Breeding high yielding forages with good nutritive values is difficult in semiarid and arid locations of the world. The goal of this study was to identify guar [Cyamopsis tetragonoloba (L.) Taub.] breeding lines with potential use as forages for the US southern Great Plains using additive main effect and multiplicative interaction (AMMI) analysis and AMMI stability values (ASV). Twenty six breeding lines and four commercial cultivars were evaluated at two locations during 2 years. Although no genotype had an ASV of 1 (best) for grain yield, biomass production, and the seven forage nutritive value traits, three genotypes had lower ASV than or equal to the commercial controls when averaged across all traits. Among many individual traits, several genotypes performed better than the commercial cultivars. For example, breeding line 25 had good ASV for biomass and seed yield production, whereas breeding line 8 had good acid detergent fiber, relative forage quality, and total digestible nutrients. The results of this study showed that the guar breeding lines have adequate adaptability, variability, and stability to create future high yielding guar varieties with good forage nutritive values.

Early and late leafspot diseases are major constraints in peanut production, causing up to 70% yield losses in combined occurrences. Phenotyping has focused mainly on disease incidence and severity with little attention on disease progression and component traits that determine overall resistance. This study distinguished resistant and susceptible genotypes based on disease progression and components of resistance. Ten peanut genotypes were evaluated under natural leafspot pressure at Nyankpala, Ghana, over two cropping seasons. The set included six genotypes derived from crosses between BC3F6 interspecific introgression lines and Spanish peanut genotypes and four released varieties. Disease incidence, severity, lesion number and diameter, and percentage of necrotic area were recorded to compute area under disease progress curve (AUDPC) and residence indices. Results revealed that leafspot disease progressed steadily among susceptible peanut genotypes as compared with the resistant genotypes. Susceptible genotypes exhibited higher lesion number, lesion diameter, and percentage necrotic area, which showed strong positive correlations with AUDPC-ELS, AUDPC-LLS, and AUDPC-DI. L076J had the highest resistance based on components of resistance index, whereas Nkatiesari had the highest level of resistance based on the disease progression index (DPI). Integrating both components into an overall resistance index (ORI) classified Nkatiesari and Sarinut-1 as resistant; L076J, L027B, and L010A1 as moderately resistant; L030, L046, and L104B as susceptible; and Sarinut-2 and Chinese as highly susceptible. These resistant genotypes provide valuable sources for leafspot management and peanut improvement in sub-Saharan Africa.

Global peanut production is constrained by the frequency and severity of drought. New insights into photosynthetic biophysical and biochemical limitations under water-deficit stress are important to enhance peanut photosynthetic efficiency and production. This study examines the combined effects of water deficit, genotype, and growth stage on peanut physiology. An experiment was conducted during three growing seasons (2020 – 2022) to evaluate peanut genotypes (AG18, C76-16, GA-09B, and Lariat) at three developmental stages: flowering/peg development (R2-stage), pod initiation/seed development (R4-stage), and pod filling/initiation of crop maturity (R7-stage). The study was carried out under well-watered and water-deficit conditions. We quantified the biophysical (stomatal conductance) and biochemical limitations [the maximum rate of carboxylation (Vc, max), rate of RuBP regeneration (Jmax), and photosynthetic electron transport rate (ETR)]. The drought-induced reduction in AN during the R2-stage stage was primarily attributed to a significant decrease in stomatal conductance (gs). In contrast, at the R7-stage, the reduction in AN was driven by limitations in the gs, Vc, max, and Jmax. Notably, at the R7-stage, genotypes C76-16 and Lariat showed higher gs, ETR, and Vc, max, contributing to increased AN and enhanced pod and kernel yield compared to AG18 and GA-09B. AN reduction was driven by the biophysical limitation at the R2-stage and a combination of biophysical and biochemical limitations at the R7-stage. Furthermore, physiological strategies such as maintaining higher stomatal conductance while reducing photosystem II damage, as shown by C76-16, could be an effective drought tolerance strategy for maintaining high pod yield.

