Technological Advancements

The development of science and technology-based management practices is key to realizing the maximum potential of resistant cultivars. We discuss the application of some of these technologies and practices which will help producers by better forecasting stressors, improving soil health, reducing chemicals and fertilizer use, and minimizing the environmental footprint.

Application of Sensor-based Technology to Reduce Fertilizer Use

Team Members:

• Brenda Tubana (Co-PD) - Louisiana State University Agricultural Center
• Eve Daphne Radam (Graduate Student) - Louisiana State University Agricultural Center

Year 1 Activities:

• Evaluation of Sensor-Based Nitrogen (SBN) Technology: Conducted trials in two production fields in Kaplan, Louisiana—one under rice-soybean rotation and another under rice-crawfish rotation. The treatments included SBN technology, farmer's standard practice at 150 lbs N/ac, and a nitrogen-rich strip at 200 lbs N/ac (Figure 16). The mid-season nitrogen application rate based on SBN (using NDVI readings) was 23 lbs N/ac for rice-soybean and 11 lbs N/ac for rice-crawfish, compared to 33 lbs N/ac with the farmer’s practice. The grain yield levels for SBN, farmer’s practice, and nitrogen-rich strip were 11,052, 8,473, and 9,862 lbs/ac, respectively, in rice-soybean rotation, and 5,524, 3,590, and 5,177 lbs/ac in rice-crawfish rotation, suggesting a productivity benefit with SBN technology.
• Silicon Addition for Soil Health and Yield: Replicated plots with silicate slag (7% silicon) were established to assess impacts on rice yield in both rotations. Grain yields were similar with and without silicon in the rice-soybean rotation (10,771 vs. 11,136 lbs/ac) and in the rice-crawfish rotation (8,127 vs. 6,783 lbs/ac). Samples were analyzed for yield components and silicon content in grain, straw, and soil.
• Greenhouse Study with SSB (Silica-Solubilizing Bacteria): Identified a GFP-tagged SSB strain from previous research, and initiated a greenhouse study in 2024 due to its GMO status. Collected rice soil samples across Louisiana to isolate additional SSB strains with high solubilizing potential for future field tests.

Year 2 Plan:

• Continue field trials with SBN technology, adding two new sites, and study silicate slag’s effect on rice productivity.
• Conduct a pot experiment using soil from the rice-soybean and rice-crawfish fields, including treatments with and without silicon and SSB.
• Begin the isolation and identification of additional SSB strains from collected soil samples.

Field showing the location of NDVI in the field (80 acres). Values are NDVI readings based on aerial images (A), graduate student Eve taking NDVI readings from the N-Rich strip (B), and students taking aerial images from NDVI maps (C).

Cover Crop Studies

Team Members:

• Jim Wang (Co-PD) - Louisiana State University Agricultural Center
• Krizzia Guardado (Graduate Student) - Louisiana State University Agricultural Center

Year 1 Activities:

• Objective: Improve soil health and rice productivity through cover crop implementation.
• Site Establishment: Planted cover crops at three Louisiana locations: Crowley LSU Rice Research Station (Acadia Parish) and Mamou Lando Hunt Farms (Evangeline Parish) on October 19, 2023, and Kinder Langley Farms (Allen Parish) on October 25, 2023 (Figure 17).
• Crowley Site: Planted Australian winter pea (49 lbs/A), cosaque black oat (15 lbs/A), sodbuster radish (3 lbs/A), and a mix of the three. Biomass samples were taken on February 15, 2024, followed by termination on February 20, 2024, using herbicides (40 oz/A cornerstone, 4 lbs/A glyphosate, and 16 oz/A 2,4-D with water conditioning and surfactant). Rice was planted on March 15, 2024.
• Mamou Site: Planted Australian winter pea (60 lbs/A), cosaque black oat (50 lbs/A), and hairy vetch (15 lbs/A), as well as a mix of the three. Biomass sampling was completed on February 23, 2024, and cover crops were terminated on February 27, 2024. Rice planting was delayed due to climate conditions.
• Kinder Site: Planted hairy vetch (30.4 lbs/A), Dixie Crimson clover (2.9 lbs/A), and a custom Kevin Mix (8 lbs/A) consisting of dwarf rape seeds, Pacific Gold mustard, and Kodiak brown mustard. Due to poor growth and stand establishment, the cover crop trial at Kinder was discontinued following evaluation on February 27, 2024. Plans to re-establish this site are set for next year.

Year 2 Plan:

• Establish a new cover crop site to further enhance soil health for sustainable rice production.
• Conduct nitrogen rate-cover crop interaction trials.
• Measure soil health parameters to assess correlations with rice productivity.

