Non Technical Summary
Agriculture must adapt to threats from climate change, including variable precipitation and changes in weed pressure. This project examines the individual and combined effects of multiple, complementary agroecological practices: strategic manipulation of crop row orientation and spacing to maximize light interception by the crop; interseeding cover crops to increase species diversity and total photosynthesis; and the use of terminated cover crop mulches to conserve soil moisture and suppress weeds. This project will also utilize an extensive on-farmdataset of more than 400 site-years of geospatially referenced information across 28 US states to quantify the effects of crop row orientation on crop yield and other agronomically relevant variables. To quantify the effects of each of these agricultural practices alone and in conjunction with one another, we will conduct two multi-year field experiments. We will measure relevant short-term agronomic variables including yield, weeds, soil water, plant physiological responses, and carryover effects on the subsequent crop and soil health indicators. To gain a greater understanding of the potential mechanisms underlying the effects of light modulation on crops resulting from differing row orientations and spacing, we will measure photosynthetically active radiation, soil moisture, and temperature continuously. This project will illucidate general principles about the function, properties, and performance of agricultural production systems and investigate how multiple management components of agricultural production systems can be integrated to enhance soil-crop-atmospheric processes and agriculturalresilience to stressors including those exacerbated by climate change.

Classification

Knowledge Area (KA)	Subject of Investigation (SOI)	Field of Science (FOS)	Percent
102	2410	1070	100%

Knowledge Area
102 - Soil, Plant, Water, Nutrient Relationships;

Subject Of Investigation
2410 - Cross-commodity research--multiple crops;

Field Of Science
1070 - Ecology;

Goals / Objectives
The long-term goal of our proposed research is to increase the ability of US agriculture to withstand pressing threats posed by climate change and weeds by integrating multiple, complementary agroecological practices. These practices include strategic manipulation of row orientation and row spacing to modulate light interception; interseeding cover crops to increase species diversity and total photosynthesis; and the use of terminated cover crop mulches to conserve soil moisture and suppress weeds. Alone, each of these individual practices has potential to ameliorate some threats from weather extremes and weeds through different, complementary mechanisms. However, transformative benefits will come from combining practices to provide both short-term agronomic benefits and long-term improvements to soil health and resilience.The specific objectives of the proposed research are:Objective 1: Leverage the Precision Sustainable Agriculture Network dataset to quantify the relationships between row orientation, environmental variables, level of cover crop mulch, soil moisture, and crop yields for corn, soybeans, and cotton to determine the potential of row orientation as a climate adaptive practice.Objective 2: Quantify the individual, additive, and interactive effects of row orientation, row spacing, and cover crop mulch on relevant agronomic and environmental variables to gain a deeper understanding of the value of these practices in climate adaptation.Objective 3: Leverage an existing SARE-funded field experiment to further explore the effects of row orientation and interseeded cover crops on subsequent crop performance and soil health by extending the cropping sequence.?

