2017
The Quest of 100 Bushel Soybean: On-Farm Approach
Contributor/Checkoff:
Category:
Sustainable Production
Keywords:
Field management Nutrient managementSoil healthTillageYield trials
Lead Principal Investigator:
Ignacio Ciampitti, Kansas State University
Co-Principal Investigators:
Stewart R. Duncan, Kansas State University
Terry Griffin, Kansas State University
Xiaomao Lin, Kansas State University
Doug Shoup, Kansas State University
+3 More
Project Code:
1776
Brief Project Summary:

Research information was recently generated through a USB-funded project regarding best management practices to increase soybean production, but only as small-scale research plots. High-yield potential can be better understood when based on farmer information. Weather, soil, crop, and environmental components should be properly characterized to provide a platform and baseline of comparison across soybean fields. Plant growth rates and nutrient uptake should be characterized at the farm scale. Characterizing high-yielding soybean farmers and understanding soybean development would encourage other farmers to study the factors blocking production. Researchers will work with farmers to document and understand best management practices to increase soybean yields under varying environments.

Key Benefactors:
farmers, agronomists, extension specialists

Information And Results
Project Deliverables

The project can be dissected in FIVE major components:

1) Historical component: Soybean contest winners for yield will be identified as potential collaborators (at least 4 farmers across diverse regions). Historical soybean information (last 5 yrs) on high-yielding soybean systems will be recorded from these farmers in order to better understand interaction of production practices x weather x economic scenarios from the most recent years.

2) Baseline Information: Characterize all production practices including input usage, field operation timing, and other activities implemented by the farmer in the current growing season (1st year of the project).
Example of production practices potentially to be identified in a contest winner’s farmer including input usage, field operation timing, and other activities. Specific examples may include: 1) Planting date prior to May 10; 2) Narrow row spacing (15”-7.5”); 3) Seeding rates ranged from 130 to 160 thousand per acre; 4) Seed treatment; 5) Application of foliar fungicides/ insecticides when required (based on disease infestation and insect incidence, # insects per plant); 6) Apply nutrients, P, K, S, when soil testing is low.

3) Soybean Yield Dissection: Extensively characterize soil, weather, plant growth, nutrient uptake, and main yield limiting factors during the current growing season (1st yr of the project). For this objective, proper screening of field conditions is needed. One (1) acre of the field will be jointly selected (farmer and PI-collaborators) for identifying physiological, nutrient, and all yield limiting factors. Farmers will get compensated for the use of the land at the yield obtained in the best area of their field (e.g. 75 bushels per acre x $9/bu = $675). Several 500-sq ft areas will be collected at varying growth stages.

Plant measurements to be determined:
- Leaf Area Index (LAI, derived via a LiCOR machine), light interception, and
Chlorophyll (SPAD) readings will be taken at the same moment of the biomass sampling.
- Visual disease and insect ratings from bottom, middle, and top of soybean canopy. - Grain yield components – pod number, grain number per pod, and grain weight harvested from the non-destructive areas (where “plant traits” are determined).
- Nodulation measurements at multiple growth stages (number of nodules).
- Plant biomass [e.g. Early season –V5, R3 stage-] and dry mass will be calculated and samples will be prepared for nutrient testing (complete nutrient analysis).

On-farm field characterization of all four-soybean environments (Chris Bodenhausen, Muscotah; Andy Winsor, Perry; Justin Knopf, Salina; and Ron Ohlde, Morganville).

4) Outreach:
A multifaceted extension and outreach program will include participation from faculty in cooperation with grower organizations, and producers. Information from this study will be presented at extension activities and the topics tailored to each specific audience. Presenting in field days, production schools, summer tours, and grower-oriented meetings will be key-component of this proposal. The PI will collaborate with Area Agronomists, Kansas Soybean, and agriculture and natural resources extension agents to identify farmers for this project and the needs of local clientele. All the information produced from this study will be available via the utilization of diverse communication venues
(websites, social media, extension programming, radio, television interviews, and press).

Final Project Results

Update:
Summary:
Nowadays good agronomical practices demand the adoption of new technologies that deliver better resource efficiency. The objective of this study was to identify and work closely with high-yielding soybean farmers in order to implement Ag precision tools, in this case: satellite imagery. Fields were selected for the 2017 growing season. The study is based on working with the field variation and the selection of three productivity zones outlined according to normalized difference vegetation index (NDVI) values.

Introduction
Vast information about crop health and development can be obtained via characterization of the temporal and spatial variability in the field, for example with the utilization of satellite imagery. Satellite imagery may provide crucial information that could potentially influence the decision-making process related to all farming inputs such as fertilizer, seeding rate, genotype selection, and pesticide application, among others.
The main objectives of this study are to: 1) explore the potential use of satellite imagery to identify productivity zones and evaluate soybean development across the growing season at the on-farm scale, and 2) explore relationships between satellite imagery data and ground-truth based plant traits such as plant growth and final yield.

Procedure
Sites Description
Field sites were established for 2017. Agronomical practices were those suitable per site.
Determination of Productivity Zones
A map defining productivity zones will be elaborated with previous year data for NDVI obtained from satellite imagery.

Outcomes:
Reports were prepared and sent to farmers.

Attached is the final report for this growing season for your field and also a complementary report to show how we use the information and what kind of data we process, in this example, we didn’t find significant differences that mean we don’t have differences between the different row spacing treatments.

About your field:
The present report includes:
- Characterization of the soil type within your field (data gathered from SSURGO)
- Map of the field altitude with LIDAR images obtained with radars
- Maps of the changes in greenness of the crop along the growing season characterized by normalized difference vegetation index (NDVI*), utilizing satellite imagery data with different spatial resolution (Landsat 8-L8- with 30 m x30 m; Sentinel 2-S2- with 10 m x 10 m) throughout the cropping season.

View uploaded report PDF file

View uploaded report 2 PDF file

View uploaded report 3 PDF file

View uploaded report 4 PDF file

This project help identifying on-farm production practices that are blocking yield potential. This information is currently helping other farmers in the region to FINE-TUNE their management practices for closing yield gaps. All project outcomes will be disseminated in diverse research and extension communication outlets to better educate Kansas soybean producers and agri-business professionals in the use of best management practices for maximizing financial returns and preserve the land and water resources under their control. The main outcomes were already presented in the Kansas Soybean Schools for the winter of 2018.

The United Soybean Research Retention policy will display final reports with the project once completed but working files will be purged after three years. And financial information after seven years. All pertinent information is in the final report or if you want more information, please contact the project lead at your state soybean organization or principal investigator listed on the project.