IntroductionElevated atmospheric carbon dioxide [CO2] increases peanut carbon assimilation and productivity. However, the molecular basis of such responses is not well understood. We tested the hypothesis that maintaining high photosynthesis under long-term elevated [CO2] is associated with the shift in C metabolism gene expression regulation.MethodsWe used a field CO2 enrichment system to examine the effects of elevated [CO2] (ambient + 250 ppm) across different soil water availability and plant developmental stages on the molecular responses in a peanut runner-type genotype. Plants under both [CO2] treatments were grown in semiarid conditions. We evaluated a comparative leaf transcriptomic profile across three periodic water deficit/re-hydration (well-watered/recovery) cycles throughout the growing season using RNAseq analysis.ResultsOur results showed that the transcriptome responses were influenced by [CO2], water availability, and developmental stages. The traditional Mercator annotation analysis based on percentage total revealed that lipid metabolism, hormone biosynthesis, secondary metabolism, amino acid biosynthesis, and transport were the most regulated biological processes. However, our new approach based on the comparative relative percentage change per individual category across stages revealed new insights into the gene expression patterns of biological functional groups, highlighting the relevance of the C-related pathways regulated by elevated [CO2].DiscussionThe photosynthesis analysis showed that 1) The light reaction was the most upregulated pathway by elevated [CO2] during water stress, 2) Photorespiration was downregulated across all stages, 3) Sucrose synthesis genes were upregulated by elevated [CO2] before stress, 4) Starch synthesis genes were upregulated by elevated [CO2] under drought periods, and 5) CO2 regulation of sucrose and starch degradation was critical under drought periods. Our findings provide valuable insights into the molecular basis underlying the photosynthetic acclimation response to elevated [CO2] in peanuts.

Drought is a major environmental constraint limiting global peanut productivity. Wild peanut species, characterized by greater genetic diversity, represent valuable resources for improving drought resilience in cultivated peanut. However, the molecular mechanisms underpinning drought tolerance in wild peanut species remain largely unexplored. This study evaluated the drought tolerance of three wild-type peanut accessions from two different species, Arachis dardani GK12946, Arachis dardani V7215, and Arachis ipaënsis K30076. Physiological measurements such as fresh weight and dry weight revealed statistically non-significant differences between drought-stressed and well-watered conditions, indicating strong inherent drought tolerance. Transcriptome analysis revealed that 3272, 3648, and 1181 genes in leaf samples of A. dardani GK12946, A. dardani V7215, and A. ipaënsis K30076 were differentially expressed, respectively. In root samples, 3014, 3472, and 2033 genes were differentially expressed in the same accessions. Notably, differentially expressed genes (DEGs) and set intersection (Venn) analysis suggests A. dardani V7215 exhibited the highest number of DEGs (1155) uniquely expressed in leaves, and 899 DEGs uniquely expressed in roots, suggesting accession-specific gene expression. Gene Ontology enrichment revealed that upregulated genes were associated with abiotic stress responses, temperature stimulus, heat stress, and DNA-binding transcription factor activity. Co-expression network analysis using WGCNA identified key drought-responsive modules, enriched for GO terms like stress regulation, protein folding, as well as GST family amino acid metabolic processes. Overall, this study provides comprehensive insights into the molecular basis of drought tolerance in wild peanut accessions. Our findings establish a valuable resource for functional genomics and crop improvement under water-limited conditions.

The peanut seed coat acts as a physical and biochemical barrier against Aspergillus flavus infection; however, the nature of the inhibitory chemicals in the peanut seed coat in general is not known. This study identified and characterized peanut seed coat metabolites that inhibit A. flavus growth and aflatoxin contamination. Selected peanut accessions grown under well-watered and water-deficit conditions were assayed for A. flavus resistance, and seed coats were metabolically profiled using liquid chromatography mass spectrometry. Kyoto Encyclopedia of Genes and Genome phenylpropanoid pathway reference analysis resulted in the identification of several seed coat metabolic compounds, and ten selected metabolites were tested for inhibition of A. flavus growth and aflatoxin contamination. Radial growth bioassay demonstrated that 2,5-dihydroxybenzaldehyde inhibited A. flavus growth (98.7%) and reduced the aflatoxin contamination estimate from 994 to 1 mu g/kg. Scanning electron micrographs showed distorted hyphae and conidiophores in cultures of 2,5-dihydroxybenzaldehyde-treated A. flavus, indicating its potential use for field application as well as seed coat metabolic engineering.

