Performing Department
Animal Science
Non Technical Summary
Alfalfa as a livestock feed has direct value in rations for a diversity of livestock. Alfalfa provides multiple ecosystem services, and is an important rotation crop for breaking insect pest, weed, and disease cycles. Alfalfa reduces soil erosion, captures nutrients from annual crop fields that can contaminate surface and ground water, and promotes soil carbon sequestration. The value of the N from alfalfa biological N fixation to annual crops represents a fertilizer saving of more than $80/acre.We now have a unique opportunity to enhance alfalfa use in livestock rations and to increase its presence on the agricultural landscape. The development of a new reduced-lignin alfalfa has potential to provide a higher digestibility feed that will increase its feeding value and profitability of its use in rations. A transgenic, reduced-lignin alfalfa, named HarvXtra and marketed by Forage Genetics International, contains about 12-18% less whole plant lignin than standard varieties. The new transgenic reduced-lignin alfalfa was produced by deactivating enzymes in the lignin synthesis pathway.Dairy cow feeding trials with this alfalfa forage in the ration showed increased milk production of 1.2 kg/cow/day compared to forage from conventional alfalfa. Lignin concentration is highly correlated with forage digestibility, such that relatively small changes in lignin concentration will significantly influence fiber digestibility. The greater the reduction in lignin, the greater the impact on fiber digestibility, therefore transgenic reduced-lignin alfalfa is expected to have the greatest impact on animal performance. This new technology needs to be evaluated under diverse harvest regimes designed to produce forage with yield and quality to meet producer goals, including systems with alfalfa in mixture with perennial grasses.Use of new reduced-lignin alfalfa varieties has potential to be very advantageous to growers. At any given maturity stage, reduced-lignin alfalfa will have greater cell wall digestibility and greater feeding value than conventional varieties. In addition, the new technology also provides growers management flexibility to delay harvest to a later stage of maturity. It provides a wider harvest window without loss of digestibility.Increasing diversity in cropping systems helps to balance profitability and environmental concerns. We propose to increase cropping systems diversity by diversification in time and with diversity in space. Throughout the northern and transition zone regions, alfalfa is frequently grown in binary mixture, and new grasses provide unique opportunities to increase use of alfalfa mixtures. For example, a survey of alfalfa acreage in New York State in 2014, determined that over 84% of the alfalfa acreage in NY is planted with a perennial grass, compared to many regions of the Midwest where alfalfa is primary grown in monoculture. Advantages of alfalfa-grass mixtures compared with alfalfa monocultures include:1) Reduced chance of alfalfa heaving and winter kill.2) Less concern over application of animal manures.3) Improved soil and water conservation.4) Maintain a full stand of forage for more years as the alfalfa component declines.5) Increased resistance to alfalfa insect pests.6) Faster drying of mixed alfalfa-grass forage in the field.7) Reduced bloat potential of grazed alfalfa.8) Reduced soil structure damage by grazing animals.9) Provide more balanced nutrition to livestock than a pure crop of either alfalfa or perennial grass.While regional seeding rate recommendations exist for establishment of desired proportions of alfalfa and grass in mixtures, often the outcome of mixed seedings is unpredictable. In addition, the proportion of alfalfa and grass in mixtures is dynamic and changes from season to season and year to year. However, estimating the alfalfa proportion of mixtures is essential for producers for harvesting at optimum forage quality and for researchers for evaluating results. While many producers recognize the importance of grass-alfalfa mixtures, determination of the proportion of grasses and alfalfa is challenging. Most mixed stands are variable, so visual estimation of composition or making collection of a representative sample for manual separation are both difficult.Knowing the alfalfa-grass proportion in a mixture is a critical factor influencing use of mixed stands because this proportion strongly affects neutral detergent fiber (NDF) concentration. Neutral detergent fiber is critical in formulating diets for lactating dairy cattle, and within a species, the NDF content is well related to the digestible NDF content. These are the primary reasons that we focus on evaluation of NDF as a basis for harvest. Maximum alfalfa height by itself has been shown to be an accurate method of estimating neutral detergent fiber (NDF) of pure alfalfa, and also NDF of alfalfa-grass mixtures, as long as alfalfa proportion is known. The NDF equation for alfalfa-grass mixtures is the cornerstone of the Alfalfa-Grass Evaluation System (AGES) for assessing alfalfa proportion and alfalfa quality by producers, which will be assessed by this proposed project. These equations are currently being evaluated at McGill University, Montreal, QC, to test their robustness. Optimum NDF concentrations for alfalfa and pure grass species have been established, and we can estimate optimum NDFD content based on NDF for spring growth.Forage properties, such as species