical features separate a field from adjacent fields or other land uses. The equipment traffic areas can be compacted which can cause considerable yield loss. Beyond compaction, yield loss in headland areas may also reflect edge-feeding of pests such as birds, rodents and deer, and competition for light, water, and nutrient resources with adjacent tree lines. Better decisions about headland management including investments to improve production potential, planting of other crops, or reductions in fertility or other crop inputs can be made when we know how much yield is given up on headlands. In the past several years, we have provided farm specific yield reports to farmers who have shared their corn silage and grain yield data with us.  The reports included yield by field with and without headland areas included.  Here we put all that information together, across farms, to evaluate how much corn grain and silage yield may be lost on headland areas across fields.

Corn Grain and Silage Yield Data

Corn yield data from 2648 fields representing ~49000 acres across 63 farms in New York were analyzed. This included 1281 corn grain fields and 1367 corn silage fields across two years (2017 & 2018). The yield data from each field were processed and cleaned using Yield Editor (free software from USDA-ARS) following the cleaning protocol developed by the Nutrient Management Spear Program at Cornell University (Kharel et al., 2020). Headland removal was performed in Yield Editor by manually selecting the outer edge passes and deleting the data points (Figure 1).

maps of headlands
Figure 1. Headland areas were removed using Yield Editor. Shown are (a) cleaned yield data including headland areas, (b) selected headland areas represented in black, and (c) yield in non-headland areas (i.e. after removal of headlands). Adapted from Sunoj et al. (2020).

Average field size ranged from 18.5 acres per field for grain and 19.3 acres per field for silage. Corn grain yields averaged 181 ± 33 bu/acre versus 22 ± 5 tons/acre for corn silage. We calculated optimal production, defined as production that could be obtained if the headland portion had yielded the same as the non-headland portion. We calculated production gain as the percentage increase between the actual and optimal production.

Results

Across all fields, the yield in the headland area was lower than the yield of the non-headland area (Figure 2A) for 94% of the grain fields and 91% of the silage fields. For some fields, the headland area yielded more than the non-headland area, possibly due to: (1) within-field features (e.g., trees, wet spots, alley ways), (2) irregular shapes of fields with short passes (as typically seen in New York agriculture), and (3) multiple directions of harvest within a field. The average yields were 188 bu/acre (non-headland area) and 161 bu/acre (headland areas) for corn grain. For silage, the average yields were 22.6 tons/acre (non-headland area) and 18.9 tons/acre (headland areas). Thus, headland yields were 14% (grain) and 16% (silage) lower than yields in the non-headland areas.

yield in scatter plot and bar graph
Figure 2. (A) Field scale yield in headland versus non-headland for corn grain and silage; and (B) distribution of production gain across all fields. Each circular marker in (A) represents a field. Adapted from Sunoj et al. (2020).

If the headlands yielded as much as the non-headland area, the production gain ranged from -8 to 32% for corn grain, and from -17 to 42% for corn silage (Figure 2B). The negative production gains reflected field that yielded more on the headland areas than the non-headland areas (points below the 1:1 line in Figure 2A). Averaging across all fields, the production gain amounted to about 4% for both corn grain and silage fields. However, 1% of the grain and silage fields had a potential production gain that exceeded 20%; 25% of the grain fields and 28% of the silage fields had gains between 5 and 20%, while for the rest of the fields (74% and 71%) potential yield gains were less than 5%. Production gains exceeding 20% were obtained on fields with the total field area was less than 25 acres, and with corn grain yields less than 143 bu/acre and silage yield less than 24 tons/acre. Such yield differences can, depending on the farm, reflect a considerable loss of yield and opportunity to improve total returns per cropland area.