The identification of informative molecular markers is useful for linkage mapping and can benefit genome-wide association studies by providing fine-scale information about sequence variations. However, high-throughput genotyping approaches are not cost-effective for labs that require frequent use, such as breeding programs that need to perform genotyping on large populations with hundreds of individuals. The number of single nucleotide polymorphism markers generated by those approaches can be far more than needed for most breeding programs; instead, breeders focus on the use of at most hundreds of polymorphic molecular markers for analysis. To help make use of molecular markers a routine tool for breeding programs, we aim to develop a cost-effective genotyping system by using the Tecan Allegro Targeted Resequencing V2 kit. This provides a customized probe design, which indicates that all the DNA fragments synthesized are known targets. SNPs obtained from previous peanut next-generation sequencing data were pre-filtered and selected as targets. These SNP targets were polymorphic among different tetraploid accessions and were selected to be distinguishable from paralogs. A total of 5154 probes were designed to detect 2770 SNP targets and were tested on 48 accessions, which include some closely related sister lines from a breeding population. The results indicated that genotyping by a targeted resequencing approach reduced the cost from around USD 28 (SNP chip and GBS) to USD 18 per sample, while providing polymorphic markers with accurate SNP calls. With this cost-effective genotyping platform, pre-selected SNP markers can be used effectively and routinely for more breeding programs.

'Tamrun OL18L' (Reg. no. CV-155, PI 703068) and 'Tamrun OL19' (Reg. no. CV-156, PI 703069) are high-yielding, high oleic, early-maturing runner-type peanut (Arachis hypogaea L. subsp. hypogaea) cultivars. Tamrun OL18L was derived from a cross between a high oleic runner cultivar, 'Tamrun OL02', and TxL017746, an early runner breeding line selection developed from a cross between PI 109839 and 'Florunner'. Tamrun OL19 was derived from a cross between a high oleic runner cultivar, 'Tamrun OL01', and TxL017746. Maturity of Tamrun OL18L was similar to 'Tamrun OL12', approximately 2 weeks earlier than 'Tamrun OL07'. Tamrun OL19 matured approximately 1 week earlier than Tamrun OL07 and 1 week later than Tamrun OL12. Grades of Tamrun OL18L and Tamrun OL19 were similar, intermediate numerically between but not statistically different from Tamrun OL07 and Tamrun OL12; by comparison, Tamrun OL12 had a significantly lower grade than Tamrun OL07. Grades of Tamrun OL18L and Tamrun OL19 were lower than 'Tamrun OL11' but were similar to 'Georgia-09B', 'FloRun 107,' and 'TUFRunner 511.' Yields were similar to Georgia-09B, FloRun 107, and TUFRunner 511 but were higher than 'Tamnut OL06' and Tamrun OL11. Tamrun OL18L had a larger seed than most cultivars tested, significantly larger than Tamrun OL12 and Tamnut OL06, but was similar in size to Tamrun OL07 and 'Webb'. No differences in flavor were noted between Tamrun OL18L, Tamrun OL19, and check cultivars. Tamrun OL18L and Tamrun OL19 are new high oleic runner peanut cultivars.Tamrun OL18L and Tamrun OL19 mature 1 to 2 weeks earlier than other runners.Earliness and high oleic oil are expected to give reduced chance for off-flavors.Both Tamrun OL18L and Tamrun OL19 have high yield and grades comparable to other cultivars.

