What's Cropping Up? Blog

Articles from the bi-monthly Cornell Field Crops newsletter

March 31, 2017
by Cornell Field Crops
Comments Off on What’s Cropping Up? Volume 27 Number 2 – March/April 2017

What’s Cropping Up? Volume 27 Number 2 – March/April 2017


The full version of What’s Cropping Up? Volume 27 No. 2 is available as a downloadable PDF and on issuu.  Individual articles are available below:

March 28, 2017
by Cornell Field Crops
Comments Off on Utilizing Corn Silage Hybrid Trial Results

Utilizing Corn Silage Hybrid Trial Results

Joe Lawrence, Tom Overton, Allison Lawton, Margaret Smith
Department of Animal Science, PRO-DAIRY; Plant Breeding and Genetics

A number of independent Corn Silage Hybrid Testing Programs, including the New York (NY) Corn Silage Hybrid Trials, offer valuable information on hybrid performance. But what if the hybrids you’re looking at are not found in individual trials? Hybrids in the trials are a subset, and on the surface may seem limited in their usefulness. However, the results can offer a wealth of information beyond the ranking of participating hybrids.

In fact, just looking at the top performing hybrids from a single year, while interesting, has limited value. Trial data for an individual hybrid is most useful with multiple locations and multiple years to understand how the hybrid performs across a wide range of conditions. This level of data can be hard to come by in the independent trials but may be available from seed companies.

In the absence of data on a specific hybrid, independent trials offer the opportunity to study;

  • how participating hybrids performed relative to their peers at each location,
  • which characteristics, among the participating hybrids, resulted in the most consistent performance, and
  • the expected range in results for important values, such as starch content and fiber digestibility.

With this information, you are equipped to ask individual companies for data on these important characteristics and values in their hybrids. While the specific hybrid may not be in the trial, a company should have information on other hybrids that share the same lineage or have similar performance to a hybrid that exhibited desirable characteristics in the trials.

Comparing to the Location Mean
The mean for a location is the average value of the measured parameter (yield or % starch). Since several localized factors, such as weather and soil type, influence the performance of the hybrids at a particular location, studying the absolute values (yield per acre, % starch or fiber digestibility) is not suggested. It is much more helpful to study the trial mean and compare hybrid performance relative to this mean to gain a better understanding of how it performed under the conditions at that location.

Whole Plant Dry Matter (DM) Considerations
In any testing program, the goal is to harvest all hybrids as close to the same stage of maturity (whole plant DM) as possible. In practice it is recognized that there will be variation in DM at harvest. Yields are corrected to a uniform DM for reporting. They are generally reported at 35% DM. However, it is also important to acknowledge the effect of DM on forage quality. It is recommended to only compare the forage quality results of hybrids that are within three percentage points of DM to each other.

Impact of Location
When data for multiple locations within the same trial are available or data on the same hybrids grown under slightly different management in other testing programs are available, it can be very useful to understand the effects that weather patterns, planting dates, seeding rates and other differences can have on the hybrid. This insight helps to address questions regarding the ability of a hybrid to perform consistently across conditions or if there are specific conditions where it performs best that match the conditions typical of your farm. Again, utilizing company data in conjunction with other trials can be very powerful for this.

It is also important to note that differences in growing conditions does not just impact yield, it can have large impacts on forage quality. While we commonly look at important factors such as whole plant dry matter and starch content, the effect of growing conditions on fiber digestibility was very apparent.

Fiber Digestibility
In recent years several advances in ruminant nutrition have increased our understanding of fiber digestibility, how this drives how much a cow will eat and the implications on her potential to produce milk. The measurement of undigested neutral detergent fiber (uNDF) is being reported by more hybrid testing programs and was an integral piece of data in the new approach to predicting potential milk yields in the NY Corn Silage Testing Program.