composition and NDF content, can be evaluated nondestructively in alfalfa-grass stands. We have determined that it is possible to accurately estimate alfalfa proportion of alfalfa-grass mixtures in the field, using digital image analysis. Multiple cameras, including Android and iPhones cameras, were used to collect images. Local binary patterns (LBP) applied to pixel tiles is proving to be successful.Preliminary model testing demonstrated potential for accurate results under a range of conditions. This photo assessment process is somewhat similar to that involved with facial recognition software. Photos taken with a cell phone will be able to accurately estimate alfalfa proportion. Using a smart phone or computer, the alfalfa proportion information can be combined with alfalfa maximum height information to immediately generate the current mixed stand NDF content. This information can be used to estimate the number of days it will take to reach optimum forage quality, because we know the average rate of decline in NDF and NDFD per day. Model development is now complete, with additional sampling, testing, and validation is occurring in 2015.Our planned work on evaluation of alfalfa-grass mixtures in diverse environments provides a unique opportunity to evaluate this new technology in diverse environments, and over multiple alfalfa-grass combinations.Use of new reduced-lignin high digestibility alfalfas is a foundational approach to increasing profitability, value, and use of alfalfa grown in pure stands (monoculture) and mixture with improved quality perennial grasses. Validation of a method to determine alfalfa proportion in mixed stands will allow both researchers and alfalfa producers to accurately evaluate this crucial parameter for mixtures. Direct beneficiaries of this research will include livestock farmers feeding alfalfa and alfalfa-grass mixtures, hay producers, and hay marketers. Greater acreage of alfalfa in monoculture and mixtures will benefit all citizens from improved water quality and healthier agroecosystems.
Animal Health Component
50%
Research Effort Categories
Basic
10%
Applied
50%
Developmental
40%
Goals / Objectives
Project ObjectivesObjective 1: We will evaluate forage yield and forage quality of reduced-lignin alfalfa in monoculture and in binary stands when subject to two harvest regimes focused on forage yield or quality.Experimental design: Randomized complete block with treatments in a split-split plot arrangements with four replicates. Whole plot Methods: Atwo year (seeding plus first production year) experiment is proposed from 2015-2017 at Cornell University Caldwell Field research farm, Univ. of Minnesota Research and Outreach Center, Rosemount, and Univ. of Kentucky Spindletop research farm. A third year harvest year is planned, but not included for funding in this proposal. Plots will be established in April or early May of 2016 by broadcasting inoculated seed and cultipacking or seeding with a plot drill into a prepared seedbed. Alfalfa monocultures will be seeded at 16.8 kg pure live seed/ha and alfalfa in mixture will be seeded at 11.2 kg/ha. Grasses will be seeded at approximately 6 kg/ha, with all three grasses seeded at the same number of pure live seeds/ha. Subplot size will be 1.8 x 6.1 m. Weeds in monoculture will be controlled using a post-emergent herbicide applied according to herbicide label. We will scout for insects known to be detrimental to alfalfa yield and quality and apply appropriate insecticides.Alfalfa harvest managements will be applied beginning in the seeding year when alfalfa reaches the designated stages of maturity but will conclude by early September at all locations. They will be applied again beginning in the spring in the year following seeding. No fall cutting will occur either year.?Alfalfa proportion in binary mixtures will be determined using techniques described under Objective 2. Forage yield will be measured at each harvest in the seeding year and year following seeding by harvesting a 0.9 by 5.5 m area in each plot to a 5 cm height. A 1 kg subsample of standing forage will be collected, dried, and yield expressed on a dry matter basis. Forage quality will be measured by manually taking a sample from 0.2 m2 from standing forage at time of plot harvest and drying at 60o C for 3 days. Samples will be taken in the seeding and year following seeding. Binary mixtures will be separated in alfalfa and grass components, and analyzed separately. Analysis will be assessed on the subsample by determination of crude protein, acid detergent fiber, NDF, NDFD, and mineral concentration (P, K, Ca, Mg) using a combination of near infrared reflectance spectroscopy (NIRS)(Sheaffer et al., 1998) and standard laboratory chemistry for calibration. Using forage quality variables, we will calculate the RFQ (Relative Forage Quality) forage quality index.Alfalfa maturity at harvest will be quantified at each harvest using the mean stage by weight method (Kalu and Fick, 1983). Grass maturity at harvest will be quantified using a simplified staging system (Parsons et al., 2006a). Stand evaluation will be determined by counting plants in 0.2 m2 areas in the 4 weeks following seeding and in the fall of the seeding year and in the spring and fall in the year following seeding. Botanical composition of the monocultures and binary mixtures will be measured at each harvest by methods described in Objective 2. Plant foliar disease will be determined by visually rating percent defoliation of 10 randomly