Peanut (Arachis hypogaea L.) plants respond to drought stress through changes in morpho-physiological and agronomic characteristics that breeders can use to improve the drought tolerance of this crop. Although agronomic traits, such as plant height, lateral growth, and yield, are easily measured, they may have low heritability due to environmental dependencies, including the soil type and rainfall distribution. Morpho-physiological characteristics, which may have high heritability, allow for optimal genetic gain. However, they are challenging to measure accurately at the field scale, hindering the confident selection of drought-tolerant genotypes. To this end, aerial imagery collected from unmanned aerial vehicles (UAVs) may provide confident phenotyping of drought tolerance. We selected a subset of 28 accessions from the U.S. peanut mini-core germplasm collection for in-depth evaluation under well-watered (rainfed) and water-restricted conditions in 2018 and 2019. We measured morpho-physiological and agronomic characteristics manually and estimated them from aerially collected vegetation indices. The peanut genotype and water regime significantly (p < 0.05) affected all the plant characteristics (RCC, SLA, yield, etc.). Manual and aerial measurements correlated with r values ranging from 0.02 to 0.94 (p < 0.05), but aerially estimated traits had a higher broad sense heritability (H2) than manual measurements. In particular, CO2 assimilation, stomatal conductance, and transpiration rates were efficiently estimated (R2 ranging from 0.76 to 0.86) from the vegetation indices, indicating that UAVs can be used to phenotype drought tolerance for genetic gains in peanut plants.

Hemp (Cannabis sativa L. ssp. sativa) has a long history of domestication due to its versatile use. Recently, different sectors in the economy are investigating hemp cultivation to increase agronomic production and to limit delta-9-tetrahydrocannabinol (THC). Despite the rapid growth of hemp literature in recent years, it is still uncertain whether the knowledge gained from higher latitude regions is applicable to low latitude and tropical regions where hemp has not been grown traditionally. This review provides a comprehensive and updated survey of hemp agronomy, focusing on environmental and management factors influencing the growth and yield of hemp, methods of cannabinoids detection and quantification, and hemp breeding. This review suggests that some previous claims about hemp as a low input crop may not hold true in low-latitude regions. Additional research strategies, such as the integration of experimentation and modeling efforts, are encouraged to hasten new discoveries. Furthermore, to effectively increase the outputs of value products (cannabinoids, seeds, fiber and biomass, etc.) while limiting the THC level, new collaborations between hemp agronomists and economists may streamline the production process by increasing the efficiency of the total production system of hemp as a multifaceted crop.

'NemaTAM II' (Reg. no. CV-152, PI 699122) is a high-yielding, high-oleic fatty acid, runner-type peanut (Arachis hypogaea L. ssp. hypogaea var. hypogaea) cultivar with resistance to root-knot nematode (RKN). The cultivar was developed by the Texas A&M AgriLife Research peanut breeding program to provide growers with a nematode resistant replacement option for the former 'Webb' cultivar, which had excellent nematode resistance but also had a very large vine size that made harvest difficult for peanut farmers. It was tested under the experimental designation of Tx144342 and was released on 11 Jan. 2021. NemaTAM II maintains the resistance to RKN of Webb, has proven to yield equal to or better than Webb, and has higher grade potential. NemaTAM II has a shorter canopy than Webb, which leads to easier digging and inverting at harvest than its predecessor.

Peanut ( Arachis hypogaea L.) is an important crop grown around the world but lacks genetic resistance to many biotic and abiotic stresses. However, these traits can be found in the wild and exotic germplasm to which peanut is genetically related. The genus Arachis contains 83 described species, some of which are home to a reservoir of useful traits and that have served as a source of resistance with their movement into the cultivated peanut. There are several excellent examples of using exotic and wild germplasm to successfully to incorporate biotic resistance traits into cultivated peanut. It is also possible that some of the genetic resources could someday be used to further enhance peanut in unforeseen ways. In this article we present some examples of successful introgression and how these success stories have been achieved.