Starting in 2016, the NY trials used new methods to evaluate the milk producing potential of corn silage. The Cornell Net Carbohydrate & Protein System (CNCPS) model was used to predict the expected milk yield (in pounds per day) of a typical, Northeastern high lactating ration with each of the participating corn hybrids entered into the same total ration. Again, the relative ranking of the hybrids is more useful than the absolute values, but this approach uses a much more in depth analysis to assess how each hybrid may perform in an actual ration compared to previous approaches. It is evident in the report how the uNDF content of each hybrid may affect the potential dry matter intake of the ration and the subsequent effect on projected milk yield.

Starch Content & Digestibility
Starch content is a popular number to look at and justifiably so. At the risk of excessive repetition, this is another case where it is critical to look at these values in the context of the location mean, rather than absolute values as growing conditions and stage of harvest (whole plant dry matter) can affect this value.

Starch digestibility is more challenging. We know this value changes as the silage ferments, and laboratories continue to refine their ability to accurately predict starch digestibility using NIR methods, compared to the more intensive wet chemistry laboratory testing methods. It is also recognized that results from green (unfermented) samples, as are often used in Hybrid Testing Programs, are less consistent. It is generally accepted that a hybrid with good starch digestibility before fermentation will remain incrementally better after fermentation when compared to a hybrid that starts with lower digestibility before fermentation. Inquiring with a company about their data is quite beneficial, especially if they have wet chemistry data on fermented samples. It is always best to compare results from the same laboratory. However, if the results available are from different labs, ask for data from multiple hybrids to establish the relative differences in like datasets.

Yield and Agronomic Characteristics
While yield often receives too much attention in silage hybrid selection, you do want strong hybrids that have a competitive yield and are able to handle potential stressors. Some of these stressors may be more broadly driven by weather, while others may be typical of the micro-climate you farm, such as soil drainage, air drainage (disease prevalence) or elevation driven temperature trends.

This is another instance where rather than focusing on actual yield numbers, pooling data from multiple locations and sources and matching this with weather data from those locations will help you understand if a hybrid’s performance is consistent across conditions or if it excels and falters in certain situations that may be applicable to your area.

Results for the 2016 NYS Corn Silage Hybrid Trials can be found at: http://scs.cals.cornell.edu/extension-outreach/field-crop-production/variety-trials#corn-silage


March 28, 2017
by Cornell Field Crops


Joseph Lawrence1, Thomas Overton1, Margaret Smith2, Michael Van Amburgh1, Allison Lawton1, Sherrie Norman2, Keith Payne2, Dan Fisher2
Department of Animal Science, PRO-DAIRY; 2Plant Breeding and Genetics

In 2016, we were pleased to be able to reinstate the corn silage hybrid testing program at Cornell. The reinstatement of the New York trials was made possible with support from dairy producers, participating seed companies, Cornell University, the New York Farm Viability Institute, and the Cornell University Agricultural Experiment Station.

Twenty-nine corn silage hybrids (ranging from 84 day to 107 day relative maturity [RM]) were tested at two locations in NY in 2016. Hybrids were planted at the Musgrave Research Farm in Aurora (Cayuga Co.) and at Greenwood Farms in Madrid (St. Lawrence Co.). Seed companies were invited to submit hybrids for both sites for a fee. The purpose of this trial is to provide unbiased, local data to aid in producers’ decision making and consultants’ recommendations.  Detailed results can be found in the full report at (https://scs.cals.cornell.edu/extension-outreach/field-crop-production/variety-trials#corn-silage). Here we will discuss the main points of the 2016 trials.

All hybrids were planted at 34,000 plants/acre. The Aurora site was planted on May 12th and the Madrid site was planted on May 17th. Hybrids were planted in a randomized complete block design, with 4 replications, by 5-day maturity groups.

The Aurora site was harvested on three dates, according to maturity group. Early (90-95 day) corn was harvested on August 29th, medium (96-100 day) corn was harvested on September 1st, and late (101-105 day) corn was harvested on September 7th. At the Madrid location, all maturity groups were harvested on September 13th. The goal was to harvest all hybrids at about 65% (±3%) moisture.