harvested stems will be measured from each plot immediately prior to each forage harvest. The primary foliar diseases will be identified by symptoms and/or pathogen isolation.Statistical and economic analysis: Analysis of variance using least squares will be used to determine significant differences in treatments. Treatments will be tested as fixed effects while blocks nested within locations will be tested as random effects. Statistical analysis will be done using program SAS or R.We will conduct a spreadsheet-model cost-benefit analysis for each treatment combination. We will determine the returns of each treatment using yield and forage quality data, and then subtract production costs and added costs to identify the system that maximizes profits. We will calculate the returns using variable return and input cost scenarios.Timeline: We are asking for funding for two years, from 2015 to 2017, however, we plan on harvesting this study in 2018. Field activities will be conducted in 2016 and 2017. Fall 2015: plots will be prepared and fertilized at all locations. Winter 2015: Final plot plans developed; seeds of all alfalfa and grass varieties will be obtained. Spring 2016: Planting of seeds. Summer and Fall 2016: Cutting treatments will be applied. Forage yield will be determined and forage quality samples collected. Plant populations will be determined. Fall and Winter 2016-2016: Analysis for forage quality and statistical analysis of seeding year data. Spring, Summer, 2017: Intensive harvest schedule applied over all plots, forage yield measured and forage quality samples collected, plant populations measured. Fall and Winter 2016-2017: Laboratory analysis for forage quality and combined 2-year statistical analysis of data.Objective 2: Validate a system (AGES: Alfalfa-Grass Evaluation System) for assessing alfalfa proportion of alfalfa-grass mixtures in Objective one, and also for assessing alfalfa proportion and alfalfa quality by producers, for optimum forage quality and effective management of stands.Samples (0.8 m diameter circle) of binary alfalfa-grass mixtures will be collected across NY State in 2016, after taking photos, and recording stand height information, and then separated into species components for analysis. A minimum of 100 samples will be collected for validation purposes. A range of grass species will be included in these samples. These samples will allow both the validation of the alfalfa proportion from photos software, and will allow further testing of our NDF prediction equations.Objective 3: Develop an extension education program to help educate all stakeholders about the production and management requirements for reduced-lignin alfalfa and alfalfa-grass mixtures and the quality and feeding benefits of this new trait, and also educate stakeholders about AGES.The Education and Outreach portion of this project is a cooperative partnership between state forage crop extension specialists in Minnesota, Kentucky, and New York. Together, these organizations will provide a comprehensive education and outreach effort that will be available to a diverse group of stakeholders: (i) farmers and crop advisors, (ii) extension educators and state agency personnel, (iii) the scientific community, and (iv) the general public.
Project Methods
Objective 1: We will evaluate forage yield and forage quality of reduced-lignin alfalfa in monoculture and in binary stands when subject to two harvest regimes focused on forage yield or quality.Locations: In spring 2016, we will established research in three unique environments: St. Paul, MN; Ithaca, NY; and Lexington KY. The soils will be fertilized to optimum levels of pH, P, K, and S based on state soil fertilization guidelines.Experimental design: Randomized complete block with treatments in a split-split plot arrangements with four replicates. Whole plot treatments include two cutting treatments based on alfalfa maturity that will be applied beginning in the establishment year and continuing in the year following seeding: a) cutting to maximize forage yield based on harvests at early flower; and b) cutting to maximize forage quality based on harvest at bud stage. Sub plot treatments will be: a) alfalfa grown in monoculture, and in binary mixture with three perennial grasses: b) meadow fescue, c) festulolium, and d) orchardgrass.Methods: A two year (seeding plus first production year) experiment is proposed from 2015-2017 at Cornell University Caldwell Field research farm, Univ. of Minnesota Research and Outreach Center, Rosemount, and Univ. of Kentucky Spindletop research farm. A third year harvest year is planned, but not included for funding in this proposal. Plots will be established in April or early May of 2016 by broadcasting inoculated seed and cultipacking or seeding with a plot drill into a prepared seedbed. Alfalfa monocultures will be seeded at 16.8 kg pure live seed/ha and alfalfa in mixture will be seeded at 11.2 kg/ha. Grasses will be seeded at approximately 6 kg/ha, with all three grasses seeded at the same number of pure live seeds/ha. Subplot size will be 1.8 x 6.1 m. Weeds in monoculture will be controlled using a post-emergent herbicide applied according to herbicide label. We will scout for insects known to be detrimental to alfalfa yield and quality and apply appropriate insecticides.Alfalfa harvest managements will be applied beginning in the seeding year when alfalfa reaches the designated stages of maturity but will conclude by early September at all locations. They