At the cellular level, membrane damage is a fundamental cause of yield loss at high temperatures (HT). We report our investigations on a subset of a peanut (Arachis hypogaea) recombinant inbred line population, demonstrating that the membrane lipid remodeling occurring at HT is consistent with homeoviscous adaptation to maintain membrane fluidity. A major alteration in the leaf lipidome at HT was the reduction in the unsaturation levels, primarily through reductions of 18:3 fatty acid chains, of the plastidic and extra-plastidic diacyl membrane lipids. In contrast, levels of 18:3-containing triacylglycerols (TGs) increased at HT, consistent with a role for TGs in sequestering fatty acids when membrane lipids undergo remodeling during plant stress. Polyunsaturated acyl chains from membrane diacyl lipids were also sequestered as sterol esters (SEs). The removal of 18:3 chains from the membrane lipids decreased the availability of susceptible molecules for oxidation, thereby minimizing oxidative damage in membranes. Our results suggest that transferring 18:3 chains from membrane diacyl lipids to TGs and SEs is a key feature of lipid remodeling for HT adaptation in peanut. Finally, QTL-seq allowed the identification of a genomic region associated with heat-adaptive lipid remodeling, which would be useful for identifying molecular markers for heat tolerance.

Early leaf spot (ELS) and late leaf spot (LLS) diseases are the two most destructive groundnut diseases in Ghana resulting in ≤ 70% yield losses which is controlled largely by chemical method. To develop leaf spot resistant varieties, the present study was undertaken to identify single nucleotide polymorphism (SNP) markers and putative candidate genes underlying both ELS and LLS. In this study, six multi-locus models of genome-wide association study were conducted with the best linear unbiased predictor obtained from 294 African groundnut germplasm screened for ELS and LLS as well as image-based indices of leaf spot diseases severity in 2020 and 2021 and 8,772 high-quality SNPs from a 48 K SNP array Axiom platform. Ninety-seven SNPs associated with ELS, LLS and five image-based indices across the chromosomes in the 2 two sub-genomes. From these, twenty-nine unique SNPs were detected by at least two models for one or more traits across 16 chromosomes with explained phenotypic variation ranging from 0.01 - 62.76%, with exception of chromosome (Chr) 08 (Chr08), Chr10, Chr11, and Chr19. Seventeen potential candidate genes were predicted at ± 300 kbp of the stable/prominent SNP positions (12 and 5, down- and upstream, respectively). The results from this study provide a basis for understanding the genetic architecture of ELS and LLS diseases in African groundnut germplasm, and the associated SNPs and predicted candidate genes would be valuable for breeding leaf spot diseases resistant varieties upon further validation.

In many parts of the world, limited water and climate change are significant challenges to the future of peanut production, and much work remains in developing heat- and drought-tolerant cultivars. To this end, we evaluated 21 accessions of the U.S. peanut mini-core under water-limited conditions in 2018 and 2019 in Oklahoma, Texas, and Virginia. These accessions were identified as potentially exhibiting phenotypic extremes for ten drought stress traits, and therefore may be useful for identifying genetic markers associated with drought tolerance. Results indicated that plant wilting and paraheliotropism (leaf folding) were less affected by genotype by environment interactions than SCMR (SPAD chlorophyll meter readings), flower counts, yield, TSMK (total sound mature kernels), and seed weight. No differences among genotypes were observed with canopy temperature, canopy temperature depression, or NDVI (normalized difference vegetation index). Paraheliotropism was moderately correlated (|r| = 0.40 to 0.52, P < 0.01) with SCMR and flower counts in the Southwest; SCMR was also correlated with yield and TSMK (r = 0.48, P < 0.01). Despite environmental differences between subhumid Virginia and the semiarid Southwest, the locations shared genotypes at the extremes for most traits. This information may be useful for future studies by highlighting traits associated with drought tolerance that may be more stable in different production environments, as well as divergent genotypes for those traits.