Overall growing degree day accumulation was above average across the state while rainfall was extremely variable.  Both locations in this trial were below average in total rainfall (Table 1) but the patterns in the rain events made significant differences in the crop’s performance.

A significant change to the program in 2016 was the way in which hybrids were evaluated for forage quality.  For each hybrid, the forage analysis results (four replicates) were applied to a typical New York higher corn silage-based diet utilizing the Cornell Net Carbohydrate and Protein System (CNCPS v. 6.5.5; Cornell University, Ithaca, NY) biology and dynamic model and were averaged by site. The diet was developed for a second lactation dairy cow to produce 100 pounds of milk per day with forage at ~60% of diet dry matter (DM) and corn silage ~70% of forage DM in a software platform (NDS Professional version, RUM&N Sas, Reggio Emilia, Italy), which utilizes the CNCPS biology.

This novel approach to hybrid evaluation allowed us to account for differences in dry matter intake (DMI) potential of the total ration based upon hybrid selection and is a more biologically robust representation compared to evaluating hybrids on a constant DMI basis.  The predictions made by the CNCPS biology were used to evaluate differences in intake potential and subsequent metabolizable energy (ME) and metabolizable protein (MP) allowable milk yield based upon the nutrient and digestibility characteristics of each hybrid. Only the ME allowable milk yield is reported as it was more limiting than MP allowable milk yield for all hybrids.

A season such as this provides an opportunity to evaluate hybrid performance under variable growing conditions. While more locations are always beneficial, the difference in growing conditions and performance at these two locations provided some valuable insight into hybrid performance.  Figures 1 and 2 identify hybrids that performed above average in both crop yield and milk yield (top right quadrant) at each location. The hybrids performing above average at both locations are more likely to maintain a high level of performance across varying growing conditions.

Due to very different growing conditions experienced at the two sites, there was a large difference in the undigested neutral detergent fiber (uNDF) overall mean values, which translated into large differences in the predicted milk yield when corrected for uNDF at the 240 hour time point (uNDF240). The predicted ME allowable milk yield on a DMI equivalent was not as variable as the predicted ME allowable milk yield on an uNDF240 equivalent. This would be expected when DMI of the total ration is allowed to vary to meet a constant uNDF240 intake. We also need to acknowledge that while this approach offers a sound method for comparing relative hybrid performance, the absolute differences in predicted milk yield are predicted values from the model and are likely greater than the actual differences in milk yield expected in a herd of cows.

Based on the overall mean for predicted milk yield on an uNDF240 equivalent, corn silages performed exceptionally better at the Aurora site than at the Madrid site. However, the overall mean corn silage yield, when adjusted to 65% moisture, was drastically lower at Aurora than at Madrid. Due to higher fiber digestibility content in the hybrids grown at Aurora, it is predicted that dairy cows will consume more feed compared to the feed produced at Madrid, as reflected in the adjusted total mixed ration (TMR) DMI. With lower yields and higher predicted DMI at Aurora, dairy farmers feeding corn silages grown under these environmental conditions are more likely to be constrained by inventory for the following year compared to farmers feeding corn silages grown at Madrid.

The locations of our trials underlined the highly variable rainfall patterns experienced across NY state in 2016 and highlighted how critical timing of rainfall can be, rather than solely total rainfall.

In general, the eastern part of NY state experienced adequate rainfall with amounts diminishing as you moved west across the state, though there were large variations within regions. Producers in areas with adequate rainfall reported average to well above average yields, while other areas ranged from below average yields to complete crop failure. As was the case at our Aurora location, August rains in some locations helped save the crop from complete failure, though it was clearly still below average.

The impact of weather patterns and growing conditions on key factors, notably fiber digestibility and starch, influencing forage quality and milk producing potential on these hybrids was very evident when comparing the differences in crop yield and predicted milk yield across the two trial locations (Figures 1 and 2).