Conclusions and Implications

Yield in headland areas was, on average, 14% (grain) and 16% (silage) lower than in the non-headland areas of the field. Taking into account the total percentage of a field in headland, at the field and farm levels, the potential yield gain amounted to 4%. The overall averages conceal the wide range of production gain values obtained in New York fields, from negative up to 32% for corn grain and up to 42% for some corn silage fields. Based on production gain for specific fields, farmers can either choose to ‘repair’ the headland with management (e.g., vertical tillage or subsoiling) to increase overall productivity and return on investment in seed and crop inputs, reduce crop inputs without further loss of yield in headlands, or ‘retire’ the headland from main crop farming and opt for perennial hay crop and conservation uses.

Additional Resources

Full Citation

This article is summarized from our peer-reviewed publication: Sunoj, S., D. Kharel, T.P. Kharel, J. Cho, K.J. Czymmek, and Q.M. Ketterings (2020). Impact of headland area on whole field and farm corn silage and grain yield. Agronomy Journal (in press). https://doi.org/10.1002/agj2.20489.

Acknowledgements

This research was funded with grants from the Northern New York Agricultural Development Program (NNYADP), New York State Corn Growers Association (NYSCGA), and federal formula funds. We thank the farmers and crop consultants for sharing whole-farm corn silage and grain yield data. For questions about these results, contact Quirine M. Ketterings at 607-255-3061 or qmk2@cornell.edu, and/or visit the Cornell Nutrient Management Spear Program website at: http://nmsp.cals.cornell.edu/.

Soil Health in New York State: Effects of Soil Texture and Cropping System

Joseph Amsili, Harold van Es, Robert Schindelbeck, Kirsten Kurtz, David Wolfe, and Galia Barshad
Soil and Crop Sciences and Horticulture Sections, Cornell University

Soil health concepts, practices, and testing have generated a growing awareness of the soil’s central role and highlights that sustainable soil management requires an understanding of biological, physical, and chemical processes and their interrelationships. Furthermore, it is recognized that human management can significantly degrade or improve the quality of the soil.

New York State (NYS), through Cornell University, has been a global leader in the development of soil health programs, including the development of testing methodologies. NYS land managers are becoming increasingly excited about improving the health of their soils. As progress is made in characterizing the health of soils nationwide, researchers will be able to develop regionally specific interpretive metrics that are shaped by the interplay of soil management with soil types and climate.

As part of that effort, we have summarized results from 1,456 soil samples from across New York State from a variety of soil types and cropping systems (Figure 1). Each composite soil sample went through the Standard Comprehensive Assessment of Soil Health (CASH) package at the Cornell Soil Health Laboratory.

Figure 1. Distribution of soil health samples by county across New York State.

The report demonstrated the important effects of soil texture and cropping system on soil health parameters (Figure 2). For many biological soil health indicators, soils with higher amounts of silt and clay showed higher values, which needs to be accounted for when interpreting test results. Overall, human management through cropping system had a big impact on soil health status, and cropping system differences often reflected the cycling and flows of carbon and nutrients. Pasture systems maintained the best overall soil health because these fields are seldom disturbed by tillage and receive year-round root and shoot inputs. Mixed Vegetable systems typically involve certified organic practices with diverse rotations, cover cropping, and significant quantities of organic nutrient amendments such as compost. Dairy Crop systems can maintain soil health due to cycling of carbon and nutrients through manure inputs and rotations with perennial legume and grass sods. In contrast, Annual Grain and Processing Vegetable systems are intensively managed, and typically don’t apply enough organic amendments to replace the organic matter that is lost each year. Typically, 40-80% of the carbon and nutrients in the aboveground biomass are exported off the farm in the form of crop harvests, which is generally not counterbalanced with regenerative soil management practices like cover cropping and organic amendment application. The results of this study (available in the Reports below) will enable New York State policy makers, agricultural professionals, and farmers to interpret soil health data within the context of soil type and cropping system (Figure 3).

Figure 2. Mean soil organic matter across soil texture groups (left, A). And mean soil organic matter across cropping systems on loam textured soils (right, B).
Figure 3. The Characterization of Soil Health in New York State Summary (left) and Technical Report (right) are now available.

