Author: mmh262

Value of Manure Calculator Cell Phone App Available Now

Juan Carlos Ramos Tanchez¹, Kirsten Workman¹𝄒², Carlos Irias¹, and Quirine M. Ketterings¹ 

Cornell University Nutrient Management Spear Program¹, PRO-DAIRY²

Introduction

Quantification of nutrients in manure is essential to ensure efficient resource management, maximize agricultural productivity, and minimize negative environmental impact. A Value of Manure Calculator cell phone app was developed to estimate the agronomic and economic fertilizer replacement value of manure. To use the app, users will need to enter (1) the percent solids, N, P, and K nutrient content from a recent manure analysis, (2) the implemented or planned manure application rate, (3) crop nutrient needs, and (4) fertilizer costs. The app will then return past and current N credits, P and K credits, the fertilizer replacement value of the manure. Once the land application cost per gallon of manure is added, the tool also calculates the land application cost per extra mile hauled and the break-even hauling distance and costs. The app uses manure N credits that are in line with Cornell’s Nitrogen Guidelines for Field Crops in New York (2023). If you are in another state, consult your local land grant university guidance for manure N credits.

Calculator Access 

The Value of Manure app can be accessed at Value of Manure Calculator (https://valueofmanure-nmsp.glideapp.io/) with any browser or by scanning the QR code to the right. Once opened, the user will see the opening page of the calculator (Figure 1 left). The front page shows, at the bottom of the screen, seven tabs: Lab Analyses; Past Application; Current Application; Crop Needs; Fertilizer Value; Hauling; and Results (Figure 1 right).

Two phone screens.
Figure 1. Value of Manure App main page showing the manure analyses tab (left) and the results page (right).

Calculator User’s Guide

Recently a User’s Guide explaining what the app does and how to use it, was released (Figure 2). The guide walks the user through the different taps and explains in detail the following topics:

  1. Entering a Manure Analysis
  2. Calculating Nitrogen Credits from Past Applications
  3. Calculating Current Year Manure Nutrient Credits
  4. Entering Crop Needs
  5. Entering Fertilizer Value
  6. Calculating Break-Even Hauling Distances and Costs
  7. Understanding the Results
  8. Signing in to Save Results
An image of the cover of the Value of Manure project calculator user's guide.
Figure 2. Value of Manure Calculator User’s Guide.

The Value of Manure Calculator User’s Guide can be accessed at the NMSP website by clicking on the following link: http://nmsp.cals.cornell.edu/publications/extension/ValueManure2025.pdf.

Additional resources

Acknowledgments

The original manure crediting system was developed based on many years of field research under the leadership of S.D. Klausner, with contributions by D.J. Lathwell, D.R. Bouldin, and W.S. Reid of Cornell University, Department of Crop and Soil Sciences. This app was developed with financial support from the Northern New York Agricultural Development Program, the New York Agricultural Viability Institute, and USDA-NIFA. For questions about this project, 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/. 

 

 

New End-Of-Season Assessment Tool for Nitrogen Management of Corn Silage

Agustin J. Olivo1, Olivia F. Godber1, Kirsten Workman1,2, Karl J. Czymmek1,2, Kristan F. Reed1, Daryl V. Nydam3, Quirine M. Ketterings1

1Department of Animal Science, 2PRO-DAIRY, 3Department of Public and Ecosystem Health Cornell University, Ithaca, NY United States 

Introduction

            Effective nitrogen (N) management is an essential aspect of productivity and sustainability of corn silage production for dairies. In New York (NY), end-of-season evaluations that consider indicators like N balance (N supply – N removal) and ratio of N removal to N supply can be implemented to assess nutrient use efficiency. Comparing these results with feasible outcomes can help farmers identify opportunities to refine N management over time, and support field experimentation through the NY adaptive N management process. To identify target values for these indicators, characteristics of 994 corn silage field observations across eight NY dairies, together with land grant university guidelines for N management were used to create the “Green Operational Outcomes Domain” (GOOD) assessment framework. The GOOD combines feasible target values for field-level N balances, N removal/N supply, and an indicator related to manure inorganic N utilization efficiency. Indicators were derived using the method outlined in Agronomy Factsheet 125.