Figure 1. Relationship between silage yield and milk production potential at Madrid, NY. Hybrids located in the top right quadrant were above the overall mean for both crop yield and milk production potential and are considered good performers. Hybrids located in the bottom left quadrant were below the mean for yield and milk production potential. Hybrids in the top left quadrant were below the mean for yield and above the mean for milk production potential and hybrids in the bottom right quadrant were above the mean for yield and below the mean for milk production potential. Hybrids that were above average for crop and milk yield at both locations are marked and noted in the legend.

Figure 2. Relationship between silage yield and milk production potential at Aurora, NY. Hybrids located in the top right quadrant were above the overall mean for crop yield and milk production potential and are considered good performers. Hybrids in the bottom left quadrant were below the mean for yield and milk production potential. Hybrids located in the top left quadrant were below the mean for yield and above the mean for milk production potential and hybrids located in the bottom right quadrant were above the mean for yield and below the mean for milk production potential. Hybrids that were above average for crop and milk yield at both locations are marked and noted in the legend.

Predicting milk yield with the use of the CNCPS model provides dairy farmers and dairy nutritionists in NY with a more applicable approach for evaluating different corn silage hybrids. The predicted ME allowable milk yield on an uNDF240 equivalent reflects how much DMI the cow might be able to consume based on rumen fill and passage rate. These results demonstrate how crucial it is to adjust rations based on the predicted DMI rather than replacing corn silages on a DM equivalent basis.


We thank the seed companies that participated in 2016 for their collaboration. We urge all seed companies to participate in our corn silage testing program in 2017 so we can provide the best information under New York growing conditions to our New York dairy producers.

We thank Greenwood Dairy for their ongoing collaboration and support of the program; Paul Stachowski and Jeff Stayton at the Cornell Musgrave Research Farm, Aurora for their efforts during field operations; Greg Godwin, Kitty O’Neill, and Mike Hunter for assistance at harvest and Buzz Burhans and Ermanno Melli for providing us with the NDS software and technical assistance. We appreciate the guidance of Dr. Bill Cox, Dr. Jerry Cherney, Phil Atkins, and Ken Paddock in implementing the 2016 trials.

Additional financial support was provided by New York Farm Viability Institute and the Cornell University Agricultural Experiment Station.

March 22, 2017
by Cornell Field Crops
Comments Off on Planting Date and N Availability Impact Fall N Uptake of Triticale

Planting Date and N Availability Impact Fall N Uptake of Triticale

Sarah E. Lyonsa, Quirine M. Ketteringsa, Greg Godwina, Jerome H. Cherneyb, Karl J. Czymmeka,c, and Tom Kilcera,d
Nutrient Management Spear Program, Department of Animal Science, Cornell University, Ithaca, NY, b Soil and Crop Sciences Section of the School of Integrative Plant Science, Cornell University, Ithaca, NY, c PRODAIRY, Department of Animal Science, Cornell University, Ithaca, NY, and d Advanced Agricultural Systems, LLC, Kinderhook, NY

Triticale planted as a double or cover crop after corn silage harvest in the fall can provide many benefits to forage rotations in the Northeast, including reduced risk of soil erosion over the winter months, enhanced soil organic matter, improved rotation diversity, and, if grown as a double crop, increased total season yields. In addition, triticale has the potential to take up readily available nutrients either left over from the previous crop or from fall-applied manure, reducing the potential for nutrient loss. The benefit of fall nutrient uptake will depend on how early the winter cereals are planted in the fall. To evaluate the impact of planting date and nitrogen (N) availability on the growth and N uptake of triticale, four trials were conducted from 2012-2014.