For more information, please visit our website: newyorksoilhealth.org

NYS IPM Field Corn Pheromone Trapping Networks Helps Growers Avoid Potential Damage from Black Cutworm, True Armyworm and Western Bean Cutworm

Ken Wise and Jaime Cummings: NYS IPM Program

Black cutworm, true armyworm and western bean cutworm are all migratory pests of field corn. These three pests are all species of moths. Black cutworm and true armyworm are early season pests that migrate on weather fronts from the south and southwest of New York each year. Black cutworm will feed on small corn seedlings up to the sixth leaf stage. True armyworm can occur at very high populations and can destroy whole fields of corn. Western bean cutworm is a mid to late season moth species of field corn. The larvae will enter the ear of corn and can cause significant damage. To help combat these insect pests, the NYS IPM with funding from the NYS Corn and Soybean Association, developed a field corn pheromone trapping network.

The field corn pheromone trapping network is a group of extension educators, crop consultants and farmers who set up insect pheromone traps next to corn fields and monitor for the flight and abundance of the three pests. We started the network in 2010 monitoring a new invasive species, the western bean cutworm, and in the last two years we have included black cutworm and true armyworm. The network includes 24 people who monitor and report the number of moths they catch each week. In 2020, we had 20 black cutworm, 20 true armyworm and 63 western bean cutworm traps setup statewide. The purpose of the network is to identify areas of the state that have a high number of moth captures for the particular pest and to then alert growers to the potential damage that might occur. This helps the growers and crop consultants to start scouting fields for the pests. For black cutworm and true armyworm, we define an intense catch as 15 moths caught in a week. At this point, we can predict when larvae will be in the field by using specific degree day models. This is then communicated to the grower via field crops extension specialists across the state and publications like the Weekly NYS IPM Field Crops Pest Report, local extension crop alerts, and social media.

Western bean cutworm (WBC) monitoring occurs in the same manner as black cutworm and true armyworm. Once a trap reaches 100 moths caught in a week at a specific location, it is a good indication that the cornfields surrounding the trap should be monitored for WBC. WBC female moths almost exclusively only lays eggs on pre-tassel corn. The 100 moths caught per trap in a local area will prompt WBC alerts to growers in the local area. Northern NY is the epicenter of WBC flights. Some traps in Northern NY catch more than 1000 per week/trap, and in some cases 2000 moths.  Because of this network, we can help growers determine the peak flight of WBC and scout fields accordingly each year.

A second benefit of the monitoring is that we can collect data and follow the expansion of WBC and the flights of black cutworm and true armyworm from year to year. With two years of data for black cutworm and true armyworm, the data base is starting to grow. With WBC, we have 11 years of data outlining the expansion and peak flights of the moth.

There were 20 traps placed next to corn fields to monitor BCW and TAW in 2020. These 40 traps in total were monitored by 15 extension educators, crop consultants and growers from April through mid-June. We had some significant flights of BCW and TAW this year. The following maps illustrate the trap catch intensities from green to yellow to red:

map with dots indicating counts
Figure 1. NYS Black Cutworm Trap Counts for 2020
map of NYS and true armyworm counts
Figure 2. NYS True Armyworm Trap Counts for 2020

The flight of BCW and TAW started in April and extended to mid-June. There were reports of high levels of these pests in corn. In some cases, due to this network, growers were able to avoid damage by scouting and determining if BCW and TAW were above an economic threshold, to make treatment decisions.  Much of western NY and the mid- Hudson Valley had significant catches of black cutworm. There were significant catches of TAW in western and central NY.

graph of counts
Figure 3. Flight of True armyworm and black cutworm in NY 2020
Table of averages
Table 1. Average number of moths caught per trap

For WBC, there were 63 traps next to corn fields across NYS. We had 24 extension educators, crop consultants and growers monitoring WBC weekly from late June through late August. There were significant flights of moths, as illustrated in Figure 4, in Northern NY. The rest of the state had relatively low levels of WBC flights in 2020.  The major goal of this project during the season is to alert growers to the peak flight of the moths. At this time, the moths will lay eggs on pre-tassel corn. By knowing when peak flight is, we can alert growers to scout their corn fields for egg masses and small larvae. If they are over the economic threshold, then growers can treat a field before the larvae enter the ear of corn, because once the larvae enter the ear of corn, an insecticide application will have no effect on control.