Key findings

The GOOD was defined by a 50% minimum N removal/N supply and a 142 lbs/acre maximum balance

A line graph depicting N balances and the "Green Operational Outcomes Domain."
Fig. 1. Feasible outcome values for maximum tolerable N balance and minimum N removal/N supply that define the GOOD framework.

            The GOOD framework was defined by comparing field N removal and available N supply (Fig. 1). Fields performing inside the GOOD (green area in Fig. 1) have an N removal/N supply that is at least 50%, and a field N balance of 142 lbs N/acre or less. The latter was defined based on the maximum balance that fields in the present dataset would display if managed according to land grant university guidelines. The GOOD was set to identify fields with large N balances and low efficiencies in the context of adaptive N management, without restricting application rates to less than annual P crop removal.

Average farm performance remained within the GOOD, but with large variability

            When considering actual farm management practices (“achieved” indicators) across all 994 fields, 66% of observations were within the GOOD and 34% outside. However, there was large variability across the eight farms evaluated.  The percentage of fields outside the GOOD ranged from only 1% for one farm (Fig. 2 left) and up to 54% for another farm (Fig. 2 right). The annual averages for achieved available N balance on all farms ranged between 4 and 192 lbs N/acre, and for N removal/available N supply between 38% and 95%.

Two line graphs describing the relationship between farm animal density and N balances.
Fig. 2. Nitrogen (N) removal and achieved available N supply as calculated from farm management data for corn silage fields of two different dairy farms. Percentages at the top of each graph represent the percentage of fields inside (green, left), and outside (red, right) the green operational outcomes domain (GOOD). Yellow diamonds represent the area-weighted average performance across all fields data was collected for in each farm.

Manure N use was efficient in this dataset, but with opportunities for refinement

            Forty-six percent of observations had spring manure injection or surface application followed by incorporation, whereas 32% received manure application but manure inorganic N contributions were zero (manure was either applied in fall, or in spring with no incorporation within five days). Twenty-six percent of observations were both within the GOOD and had manure inorganic N contributions larger than zero. This shows an overall efficient use of N for corn silage production. For 20% of the observations, manure injection or incorporation in the spring did take place, but the fields fell outside of the GOOD, reflecting opportunities to reallocate a portion of the nitrogen applied to other fields.

Additional graphical tools and indicators complement the GOOD framework well

A graph describing the relationships between yield and balances.
Fig. 3. Graphical tool displaying field achieved N balance vs corn silage yield, in the context of the feasible maximum tolerable N balance (142 lbs N/acre) and farm average yield. Q = quadrant.

            A series of additional graphical tools and numerical indicators were created to provide farms with more information to identify opportunities to refine N management in corn silage production. For example, one tool helps to identify fields with low yields and high N balances (Q3 in red, Fig. 3). These fields can represent the first target when attempting to refine N management in corn silage.

Conclusions

            The GOOD framework is introduced as an end-of-season assessment tool for farms to identify corn silage fields with large N balances and low N removal/N supply. This can be used in the context of the NY adaptive N management process, and/or to identify opportunities for N management refinement over time. On the latter, this study showed that the strategies with largest potential for refining N management and meeting the GOOD feasible targets included reducing N inputs, evaluating non-N yield barriers (e.g. drainage, pests) for fields with low yields and high balances, crediting N contributions from sod, and increasing manure N utilization efficiency (with spring injection or incorporation) and adjusting rates accordingly.

Full citation

            This article is summarized from our peer-reviewed publication: Olivo, A.J., O.F. Godber, K. Workman, K.J. Czymmek, K. Reed, D.V. Nydam, and Q.M. Ketterings (2024). Doing GOOD: defining a green operational outcomes domain for nitrogen use in NY corn silage production. Field Crops Research. https://doi.org/10.1016/j.fcr.2024.109676.

Acknowledgements

            We thank farmers and their certified crop advisors who shared farm data. This research was funded by a USDA-NIFA grant, funding from the Northern New York Agricultural Development Program (NNYADP), and contributions from the New York Corn Growers Association (NYCGA) managed by the New York Farm Viability Institute (NYFVI), and the Department of Animal Science, Cornell University. For questions about these results, contact Quirine M. Ketterings at qmk2@cornell.edu, and/or visit the Cornell Nutrient Management Spear Program website at: http://nmsp.cals.cornell.edu/.