Cover crop in January (A), Cover crop after termination (B), and Rice crop in the same Crowley site in May 2024 (C).

Improving Insect Pest Resistance

Team Members:

• Mike Stout (Co-PD) - Louisiana State University Agricultural Center
• Blake Wilson (Co-PD) - Louisiana State University Agricultural Center
• Laila Santos (Graduate Student) - Louisiana State University Agricultural Center
• Danyal Khan (Graduate Student) - Louisiana State University Agricultural Center
• Christine Gambino (Graduate Student) - Louisiana State University Agricultural Center
• Jyoti Sharma (Graduate Student) - Louisiana State University Agricultural Center

Year 1 Activities:

• Varietal Resistance to Mexican Rice Borer (MRB): Analyzed data from 37 field experiments (2016-2021) in Louisiana to assess the resistance of commercial rice varieties to MRB. Results showed substantial variation in whitehead density among 16 common varieties, with PVL01 experiencing the highest infestations (7-fold greater) compared to CL152, Jefferson, and Jazzman. Medium-grain varieties had higher whitehead densities than long-grain varieties, and inbred varieties showed about double the whitehead density compared to hybrids. These findings support the integration of varietal resistance into a multi-tactic management program for rice stem borers.
• Volatile Emissions and Stink Bug Behavior: Initiated studies on volatile emissions from rice panicles at different maturation stages, aiming to understand how these odors attract rice stink bugs (Oebalus pugnax) shortly after rice heading. This research could lead to novel stink bug monitoring and management techniques.
• CSSL Population Screening: Evaluated two Chromosome Segment Substitution Line (CSSL) populations (125 lines) for resistance to both rice water weevil (RWW) and MRB in a replicated field experiment. Significant variation in pest susceptibility was observed, indicating potential sources of resistance.
• Insecticidal Seed Treatments: Trials examined seed treatment efficacy, revealing a 50% reduction in RWW and MRB infestations in May-planted rice compared to March plantings. In multi-year ratoon crop studies, insecticidal seed treatments and foliar applications provided minimal yield benefit, suggesting insect pests do not significantly limit ratoon crop yields.
• Role of Silicon in Defense Against Herbivores: Conducted field and greenhouse studies using mutant rice lines deficient in silicon uptake to investigate silicon’s role in defense against insect herbivores.
• Cover Crops for Insect Management: Established cover crop plots in two locations in Fall 2023 to study their potential impact on insect pest management in rice.

Year 2 Plan:

• Continue exploring resistant varieties as part of a multi-tactic pest management approach.
• Investigate the role of cover cropping in insect pest management.
• Advance stink bug monitoring and management methods, and refine seed treatments for RWW and MRB management.
• Repeat the evaluation of CSSL populations to confirm sources of resistance to both RWW and MRB, with two-year data analysis to follow.

Impact of Irrigation Strategy on Rice Water Weevil Infestation

Team Members:

• Nick Bateman (Co-PD) – University of Arkansas
• Jared Linn (Graduate Student) - University of Arkansas

Year 1 Activities:

• Irrigation Strategy and RWW Infestation: Conducted trials at the Pinetree Research Station to assess the effects of different irrigation strategies—Alternate Wetting and Drying (AWD) versus traditional Flooding—on rice water weevil (RWW) infestation across two planting dates. Results indicated a higher number of RWW larvae in AWD plots compared to flooded plots, with hybrid cultivars showing higher larval densities overall. Seed treatments were found to be equally effective under both irrigation strategies.

Year 2 Plan:

• Continue trials to further evaluate the impact of irrigation strategy and rice variety on RWW infestation, refining management recommendations based on these findings.

Sheath Blight Modelling Studies

Team Members:

• Felipe Dalla Lana (Co-PD) - Louisiana State University Agricultural Center
• Dulakhi Mohottige (Graduate Student) - Louisiana State University Agricultural Center

Year 1 Activities:

• Research Objective: Investigated the influence of weather on sheath blight development, alongside the validation and risk assessment of sheath blight models and meta-analyses of chemical control methods.
• Data Consolidation: Merged historical data from 1957 to 2023 within the rice pathology program into a comprehensive dataset, encompassing disease intensity, yield, and grain quality metrics.
• Quality Control: Implemented quality control protocols to enhance metadata for developing and validating risk assessment models and conducting meta-analyses.
• Field Trials: Conducted four trials involving 75 rice varieties at the LSU Rice Research Station to gather data for the independent validation of risk assessment models.
• Varietal Classification Protocol: Developed a novel protocol to classify varieties based on disease reactions, integrating the accuracy component of the breeder’s equation with multiple mixed models to ensure the elimination of low-accuracy studies and to leverage assessment stability.