map of NYS with dots indicating counts
Figure 4. NYS Western Bean Cutworm Count Totals 2020
bar graph showing peak flights from 2010 to 2020
Figure 5. Peak Flight of WBC by Year

The overall peak flight for WBC in 2020 was the earliest we have had since we started monitoring in 2010. When you break out the data and look at Northern NY compared the rest of the state, it shows the peak flight in NNY was the week of July 25th, but in the rest of the state it was a week earlier.  The average number of moths caught per trap in 2020 was down a little from 2017 and 2019, but about the same as 2018.

graph showing how much higher the counts in northern NY are
Figure 6. Peak flight in Northern NY vs the rest of the state
graph of moths caught from 2011 to 2020
Figure 7. Average number of moths caught per trap for WBC each year
graph of moths caught in NNY
Figure 8. Average number of moths caught per trap in Northern NY vs the Rest of NY

If you look at the data from 2017 to 2020, the average trap counts were much higher in Northern NY compared to the rest of the state. The highest risk of damage by WBC to grain corn is in northern NY.

As part of the project, we survey those who were involved regarding the benefits and impacts of the field corn pheromone trapping network. Of those who responded to the survey, 93% stated that monitoring for black cutworm, true armyworm and western bean cutworm were beneficial to them or their growers.

pie chart
Figure 9. The benefit of the field corn pheromone trapping network.

Most survey respondents also indicated they used the information from the trapping network to alert their growers to the potential damage from these insect pests. Many of these use their local weekly newsletter, but many made personal contacts with growers and helped determine if fields were at an economic threshold.

pie chart
Figure 10. Alerting growers to the potential damage from pests.

Multiyear monitoring, such as this corn pest network, provide invaluable data on the trends of infestations so that NY farmers can proactively scout for these pests and make appropriate management decisions.  We hope to continue these surveys in future years, and potentially expand the BCW and TAW networks.  We thank all collaborators for their time and efforts, and NYCSGA for the financial support to continue this project.

Double-Cropping with Forage Sorghum and Forage Triticale in New York: Best Timing for Sorghum Harvest and Triticale Planting

Sarah E. Lyonsa*, Quirine M. Ketteringsa, Greg Godwina, Jerome H. Cherneyb, Debbie J. Cherneyc, John J. Meisingerd and Thomas F. Kilcere

aNutrient Management Spear Program, Department of Animal Science, Cornell University, Ithaca, NY, bSoil and Crop Sciences Section of the School of Integrative Plant Science, Cornell University, Ithaca, NY, cDepartment of Animal Science, Cornell University, Ithaca, NY, dUSDA-ARS Beltsville Agricultural Research Center, Beltsville, MD (retired), eAdvanced Agricultural Systems, LLC, Kinderhook, NY. *Current affiliation: Department of Crop and Soil Sciences, North Carolina State University, Raleigh, NC

Introduction

Double cropping with both warm- and cool-season forages in New York can have many benefits, including providing a source of forage yield in the spring potentially leading to greater total season yields than a monocrop system, increasing rotation diversity, and providing year-round soil cover. Winter cereals such as triticale are great options for double cropping in the northeast, as they overwinter and can produce high forage yields in the spring. Yet, depending on weather and growing season condition, a winter cereal crop harvested for forage can delay corn silage planting to mid-May or later. Sorghum is a potentially useful alternative to corn silage for double cropping rotations as sorghum can be planted later than corn. While it is possible to harvest forage sorghum earlier than the recommended soft dough growth stage without compromising yield (Lyons et al., 2019a), it was not known how sorghum harvest timing would impact total season yield of both forage crops in the rotation. Here we present the findings of a field trial to evaluate the impact of sorghum harvest timing on the combined yield of forage triticale and forage sorghum in a double cropping rotation.