Icons for the Nutrient Management Spear Program, Cornell University, Cornell CALS, and PRO-DAIRY

Manure nutrient variability during land application in four New York dairies

Aidan Villanueva1, Carlos Irias1, Juan Carlos Ramos Tanchez1, Kirsten Workman1,2, Quirine Ketterings1

1 Department of Animal Science, Cornell University, Ithaca, NY, United States; 2PRO-DAIRY, Department of Animal Science, Cornell University, Ithaca, NY, United States

Introduction

               Dairy manure is a rich source of essential plant nutrients, making it an excellent natural fertilizer. When applied correctly, it can enhance soil health, boost crop yields, and reduce reliance on synthetic fertilizers, thereby increasing agriculture’s sustainability and contributing to a more circular economy. Unlike inorganic fertilizers that have a guaranteed analysis, manure dry matter and nutrient content can vary, influenced by numerous factors such as dairy rations, type and amount of bedding, rainfall and wash water, manure storage systems and handling. Manure sampling and analyses will be essential in determining the potential value of the manure as a nutrient source. Our objectives were to assess the variability in manure dry matter (DM), nitrogen (N), phosphorus (P), and potassium (K) content across farms, across different storage units within a farm, and across time (hourly versus daily sampling), and to document the impact of agitation on DM and manure nutrient content. 

How was the data collected?

               Four New York dairy farms participated in this study. Manure samples were collected during land application in the spring of 2023 for all four farms and repeated in the spring of 2024 for one of the farms. Manure management and storage practices (Table 1) varied from farm to farm. Storages were sampled in the spring across days (“daily sampling”), and for the 2023 sampling we also took samples every two hours on selected days (“intense sampling”) to compare variability across hours and across days.

Table indicating manure management of different farms.

A manure spreader moving in a field on the left and a bucket of liquid manure on the right.
Fig. 1. Manure collection from a spreader.

               Manure samples were collected by filling a five-gallon bucket directly at the pump or the manure spreader (Figure 1). For each sampling round, three subsamples were taken and submitted for nutrient analyses to ensure outliers could be captured. Samples were analyzed for DM, total N, inorganic N, organic N, P, and K. Means, standard deviation, and coefficient of variation (CV) were determined to assess variability in the results across farms, storages, spreading events, and sampling intensity.

What was found?

               Storages varied greatly from farm to farm (results not shown) and within a farm (Figure 2). This highlights the importance of sampling each storage unit individually and maintaining accurate storage-to-field application records. 

A bar graph indicating mean nutrient content.
Fig. 2. Mean nutrient content at farm D for dry matter, total nitrogen, inorganic nitrogen, organic nitrogen phosphorus (P2O5), and potassium (K2O) in manure samples collected from four manure storage units (S1, S2, S3, and S4) in 2023. Error bars are standard deviations.

               Composition varied as the manure storage was emptied (results not shown). In general, across storages and farms, K content showed lower variability compared to P and N. In general, variability in N (total, organic, and inorganic) and P among hours within a day was much smaller than the variability from day to day (Figure 3). Hourly sampling often resulted in CVs below 13% while daily sampling showed CVs up to 34%. Because of the much lower CVs for hourly sampling, sampling over multiple days is recommended instead of sampling within a day.

Bar graph showing manure variation.
Fig. 3. Coefficient of variation for daily versus hourly sampling at three dairy farms for total nitrogen, phosphorus (P2O5), and potassium (K2O) in manure samples collected in 2023. # = Agitation, + = solid-liquid separation.

               Manure agitation completed the day before and on the day of application resulted in higher nutrient content, specifically for total N and P (Figure 3), reflecting settling of manure solids without agitation. Dry matter content was correlated with total N and P with lower N and P content for the more liquid upper layers in the storage. Potassium did not show much variability reflecting that K is predominantly found in the liquid fraction of the manure. These results show the benefits of consistent agitation to ensure a greater homogeneity over time as manure is land applied.

Bar graph indicating the impact of agitation.
Fig. 4. Impact of agitation the day before land application, during land application, and no agitation on manure mean nutrient content at farm B24 for dry matter, total nitrogen, inorganic nitrogen, organic nitrogen, phosphorus (P2O5), and potassium (K2O).

Conclusions

               Manure nutrient composition and variability differed across farms and across storage units on the same farm. Variability was also present over time as storages were emptied, although there was little variability between samples taken just a few hours apart (same day sampling). Agitation helped reduce variability. We recommend sampling each storage unit separately, keeping storage-to-field application records, agitating storages where feasible prior to and during land application, sampling manure from pumps or spreaders during land application, and sampling every time a significant change in manure dry matter content is seen.