Project Methods
Objective 1.The PSA database currently includes 400 site-years spanning 23 states, encompassing broad gradients in latitude, climate, and edaphic properties.A preliminary analysis of the 400 site-years included in the dataset indicates that there is sufficiently wide variability (and replication) in all row orientations, making it ideal for testing our overarching research questions about the relative importance of crop row orientation and its influence on our variables of interest.To analyze the effects of crop row orientation on cash crop yields we will use a generalized linear mixed modeling approach. Cash crop row orientation and cover crop mulch presence will be considered fixed effects, while possible random effects to control for will include precipitation, soil type, spatial blocking within the US (e.g., by state, county, and/or latitude), cover crop species, or accumulated solar radiation. Other models will be generated to investigate intermediate variables to support conclusions about differences in cash crop yield due to row orientation. Separate models will be generated for each crop. Because crops differ in the number of site-years available in the database (236 site-years for corn, 126 for soybean, and 38 for cotton) the nature and strength of our inferences about the effects of specific row orientations may vary by crop. Specifically, we expect our ability to draw inferences about row orientation effects across a wide range of row orientations will likely be highest for corn and lowest for cotton.Objective 2.A two-year field experiment will be established in two fields (one starting in year 1 of the project and one in year 2 of the project). The variables of interest include crop and cover crop/forage yields and quality, weed biomass and community composition, soil water, soil health indicators including microbial biomass, mineral associated organic matter (MAOM) and particulate associate organic matter (POM), and subsequent crop yields. Additionally, we will monitor light resource availability by measuring crop interception (PAR), and light quality below the crop canopy (red:far-red light ratio). We will measure the physiological responses of the crops to the treatment conditions by recording crop transpiration, stomatal conductance, and photosynthetic water use efficiency. The main crop will be silage corn. The experiment will be organized as a randomized complete block design with a split plot with four replications. Orientation will be the whole plot factor (necessitated by field layout), and "Treatment" will be the subplot factor. The following treatments will be planted in both N-S and E-W orientations: (1) a control with no cover crops and crops seeded with 76 cm row spacing, (2) an interseeded system where cover crops are interseed into corn with 76 cm row spacing, (3) a solar corridor system with interseeding, where crops are seeded in twin rows with 152 cm row spacing and a cover crop interseeded into corn, (4) a high residue system with crops seeded with 76 cm row spacing, (5) a high residue system with interseeded cover crops and 76 cm row spacing, and (6) a solar corridor system with high residue and interseeding.Agronomic management will follow standard practices for our region.Interseeded cover/forage crops will be a mixture of annual ryegrass, red clover, crimson clover, and forage radish, all species that have been identified through previous research as being relatively shade tolerant and suitable to interseeding.To investigate possible mechanisms of orientation and treatment differences with respect to light, we will install wireless HOBOnet PAR sensors in all replications of the N-S and E-W Treatments 5 & 6.To quantify soil water dynamics, we will install capacitance sensors to measure volumetric water content at 15, 30, and 45 cm depths every five minutes in N-S and E-W plots in Treatments 1 & 4.Additionally, we will install pendant temperature sensors 2 cm below the soil surface in N-S and E-W plots in the middle of the interrow space in all treatments. To assess if changes to the growing environment influence the growth and development of the crop species we will measure transpiration, stomatal conductance and photosynthetic water use efficiency with a portable photosynthesis system (CIRAS-3, PP Systems, Amesbury, MA).Corn will be harvested for silage and analyzed for forage quality including dry matter, crude protein, ADF, aNDF, NFC, RFV, TDN, NEI, NEm, NEg, ME, and DE. Interseeded cover crop and weeds biomass will be quantified in fall before the first hard frost and again in spring in a spatially explicit manner to account for position in the interrow; i.e., 0.1m2 of aboveground biomass from each individual row of cover crop will be harvested and separated to species before drying and weighing. A composite sample of cover crop tissue will be analyzed for C:N after drying. Anion exchange resin will be buried at 30 cm in each plot after crop harvest and removed in the spring prior to crop planting to quantify nitrate leaching losses over the winter.Objective 3.The current ROSCO experiment consists of a single cropping sequence of silage corn with and without interseeded cover crops. Corn was planted in 2023 and the following cover crop treatments were established in both N-S and E-W orientations: interseeded cover crop mix (annual ryegrass, red clover, crimson clover, forage radish); interseeded winter rye; post-harvest seeded winter rye; weedy control. Fertility and weed management of silage corn is as outlined in Objective 2. Response variables currently include silage yield and cover crop biomass (in fall and spring), soil moisture (not continuous), weed biomass, and limited PAR data (our limited funding through SARE does not permit us to conduct intensive, replicated monitoring of PAR). We propose to add an additional cropping sequence of a soybean crop following these treatments, with and without an interseeded cover crop. We will quantify the effects of row orientation on interseeded cover crops in soybeans, the carryover effects of the previous treatments on soybean yield, weeds, and soil health indicators including microbial biomass, MAOM, and POM.