Year 2 Plan:

• Complete data collection and further refine data quality control protocols.
• Conduct meta-analytic studies focusing on disease control and yield loss using historical data from chemical trials.
• Execute a systematic map to identify all existing prediction models for sheath blight

Biological Control Studies to Suppress Bacterial Panicle Blight

Team Members:

• Jong Hyun Ham (Co-PD) - Louisiana State University Agricultural Center
• John Ontoy (Graduate Student) - Louisiana State University Agricultural Center
• Jobelle Bruno (Graduate Student) - Louisiana State University Agricultural Center
• Jose Cortes (Postdoctoral Fellow) - Louisiana State University Agricultural Center
• Inderjit Barphaga (Research Associate) - Louisiana State University Agricultural Center

Year 1 Activities:

• Transcriptomic Analysis: Conducted the first transcriptomic analysis to explore the effects of NA2 seed treatment on rice defense responses to a virulent strain of Burkholderia glumae (336gr-1) in the susceptible variety CL111.
• Gene Identification: Identified key rice genes specifically induced by the NA2 seed treatment, which included genes related to stress response regulation and broad-sense resistance. Predicted functions of these genes encompassed heat shock proteins, secondary metabolites, plant growth hormones, and factors involved in cellular redox homeostasis. Primers were designed for several candidate genes to validate RNA-seq results using qRT-PCR.
• Field Data Collection: Obtained first-year field data on the phenotypes of the Bengal/Jupiter recombinant inbred line (RIL) population regarding NA2-mediated suppression of bacterial panicle blight (BPB). Conducted greenhouse tests with the same RIL population to confirm the phenotypic responses observed in the field.

Year 2 Plan:

• Continue RNA-seq analysis to compare host defense responses to NA2 and the virulent B. glumae strain (336gr-1) in the Jupiter variety (moderately resistant to BPB) and Bengal variety (susceptible to BPB). Validate RNA-seq results through qRT-PCR.
• Collect field data on the effects of NA2 seed treatment across different U.S. rice varieties.

Application of Digital Agriculture Technology

Team Members:

• Tri Setiyono (Co-PD) - Louisiana State University Agricultural Center
• Fagner Rontani (Research Scholar) - Louisiana State University Agricultural Center

Year 1 Activities:

• Focus on Digital Agriculture: This research component concentrated on applying digital agriculture technology to characterize nitrogen use efficiency (NUE) in rice through remote and proximal sensing techniques, aiming to improve soil health, reduce nitrogen fertilizer use, and minimize environmental impact. Instruments employed for data collection included the Matrice 300 RTK UAV, natural color sensor, multispectral sensor, EMLID RS2 RTK units, and active sensing Crop Circle ACS 430 DAS43X.
• Trial at Rice Research Station: Conducted a trial in 2023 at the Rice Research Station in Rayne, LA, involving eight rice varieties and six nitrogen rates. Data from the natural color sensor were utilized to create a canopy height map. UAV-derived plant height data collected on July 10, 2023, showed a strong correlation with manually measured plant height data collected at near maturity. This demonstrates the potential of UAV remote sensing for generating plant height data, including time series data throughout the growing season and assessing spatial variability in the field.
• Multispectral Remote Sensing Results: Multispectral remote sensing maps (Figure 24) indicated that nitrogen omission plots were easily identifiable on the maps from June 8 and July 10, showing significantly less green color compared to other plots. The nitrogen response curves for the eight varieties revealed substantial variations in response to nitrogen rates, with CLL18 being the most responsive and AddiJo the least responsive in terms of yield. The reliability of remote and proximal sensing techniques in characterizing rice crops' responses to nitrogen was confirmed.
• Digital Agriculture Approach Development: Developed a digital agriculture approach to evaluate crop stand density in the field using AI-driven image processing, initiating the process for spatial crop stand assessment. Also established a digital agriculture framework for UAV remote sensing data collection aimed at high-throughput rice phenotyping, with further data processing planned for the second year.

Year 2 Plan:

• Continue the application of digital agriculture technology to enhance soil health, decrease nitrogen fertilizer use, and reduce environmental footprint.
• Investigate the use of AI-driven image processing and UAV remote sensing for high-throughput rice phenotyping.
• Process the collected remote sensing data for high-throughput phenotyping.
• Gather key information about plot layout and relevant agronomic and yield data from project collaborators.

Natural color map developed using H2O sensor for the experiment research location for N x Var trials in 2023 at Rice Research Station in Rayne, LA. Data collection date: 10 July 2023.