Additional Resources

Acknowledgements

               We thank Dairy Support Services as well as farmers and their certified crop advisors who worked with us to collect manure samples. This research was funded by a USDA-NIFA grant, funding from the Northern New York Agricultural Development Program (NNYADP), the New York Farm Viability Institute (NYFVI), New York State Department of Agriculture and Markets (NYSAGM) and Environmental Conservation (NYSDEC). For questions, contact Quirine M. Ketterings at qmk2@cornell.edu, and/or visit the Cornell Nutrient Management Spear Program website at: http://nmsp.cals.cornell.edu/.

Icons for the Nutrient Management Spear Program, Cornell University, Cornell CALS, and PRO-DAIRY

Enhancing nitrogen management in corn silage: insights from field-level nutrient use indicators

Agustin J. Olivo1, Kirsten Workman1,2, Quirine M. Ketterings1

1 Department of Animal Science, Cornell University, Ithaca, NY, United States; 2PRO-DAIRY, Department of Animal Science, Cornell University, Ithaca, NY, United States

Introduction

              Optimizing nitrogen (N) management in corn silage production can help improve farm profitability while reducing potential environmental impacts derived from N losses in dairy farms. One strategy to monitor and improve nutrient management at the field level is the calculation of end-of-season field balances, the difference between nutrients supplied to the crop, and what is removed with harvest. Ideal field-level N balances are positive, but not excessively large.

Fig. 1. Nitrogen pools considered for N supply and N uptake when calculating field-level N balances.

              To assess the use of field N balances as an evaluation tool, field-level N balances (N supply – N uptake) and associated N use indicators were derived for 994 field observations from eight NY dairy farms across NY. Available and total N balances per acre, which differed only in the fraction of manure N accounted for (plant-available N or total N), yield-scaled N balances, and N uptake/N supply were calculated (Fig. 1).

Key findings

Nitrogen use indicators varied widely

              The median balance across all fields was 99 lbs/acre for available N and 219 lbs/acre for total N. Excluding soil N contributions reduced these medians to 26 lbs/acre for available N and 145 lbs/acre for total N. Median N uptake/N supply were 0.60 (available N) and 0.41 (total N). Balances varied by farm, ranging from 41 to 145 lbs/acre for available N and from 126 to 338 lbs/acre for total N (Fig. 2).

Two bar graphs.
Fig. 2. Relative frequency distributions for available nitrogen (N) balances per ac (A), and total N balances per ac (B), for all observations across farms and years.

Nitrogen supply considerably affected N use indicators

              Nitrogen supply was a bigger driver for N use indicators than N uptake (Fig. 3), suggesting that decisions on N inputs influence N use indicators more than yield itself. Larger balances were associated with high N supply and low-yielding fields, indicating that for those fields factors other than N supply limited yield. These could be in-season factors that prevent a field from achieving its yield potential (such as extreme weather events and pest problems), or (semi) permanent limitations (such as shallow depth to bedrock, subsurface compaction, and drainage issues) not acknowledged in N application planning.

Manure-N availability impacted N use efficiency

              The database showed a wide range of manure and fertilizer N supply to fields. Available manure organic and inorganic N played the largest roles in explaining the variability of N use indicators, with available N balances increasing with an increase in manure N supply. The study showed a 0.2 unit decrease in fertilizer N application on average in corn fields, with a 1 unit increase in available N from manure. This suggests that manure is valued as an N source, but its N content is not credited to the full extent possible, resulting in larger N balances at the end of the season.

Scatter plot.
Fig. 3. Available nitrogen (N) balances per acre, as related to N uptake and available N supply. Each data point represents a field*year observation in the database.

Sod-N crediting impacted N use efficiency

              First year corn fields showed reduced fertilizer and manure N applications than 2nd through 4th year fields (Fig. 4). Average available N balances (black dots in Fig. 4) for 1st year corn were, however, slightly larger than for fields with no sod N credits, suggesting opportunities for further reductions in nutrient allocation to 1st year corn.