Field Research

This double cropping study with forage sorghum (brachytic dwarf brown midrib variety ‘AF7102’) and forage triticale (‘Trical 815’) was conducted at the Musgrave Research Farm in Aurora, NY from October 2015 to June 2018. The study was initiated with triticale planting in mid-October, 2015. Each spring, the triticale received multiple rates of nitrogen (N) at dormancy break in mid- to late-April and was harvested in mid- to late-May at flag-leaf stage. Sorghum was planted between early and mid-June once the soil temperature stayed consistently above 60°F. Sorghum received either no N or 200 lbs N/acre at planting, and was harvested four times in the fall between early September and mid-October, approximately 2 weeks apart. Triticale was planted a day after sorghum harvest. Here we present the data from the plots that received 120 lbs N/acre for triticale and 200 lbs N/acre for sorghum, where N supply was not expected to limit yield of either crop.

Results

In 2016, sorghum yield was highest when harvested after mid-September (late-flower to early-milk growth stage or later), and the following triticale yield was highest when planted in mid-September (Figure 1). Because of the larger contribution that sorghum had, overall total season yield did not increase after the mid-September sorghum harvest and triticale planting date that year. In the second year of the study (fall 2017-spring 2018), sorghum yield was maximized at the last harvest date, and, as with the year before, triticale yielded highest when planted in mid-September. Total season yields were lower in the second year compared to the first year, most likely reflecting weather; fall 2016 was warmer and drier, while fall 2017 was cooler with higher rainfall. There were more growing degree days (GDDs) by mid-September 2016 than by the last harvest in mid-October 2017 (Figure 2).

yield bar chart
Figure 1. Total season yield for a double-crop rotation study with forage sorghum and triticale in central New York from 2016 to 2018. Triticale was planted the day after sorghum harvests in the fall. Triticale was harvested at the flag-leaf stage in May. Sorghum was fertilized with N at planting (200 lbs N/ac) and triticale was fertilized with N at dormancy break in the spring (120 lbs N/ac).
yield graph
Figure 2. Forage sorghum yield as related to growing degree days (GDDs) from 2016 to 2017. The GDDs were calculated by subtracting the lower threshold growing temperature for sorghum (10°C) from the average daily temperature (in °C). The average daily temperature was calculated by subtracting the minimum temperature from the maximum temperature and dividing by two: (Temperaturemax – Temperaturemin)/2. To convert from GDD in °C used here to GDD in °F, multiply by GDDs in °C by 1.8.

Conclusions and Implications

Forage double cropping can be both economically and environmentally beneficial in upstate New York. Sorghum, a crop well-adapted to warm and dry climates, planted in early or mid-June will likely reach maximum yields earlier in years with more GDD (by 1151 GDD in oC or 2072 GDD in oF in mid-September 2016 in this study) compared to years with fewer GDD (such as 2017 in this study). We recommend that sorghum grown in New York during warm, dry years can be harvested once ~1150 GDD (°C scale; 2070 GDD in oF scale) have accumulated. This can support both sorghum and triticale yields. If 1150 GDD have not accumulated by the soft-dough growth stage (cool, wet years), harvesting sorghum at soft dough is recommended to maximize total season yield.

Additional Resources

Full Citation

The information summarized here comes from a 2019 publication in the Agronomy Journal: Lyons, S.E., Q.M. Ketterings, G.S. Godwin, J.H. Cherney, D.J. Cherney, J.J. Meisinger, and T.F. Kilcer (2019). Double-cropping with forage sorghum and forage triticale in New York. Agronomy Journal 111:3374-3382. doi:10.2134/agronj2019.05.0386.

Acknowledgements

Cornell logo, NMSP logo, pro-dairy logoThis work was supported by Federal Formula Funds, and grants from the New York Farm Viability Institute (NYFVI) and Northeast Sustainable Agriculture Research and Education (NESARE). For questions about these results, contact Quirine M. Ketterings at 607-255-3061 or qmk2@cornell.edu, and/or visit the Cornell Nutrient Management Spear Program website at: http://nmsp.cals.cornell.edu/