Trial Set-Up
The four trials were planted with triticale (King’s Agri-Seeds Trical 815 variety) from late August to early October in eastern NY (Valatie) and central NY (Varna). Each trial had two planting dates and, to create a range in soil nitrate availability, 5 N rates were applied at planting in the fall (0, 30, 60, 90, and 120 lbs N/acre). Triticale was planted at 1-inch seeding depth and 7.5-inch row spacing (120 lbs/acre seeding rate). In late November prior to frost, we sampled the above ground biomass and analyzed the biomass for carbon and nitrogen. The “Apparent N Recovery (ANR)” was also calculated for each trial to see how efficient the triticale was at recovering fall-applied N. The ANR is calculated by subtracting the total amount of N in the biomass when no N was applied from the amount of N in the biomass when N was applied, and dividing that value by the actual amount of N applied: ANR (%) = (Triticale NN rate – Triticale N0 N)/N rate. A higher ANR means more of the N that was applied was taken up by the triticale.

Triticale planted before September 20 had more biomass than plots planted after September 20. For the triticale planted after the 20th, there was no increase in biomass when N was added. However, when triticale was planted earlier, N addition resulted in increased growth (Figure 1a). Across all N rates, biomass ranged from 0.6 to 1.1 tons DM/acre and averaged 0.9 tons DM/acre when planted before September 20, and 0.2 to 0.3 tons DM/acre with an average of 0.2 tons DM/acre when planted after September 20. These results are consistent with earlier studies in New York (see Ort et al., 2013), where triticale planted prior to September 20 yielded, on average, 0.7 tons DM/acre above-ground biomass in the fall, versus 0.2 tons DM/acre with later plantings.

In all four trials, biomass and N uptake were linearly related, meaning that as biomass increased, so did N uptake (Figure 1B). Thus, as N addition for later plantings did not increase yield, it also did not increase N uptake. Across all N rates, N uptake ranged from 36 to 78 lbs N/acre and averaged 62 lbs N/acre for the triticale planted before September 20, and ranged from 16 to 20 lbs N/acre with an average of 19 lbs N/acre for triticale planted after September 20. For every ton of DM triticale biomass produced in the fall, approximately 70 lbs of N was taken up.

Figure 1: Above-ground fall biomass accumulation (A) and nitrogen uptake (B) of triticale at different planting dates and N rates averaged across four trials.

Figure 2: Apparent nitrogen recovery (ANR) of triticale at different planting dates and fall N fertilizer rates, averaged across four trials.

The apparent N recovery was greater for earlier plantings (Figure 2). This is related to increased biomass production for the earlier planting dates, which has a direct impact on N uptake capacity of the triticale. The ANR averaged 47% for triticale planted before September 20, and only 5% for triticale planted after September 20.

Conclusions and Implications
Winter cereals, like triticale, grown as double or cover crops can take up residual N as well as additional N applied at or close to planting but the amount of N taken up depends on planting date. Triticale in this study was able to accumulate 0.9 tons DM/acre and take up 62 lbs N/acre on average when planted before September 20, but only 0.2 tons DM/acre biomass and 19 lbs/acre of N on average when it was planted after September 20. Additional N did not influence biomass or N uptake if triticale was planted late, but when planted early biomass did increase with greater N availability showing the benefits of early seeding for utilizing end-of-season N or newly applied N from manure. Planting winter cereals like triticale can sequester N that could otherwise be lost as well as provide dairy farmers with an additional opportunity to apply manure while reducing the risk of N loss. More research is needed to determine more precise planting windows for optimal N utilization by winter cereals in the Northeast, as well as determining an upper limit to the amount of manure that can be applied in the fall if a winter cover or double crop is planted.

Ort, S.B., Q.M. Ketterings, K.J. Czymmek, G.S. Godwin, S.N. Swink, and S.K. Gami. 2013. Carbon and nitrogen uptake of cereal cover crops following corn silage. What’s Cropping Up? 23: 5-6. Available at: https://scs.cals.cornell.edu/extension-outreach/whats-cropping-up.