A bar graph.
Fig. 4. Area-weighted average available nitrogen (N) from fertilizer and manure applications (colored bars), across all farms and years and for different stages of the crop rotation. Blue numbers (line one) on top of the graph represent number of observations in each category, and green numbers (line two), the area-weighted average N credits from sod for observations in each rotation stage. Black bolded numbers on top of each bar represent the sum of the area-weighted average available N from fertilizer and manure. COS1, COS2, COS3 = first, second and third crop year of corn silage after sod.

Farm animal density was associated with N use indicators

              At the whole-farm level, N balances per acre were positively related to animal density (animal units per acre) and impacted by farm crop rotations and within-farm allocation of manure N (Fig. 5).

Fig. 5. Relationship between farm animal density and (A) area-weighted farm averages for available nitrogen (N) balance, and (B) total N balance. Dotted horizontal gray lines represent the area-weighted average for each dependent variable across farms and years. AU = animal unit = 1,000 lbs of live animal weight.

Conclusions

              Nitrogen supply impacted N balance indicators more than N uptake (yield) and N balances tended to increase with larger farm animal density. Adjusting N supply based on realistically attainable yield, fully crediting manure and sod N contributions, improving manure inorganic N utilization efficiency, optimizing animal density, and/or exporting manure can aid in improving field N use indicators over time.

Full citation

              This article is summarized from our peer-reviewed publication: Olivo A.J., K. Workman, and Q.M. Ketterings (2024). Enhancing nitrogen management in corn silage: insights from field-level nutrient use indicators. Frontiers in Sustainable Food Systems 8. https://doi.org/10.3389/fsufs.2024.1385745.

Acknowledgements

              We thank farmers and their certified crop advisors who shared farm data. This research was funded by a USDA-NIFA grant, funding from the Northern New York Agricultural Development Program (NNYADP), and contributions from the New York Corn Growers Association (NYCGA) managed by the New York Farm Viability Institute (NYFVI), and the Department of Animal Science, Cornell University. For questions about these results, contact Quirine M. Ketterings at qmk2@cornell.edu, and/or visit the Cornell Nutrient Management Spear Program website at: http://nmsp.cals.cornell.edu/.

Characterization of phosphorus balances in corn silage fields from eight New York dairies

Agustin J. Olivo1, Laura Klaiber2, Kirsten Workman1,3, Quirine M. Ketterings1

1 Department of Animal Science, Cornell University, Ithaca, NY, United States; 3William H Miner Agricultural Research Institute, Chazy, NY, United States; 3PRO-DAIRY, Department of Animal Science, Cornell University, Ithaca, NY, United States

Introduction

              Optimizing phosphorus (P) application in corn silage production systems to align with crop P requirements while sustaining soil test P (STP) levels can help mitigate environmental risks and enhance farm profitability. Nutrient balances (supply minus uptake) can be an effective strategy to monitor P management in fields (Fig. 1). Sustained negative P balances (uptake > supply) can lead to a reduction in STP and negative impacts on crop productivity over time. Conversely, regular nutrient applications beyond crop removal can lead to increases in STP, which may be desirable in the short term to raise low STP, but undesirable if continued once soils reach optimum levels.

A graph with two bars.
Fig. 1. Phosphorus (P) pools considered for P supply and P uptake when calculating field-level P balances.

              Data on P balances from 994 corn silage field observations across eight New York dairies were analyzed to characterize this metric and identify drivers that may point towards opportunities for improved management. Data on manure management practices that affect field P dynamics and nitrogen (N) availability for the crop were also evaluated, as well as the relationship between P balances and STP for four of the farms.

Key findings

Phosphorus balances were low, but with a wide range across farms and fields

              On average, P balances across all fields were low (median of 7 lbs/acre), partially reflecting reductions in P surpluses on NY dairy farms over the last two decades as farm nutrient management has improved. However, there was a wide range across farm averages (-10 to 27 lbs/acre) and individual fields (-48 to 122 lbs/acre) (Fig. 2).

Two bar graphs.
Fig. 2. Relative frequency distribution for phosphorus (P) balances per acre (A), and area-weighted average P balance per acre (B) for Farms 1-8 across all years analyzed in the study.

Manure P supply was the main driver of balances

              Phosphorus supply was a more relevant driver of balances than P removed with harvest. Manure was the main source of P for all farms (Fig. 3), and farm to farm differences explained the largest portion of the variability in P supply. Higher P supply across farms was associated with higher manure application rates (driven partially by farm animal density) and higher manure P content connected to higher P rations.