will be applied again beginning in the spring in the year following seeding. No fall cutting will occur either year.Alfalfa proportion in binary mixtures will be determined using techniques described under Objective 2. Forage yield will be measured at each harvest in the seeding year and year following seeding by harvesting a 0.9 by 5.5 m area in each plot to a 5 cm height. A 1 kg subsample of standing forage will be collected, dried, and yield expressed on a dry matter basis. Forage quality will be measured by manually taking a sample from 0.2 m2 from standing forage at time of plot harvest and drying at 60o C for 3 days. Samples will be taken in the seeding and year following seeding. Binary mixtures will be separated in alfalfa and grass components, and analyzed separately. Analysis will be assessed on the subsample by determination of crude protein, acid detergent fiber, NDF, NDFD, and mineral concentration (P, K, Ca, Mg) using a combination of near infrared reflectance spectroscopy (NIRS) (Sheaffer et al., 1998) and standard laboratory chemistry for calibration. Using forage quality variables, we will calculate the RFQ (Relative Forage Quality) forage quality index.Alfalfa maturity at harvest will be quantified at each harvest using the mean stage by weight method (Kalu and Fick, 1983). Grass maturity at harvest will be quantified using a simplified staging system (Parsons et al., 2006a). Stand evaluation will be determined by counting plants in 0.2 m2 areas in the 4 weeks following seeding and in the fall of the seeding year and in the spring and fall in the year following seeding. Botanical composition of the monocultures and binary mixtures will be measured at each harvest by methods described in Objective 2. Plant foliar disease will be determined by visually rating percent defoliation of 10 randomly harvested stems will be measured from each plot immediately prior to each forage harvest. The primary foliar diseases will be identified by symptoms and/or pathogen isolation.Statistical and economic analysis: Analysis of variance using least squares will be used to determine significant differences in treatments. Treatments will be tested as fixed effects while blocks nested within locations will be tested as random effects. Statistical analysis will be done using program SAS or R.We will conduct a spreadsheet-model cost-benefit analysis for each treatment combination. We will determine the returns of each treatment using yield and forage quality data, and then subtract production costs and added costs to identify the system that maximizes profits. We will calculate the returns using variable return and input cost scenarios.Objective 2: Validate a system (AGES: Alfalfa-Grass Evaluation System) for assessing alfalfa proportion of alfalfa-grass mixtures in Objective one, and also for assessing alfalfa proportion and alfalfa quality by producers, for optimum forage quality and effective management of stands.Samples (0.8 m diameter circle) of binary alfalfa-grass mixtures will be collected across NY State in 2016, after taking photos, and recording stand height information, and then separated into species components for analysis. A minimum of 100 samples will be collected for validation purposes. A range of grass species will be included in these samples. These samples will allow both the validation of the alfalfa proportion from photos software, and will allow further testing of our NDF prediction equations.Prior to harvest of experiments in Objective 1, two photos will be taken of each binary mixture plot at all three locations. Photos will be used later to determine alfalfa proportion in binary mixtures, using the validated photo alfalfa proportion recognition program. Analysis of NDF of study samples also will be used to help validate the AGES system. We will develop cell phone apps for both Android and iPhones for the AGES system, combining the software estimation of alfalfa proportion from photos with the previously developed equations for predicting stand NDF of binary mixtures (currently available at www.forages.org).Objective 3: Develop an extension education program to help educate all stakeholders about the production and management requirements for reduced-lignin alfalfa and alfalfa-grass mixtures and the quality and feeding benefits of this new trait, and also educate stakeholders about AGES.The Education and Outreach portion of this project is a cooperative partnership between state forage crop extension specialists in Minnesota, Kentucky, and New York. Together, these organizations will provide a comprehensive education and outreach effort that will be available to a diverse group of stakeholders: (i) farmers and crop advisors, (ii) extension educators and state agency personnel, (iii) the scientific community, and (iv) the general public. Specific activities will include:Extension Meetings: Three summer field days and three winter workshops. These will occur the second year of the project and one will be held in each state. The field days and workshops will be advertised through multiple formats and on the following forage organizations websites and/or newsletters: National Alfalfa and Forage Alliance, Midwest Forage Association, American Forage and Grasslands Council, Kentucky Forage and Grassland Council, the Progressive Forage Grower magazine, and the New York, Minnesota, and Kentucky Extension Forage websites. This will encourage participation from all stakeholders in the three states and from surrounding states.