This work was supported by Federal Formula Funds, and grants from the Northern New York Agricultural Development Program (NNYADP), 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/



January 25, 2017
by Cornell Field Crops
Comments Off on Anatomy of a Rare Drought: Insights from New York Field Crop Farmers

Anatomy of a Rare Drought: Insights from New York Field Crop Farmers

Shannan Sweet and David Wolfe
School of Integrative Plant Science, Cornell University

Key Findings

  • The record-breaking 2016 drought affected farmers across New York State (NYS) with more severe effects in Western and Central NY than Eastern NY.
  • Crop loss estimates from a late summer survey of ~200 field crop farmers suggest that more than 70% of field crop and pasture acreage had losses greater than 30%, with some reporting nearly total crop failure.
  • Common suggestions from farmers on help they could use in dealing with future drought included better long-range weather forecasts, financial assistance to expand irrigation capacity, and more information on drought resistant crops.

An unusually low winter snow pack, followed by lower than average rainfall and higher than average temperatures during the 2016 growing season (NRCC) led to continuously worsening drought conditions throughout New York State, and record-breaking low stream flows in Western and Central NY by late July and August (Drought Monitor). New York (NY) farmers have asked if they should expect more dry summers like the one we had in 2016 in the future with climate change. The answer to that is we don’t entirely know. Climate scientists are fairly certain that the number of frost-free days will continue to increase and summers will be getting warmer, which will increase crop water demand (Horton et al. 2011; Walsh et al. 2014). Climate models are less reliable for predicting rainfall and snow, but most projections suggest that total annual precipitation will remain relatively stable in New York, with small decreases in summer months and possible increases in winter. Also, the recent trend of the rainfall we do get coming in heavy rainfall events (e.g. more than 2 inches in 48 hours) is likely to continue.This would suggest both flooding and drought will continue to challenge New York farmers, and it is possible that more severe short-term droughts in summer could increase in frequency. Given these projected impacts, we surveyed NY farmers throughout August and September (Drought Survey) so as to better understand how farmers were affected by the 2016 drought and if they are able to cope with drought risk. The survey was distributed online and in paper format with the help of Cornell Cooperative Extension and the Farm Bureau. Of the approximately 240 farmers that responded to the survey, 183 of those were field crop farmers from every county in Western NY, and several agricultural counties in Eastern NY (Fig. 1).

Fig. 1. Drought survey responses by county. New York State number of farms map (Source: 2012 USDA NASS, ESRI – 12-M249), where darker green colors indicate a greater number of farms. Red dots indicate counties where field crop farmers responded to the survey. The dotted line delineates two regions (WNY = Western NY and ENY = Eastern NY). Counties in WNY were those designated as “national disaster areas” due to the drought.


Drought Impact

Fig. 2. Percent of respondents that estimated field crop yield losses within certain percent ranges. Forages include hay, grasses, and alfalfa. Data is averaged across NY.

Across the state, farmer-estimated crop losses for forages, pasture, soybeans, field corn, and small grains were 41%, 42%, 33%, 31%, and 17%, respectively. Figure 2 illustrates that estimated losses of more than 30% were reported for many field crops, and some forage and soybean farms reported losses above 90%. When asked what most limited field crop farmers’ ability to maintain yields, 37% said limited water supply, 25% said inadequate irrigation equipment, and 16% said poor soil water holding capacity (data not shown). Of the 22% who reported that other factors most limited their ability to maintain yields, several mentioned: lack of time and labor, excessively hot temperatures and high solar radiation, and being completely unprepared for needing to irrigate. Additional comments from farmers related to the effect of the drought included statements about: extra costs associated with buying hay, and having to sell cattle due to an inability to keep them watered and fed. Several farmers indicated factors that helped them get through the drought, including: cover cropping, no-till farming, increased soil health, and improved grazing management. The drought impact was so severe in Western NY (WNY) that the USDA-Farm Service Agency (FSA) declared most counties in this region “natural disaster areas” in August of 2016, and eligible for some financial relief in the form of low-cost loans (FSA). The more severely drought stricken field crop farms in WNY reported higher crop loss compared to Eastern NY (ENY) (Table 1). A vast majority of field crop farmers in WNY estimated the overall economic impact to be “moderate’’ to “severe” and, though many farmers in ENY also felt a substantial economic blow, about half categorized the impacts as “minor” or a “nuisance” with almost no economic impact (Fig. 3).