A bar graph.
Fig. 3. Area-weighted average P supply from fertilizer and manure in Farms 1-8 across all years analyzed in the present study.


Phosphorus was applied at higher rates to fields with adequate STP than to lower STP fields

A b
Fig. 4. Phosphorus (P) supply (A) and P balances per acre (B) for individual observations in the dataset across agronomic soil test P categories in Farms 1, 3, 4 and 5 for all years analyzed in the study. Numbers in the top row represent means for each category. Values with different letters are statistically different.

              Morgan-extracted STP levels varied across farms and fields, with averages of 9, 13, 22 and 22 lbs P/acre for Farms 1, 3, 4 and 5, respectively (the only ones analyzed in the study for Morgan-extracted STP). These values corresponded to sub-optimal (<9 lbs P/acre), optimal (9-19 lbs P/acre), and high (20-39 lbs P/acre) agronomic P levels, according to land-grant university guidelines. Across the entire database, P was applied at higher rates to fields with adequate STP levels, indicating potential opportunities to re-allocate P within farms (Fig. 4).

P-based manure applications could cover a large fraction of crop N requirements

              Under management practices currently implemented by the farms assessed in the study, application of manure at N-based rates to corn would lead to large P balances for all farms, if utilized, due to a mismatch between manure available N to P ratio and corn N to P ratio needs. Similarly, P-based applications would cover only 51% of corn N requirements, on average. Increasing the rate of spring manure injection/incorporation or in-season injection on these farms could cover an average of 66 to 85% of corn N requirements, respectively, illustrating the greater N value of manure when more is incorporated/injected.

Conclusions

Results across the dataset showed low P balances on average, reflecting continued efforts from farms to efficiently manage manure nutrients and limit use of fertilizer P. Farms with large P balances may improve their performance by optimizing diet formulation to lower P excretion, reducing animal density, and/or exporting manure to move excess P off-farm. The data also showed potential opportunities to better allocate P within farms, re-allocating P from high or very high testing fields to P deficient fields. Combining appropriate rates of manure and N fertilizer or implementing manure treatment technologies that conserve N during storage and/or remove P, could help reduce P overapplication with N-based manure use. Similarly, spring or in-season manure incorporation or injection at P-based rates could recover a larger fraction of manure N, enough to cover almost all corn N requirements in some cases.

Full citation

This article is summarized from our peer-reviewed publication: Olivo A.J., L. Klaiber, K. Workman, and Q.M. Ketterings (2024). Characterization of phosphorus balances in corn silage fields from eight New York dairies. Agronomy Journal. https://doi.org/10.1002/agj2.21710.

Acknowledgements

We thank farmers and their certified crop advisors who shared farm data. This research was funded by a USDA-NIFA grant, funding from the Northern New York Agricultural Development Program (NNYADP), and contributions from the New York Corn Growers Association (NYCGA) managed by the New York Farm Viability Institute (NYFVI), and the Department of Animal Science, Cornell University. For questions about these results, contact Quirine M. Ketterings at qmk2@cornell.edu, and/or visit the Cornell Nutrient Management Spear Program website at: http://nmsp.cals.cornell.edu/.

New York state, regional and county level nitrogen and phosphorus balances for harvested cropland

Olivia Godber1, Kirsten Workman1,2, Kristan Reed3, and Quirine Ketterings1

1Nutrient Management Spear Program, 2PRODAIRY, 3Department of Animal Science, Cornell University, Ithaca, NY 14853

Introduction

              New York (NY) state is one of five states that collectively produce more than 50% of the annual milk supply within the United States. The local environment allows farmers to integrate crop and livestock systems, facilitating cycling of manure nutrients back to cropland. Thus, dairy farming provides NY with benefits, opportunities, and challenges in terms of environmental sustainability and climate resiliency. Improved balancing of crop needs for nitrogen (N) and phosphorus (P) with supply from manure is key for a circular agricultural economy. The objectives of this study were to calculate and evaluate (1) regional and county level N and P balances of harvested cropland; and (2) the contribution of manure to a circular agricultural economy for NY. 

              Nutrient balances were calculated for 2017 (most recent USDA Census of Agriculture year at the time) as the difference in nutrient inputs through purchased fertilizer and recoverable manure, and nutrients removed in harvested crops. Atmospheric N deposition, legume N fixation, and manure nutrient losses during collection, transfer, storage, and treatment were also estimated.

