Evaluating the impact of cover crop type and termination timing on soil nitrogen storage and nitrogen loss from fields

Commodities

Practices

As cover crops gain popularity in the Lower Rio Grande Valley
(LRGV), farmers in both irrigated and dryland systems encounter
additional challenges alongside existing issues soil as soil
moisture loss and lack of technology for proper cover crop
termination. Due to lesser water use and the potential to improve
soil nitrogen status, the two major limiting factors for growers
in LRGV, growers prefer legumes over non-legume species. Despite
the benefits of reduced weed pressure and soil erosion through
cover cropping, growers now grapple with a new issue, higher
nitrogen loss in legume cover cropped fields compared to fallow
fields. The unique climatic circumstances in the regions posed by
sub-tropical semi-arid conditions, distinct from other parts of
the country, necessitates a stie-specific information to
effectively implement cover cropping.  

The release rate of nitrogen from various cover crops is
influenced by their functional types, such as C3 vs C4 grasses
and legumes, as well as factors like soil microbial community and
background soil properties. To address this issue, we propose
incorporating grasses into the cover crop mix and closely
monitoring water usage, total nitrogen reserves in the soil, soil
microbial community dynamics, and background soil properties.
Building on previous research findings, we anticipate that the
inclusion of grasses—with their higher lignin content and C:N
ratios—has the potential to mitigate nitrous oxide (N2O)
emissions and augment soil nitrogen reserves for subsequent
commodity crops (Singh et al., 2020).

By consistently monitoring soil moisture levels, leaf nitrogen
content and plant stomatal conductance, we aim to estimate plant
water usage and identify optimal timings for cover crop
termination. The addition of grasses to legume cover crops is
expected to balance the C:N ratio in the soil, slowing the
decomposition process and reducing nitrogen release, making it
more available for subsequent crops while mitigating the release
of a potent greenhouse gas. Moreover, grasses serve as effective
nutrient scavengers, preventing the loss of residual nitrogen
from previous commodity crops. We believe that with the
evaluation of plant traits related to their growth, development,
and physiology we can develop a comprehensive cover crop
management plan tailored to the specific challenges faced by
growers in the LRGV.

This study will be conducted in an organic vegetable farm in
Edinburg Texas for two-year 2024 and 2025. In both years, at the
end of May (end of vegetable growing season), the 2-acre field
will be plowed and divided into 20 equal plots (each plot
approximately 20m x 15m in size) with a 1m buffer in between each
plot as shown in Figure 1. This experiment will have 4 cover crop
treatments: legume only, grass only, grass-legume mix (50:50),
and a fallow control each replicated 5 times. The cover crops
included in this study include grass: sudangrass
(Sorghum × drummondii) and legume:
sunn hemp (Crotalaria juncea). The seeds will be planted
at the recommended rate, the legumes will be treated with the
recommended rhizobia inoculum before planting. The edges will be
cultivated to manage weeds. The control plots will receive no
treatment allowing weeds to grow. Cover crops in half of each
treatment plot will be terminated mid-July before the sunn hemp
start flowering and the remaining half will be terminated after
sunn hemp produce flowers, during the third week of July
(approximate timeline) Cover crops will be terminated using a
flail mower and will be incorporated into the soil (as preferred
by the participating farm). 

Field data collection and analysis:

Soil samples will be collected from each treatment plot and soil
physical, chemical, and biological analysis will be performed
during the 2-year study period. From each treatment subplot, 5
random soil samples will be collected at 0-20cm depth using a 2.5
cm diameter soil probe pre and post-cover crops and after cash
crop establishment in the field.  The soil samples will be
thoroughly mixed and separated into two portions. One portion
will be placed in air-tight containers and shipped to the Ward
Laboratories  (https://www.wardlab.com/services/soil-health-analysis/)
for microbial community (PLFA) and soil health assessment. The
PLFA analysis will include the estimation of the living biomass
of different soil functional groups including total bacteria
(Gram + and Gram -), Total Fungi (AMF and saprophytes), Protozoa,
and undifferentiated biomass. Soil health assessment will include
soil micro- and macronutrients, water stable aggregates,
microbially active carbon, nitrogen release, nitrogen reserve.
The second portion of soil samples will be air-dried and analyzed
for soil moisture, soil organic matter, total carbon and nitrogen
in PI’s laboratory at UTRGV. Soil moisture in each of the
treatment plots will be recorded every week using a Soil Moisture
Meter. 

Stomatal conductance and chlorophyll fluorescence will be
measured weekly to document the ecophysiology of the two cover
crop types. Stomatal conductance and chlorophyll content will be
measured in the field using a LICOR Porometer/Fluorometer,
LI-600N. Cover crop leaf tissues will be collected every week
until termination, dried to constant weight, finely ground, and
analyzed for C: N ratio using a LECO 928 Series Macro
Determinator in PI’s laboratory. Cover crop biomass at the time
of termination from each treatment plot will be collected from
each treatment plot from randomly selected 1m x 1 m sub-plot. The
above-ground plant parts will be dried in an oven to constant
weight and weighed to estimate the total above-ground cover crop
biomass.

Data Analysis

All data will be tested for normality and normalized if
necessary. The selected soil parameters will be compared among
the different treatments done using a T-test.  Analysis of
variance will be done to compare the differences in properties
between different different treatments. Multivariate analysis
will be done to evaluate the association among different soil and
cover crop biomass variables. Repeated measures ANOVA will be
done to compare the C:N ratios in leaf tissue of the two cover
species collected every two weeks. All data will be analyzed
using R statistical software.