Fig. 3. Field crop farmer’s rating of the economic impact of the drought.



Adaptive Capacity

Field crop farmers’ responses varied when asked what they might have done differently if they had known in advance how dry this summer would be (Fig. 4). Many (37%) selected the “other” category and included suggested changes related to increasing soil organic matter and water holding capacity (e.g. cover crops and no-till), changing hay cutting regimes and increasing rotational grazing, investing in other water resources, selling or slaughtering livestock, and many others. A few farmers said they would not have done anything different if the drought could have been anticipated.

Fig. 4. Production changes field crop famers would have made if the drought could have been anticipated.

Insights for extension educators, researchers and policy makers
When asked how organizations such as Cornell Cooperative Extension, university researchers or government and non-government agencies could help them cope with future drought risk, farmers expressed interest in knowing more about:

  • Drought resistant crop varieties
  • Irrigation development and planning
  • Improving soil quality and water retention, and water saving ideas
  • Pasture rotation, silvopasture, rotational grazing, and stockpiling forage
  • How to minimize the effect of drought
  • What pests and diseases are more (or less) prevalent during a drought
  • Dealing with mental stress related to drought and climate issues

In response to that same question, farmers said they wanted more:

  • Development of online tools and better long-range forecasting
  • On-farm courses and training, and educational materials about agriculture and drought
  • Financial assistance to cover drought losses
  • Inventory of vacant farmlands for potential use
  • Financial assistance for irrigation equipment and ponds, and for soil improvement and water management
  • Crop-specific crop insurance or discontinue crop insurance which encourages growing ill-suited crops
  • Rentable and leasable irrigation equipment, and cheaper county water for agricultural use
  • Cost sharing for: cover crops and no-till supplies, and for multi-purpose ponds

This project was funded by Cornell University’s Atkinson Center for a Sustainable Future and The Nature Conservancy. For more information contact Shannan Sweet: 126 Plant Science Bldg., Ithaca, NY 14853; 607 255 8641, sks289@cornell.edu.

References and Hyperlinks
Drought Monitor – http://droughtmonitor.unl.edu/
Drought Survey – https://dl.dropboxusercontent.com/u/27816/Survey_Drought_8-5-16%20(mail-in).pdf
FSA (Farm Service Agency) – http://www.fsa.usda.gov/news-room/emergency-designations/2016/ed_2016_0825_rel_0095
Horton R, Bader D, Tryhorn L et al. (2011). Ch. 1: Climate Risks. In: Responding to Climate Change in New York State: The ClimAID Integrated Assessment for Effective Climate Change Adaptation. New York Academy of Sciences. pp 217-254.
NRCC (Northeast Regional Climate Center) – http://www.nrcc.cornell.edu/regional/drought/drought.html
USDA (United States Department of Agriculture) – https://www.agcensus.usda.gov/Publications/2012/Online_Resources/Ag_Census_Web_Maps/
Walsh J, Wuebbles D, Hayhoe et al. (2014): Ch. 2: Our Changing Climate. In: Climate Change Impacts in the United States: The Third National Climate Assessment. U.S. Global Change Research Program, 19-67.




December 7, 2016
by Cornell Field Crops
Comments Off on What’s Cropping Up? – Volume 26 No. 6 – November/December Edition

What’s Cropping Up? – Volume 26 No. 6 – November/December Edition

The full version of What’s Cropping Up? Volume 26 No. 6 is available as a downloadable PDF and on issuu.  Individual articles are available below:


Follow this blog

Get a weekly email of all new posts.

Skip to toolbar