Key Findings!

              The 2017 NY State P balance was 9 lbs P/acre. The N balance was between 35 and 85 lbs N/acre, depending on the proportion of legume cropland assumed to have received manure (Figure 1). 

2 bar graphs with a key.
Figure 1: Breakdown of the inputs and crop removal of (A) phosphorus (P), and (B) nitrogen (N) at the New York state level in 2017. Estimated N losses of manure N during storage through volatilization and denitrification are identified.

              For P balances at the regional level, a small range of 5 to 10 lbs P/acre was seen (Figure 2). Chemung County was the only county with a negative balance (-3 lbs P/acre).

Image of New York State sectioned off by region. Each region has a corresponding small bar graph indicating phosphorus input and crop phosphorus uptake. A few counties in gray are excluded.
Figure 2: Breakdown of phosphorus (P) inputs and crop P uptake at the regional level, and P balance at county and regional level for New York in 2017; counties in gray were excluded.

              For N balances at the regional level, a small range of N balances from 17 to 41 lbs N/acre was seen (Figure 3A) when balances were calculated assuming that manure and purchased fertilizer N were applied to all cropland, and no N fixation occurred. Under the assumption that no manure or purchased N fertilizer was applied to legume cropland, and additional N inputs were included as a result of N fixation on legume cropland, a higher but still small range in N balances from 60 to 94 lbs N/acre was seen (Figure 3B). Under both assumptions the balances were calculated before storage and application losses of N.

              Redistribution and application of manure to meet P-removal on only the non-legume cropland left a surplus of 3 lbs P/acre at the NY state level. Applying surplus manure to legume and non-legume cropland resulted in a slight, state-level, P deficit. In both scenarios, the large N deficit that cannot be met through legume N fixation alone indicates N fertilizer is required to meet crop needs under the reported yield and manure supply conditions. These results show NY’s ability to capitalize on the value of manure.

Two maps of the state of New York, sectioned off by region, with excluded counties colored in gray. Each map has small bar graphs corresponding with each region indicating the nitrogen input and crop uptake of nitrogen of the region. The map on top includes manure and purchased nitrogen being applied to all cropland, whereas the one on the bottom refers to non-legume cropland only. The maps are each purple.
Figure 3: Breakdown of nitrogen (N) inputs and crop N uptake at the regional level, and N balance at county and regional level for New York in 2017, assuming manure and purchased N was applied to (A) all cropland (assumes no legume N fixation) versus (B) non-legume cropland only (assumes legumes received N through fixation). Counties in gray were excluded.

              Manure has value to cropland beyond N and P and consideration of these factors at the field level, in combination with field management history and soil test results, could help to prioritize where manure should be applied, and where purchased N and P inputs are required. Development and adoption of advanced manure treatment, storage, and application practices, with consideration of how livestock feeding practices can influence manure characteristics, could all help to further improve the value of manure, improve balances, and increase circularity and sustainability of the agricultural sector in NY.

Next Steps?

              As updated manure excretion rates and the amount of nutrients lost during storage and application of manure become available, combined with an expected continuation in the upward trend of both cow numbers and milk production for NY, it will be important to continue assessments of nutrient balances and animal densities, and explore manure treatment options to allow for transport of manure nutrient throughout NY to avoid creating nutrient “hotspots” within the state. With the recent release of the 2022 USDA Census of Agriculture data, we aim to evaluate these scenarios in more detail for the 2022 state balances.

Full Citation

              This article is summarized from our peer-reviewed publication: Godber O.F., Workman K., Reed K., and Ketterings Q.M. (2024) New York state, regional and county level nitrogen and phosphorus balances for harvested cropland. Frontiers in Sustainability 5:1352296. https://www.frontiersin.org/journals/sustainability/articles/10.3389/frsus.2024.1352296/full.

Acknowledgements

              This research is funded primarily by a gift from Chobani, in addition to Federal Formula Funds and grants from the New York State Department of Agriculture and Markets (NYSAGM) and New York State Department of Environmental Conservation (NYDEC). For questions about these results, contact Quirine M. Ketterings at qmk2@cornell.edu, and/or visit the Cornell Nutrient Management Spear Program website at: http://nmsp.cals.cornell.edu/.