Toxic metabolites known as aflatoxins are produced via certain species of the Aspergillus genus, specifically A. flavus, A. parasiticus, A. nomius, and A. tamarie. Although various pre- and post-harvest strategies have been employed, aflatoxin contamination remains a major problem within peanut crop, especially in subtropical environments. Aflatoxins are the most well-known and researched mycotoxins produced within the Aspergillus genus (namely Aspergillus flavus) and are classified as group 1 carcinogens. Their effects and etiology have been extensively researched and aflatoxins are commonly linked to growth defects and liver diseases in humans and livestock. Despite the known importance of seed coats in plant defense against pathogens, peanut seed coat mediated defenses against Aspergillus flavus resistance, have not received considerable attention. The peanut seed coat (testa) is primarily composed of a complex cell wall matrix consisting of cellulose, lignin, hemicellulose, phenolic compounds, and structural proteins. Due to cell wall desiccation during seed coat maturation, postharvest A. flavus infection occurs without the pathogen encountering any active genetic resistance from the live cell(s) and the testa acts as a physical and biochemical barrier only against infection. The structure of peanut seed coat cell walls and the presence of polyphenolic compounds have been reported to inhibit the growth of A. flavus and aflatoxin contamination; however, there is no comprehensive information available on peanut seed coat mediated resistance. We have recently reviewed various plant breeding, genomic, and molecular mechanisms, and management practices for reducing A. flavus infection and aflatoxin contamination. Further, we have also proved that seed coat acts as a physical and biochemical barrier against A. flavus infection. The current review focuses specifically on the peanut seed coat cell wall-mediated disease resistance, which will enable researchers to understand the mechanism and design efficient strategies for seed coat cell wall-mediated resistance against A. flavus infection and aflatoxin contamination.

Identification of peanut cultivars for distinct phenotypic or genotypic traits whether using visual characterization or laboratory analysis requires substantial expertise, time, and resources. A less subjective and more precise method is needed for identification of peanut germplasm throughout the value chain. In this proof-of-principle study, the accuracy of Raman spectroscopy (RS), a non-invasive, non-destructive technique, in peanut phenotyping and identification is explored. We show that RS can be used for highly accurate peanut phenotyping via surface scans of peanut leaves and the resulting chemometric analysis: On average 94% accuracy in identification of peanut cultivars and breeding lines was achieved. Our results also suggest that RS can be used for highly accurate determination of nematode resistance and susceptibility of those breeding lines and cultivars. Specifically, nematode-resistant peanut cultivars can be identified with 92% accuracy, whereas susceptible breeding lines were identified with 81% accuracy. Finally, RS revealed substantial differences in biochemical composition between resistant and susceptible peanut cultivars. We found that resistant cultivars exhibit substantially higher carotenoid content compared to the susceptible breeding lines. The results of this study show that RS can be used for quick, accurate, and non-invasive identification of genotype, nematode resistance, and nutrient content. Armed with this knowledge, the peanut industry can utilize Raman spectroscopy for expedited breeding to increase yields, nutrition, and maintaining purity levels of cultivars following release.

In this paper, we present a procedure for implementing field-based high-throughput plant phenotyping (HTPP) that can be used in resource-constrained research programs. The procedure relies on opensource tools with the only expensive item being one-off purchase of a drone. It includes acquiring images of the field of interest, stitching the images to get the entire field in one image, calculating and extracting the vegetation indices of the individual plots, and analyzing the extracted indices according to the experimental design. Two populations of groundnut genotypes with different maturities were evaluated for their reaction to early and late leaf spot (ELS, LLS) diseases under field conditions in 2020 and 2021. Each population was made up of 12 genotypes in 2020 and 18 genotypes in 2021. Evaluation of the genotypes was done in four locations in each year. We observed a strong correlation between the vegetation indices and the area under the disease progress curve (AUDPC) for ELS and LLS. However, the strength and direction of the correlation depended upon the time of disease onset, level of tolerance among the genotypes and the physiological traits the vegetation indices were associated with. In 2020, when the disease was observed to have set in late in medium duration population, at the beginning of the seed stage (R5), normalized green-red difference index (NGRDI) and variable atmospheric resistance index (VARI) derived at the beginning pod stage (R3) had a positive relationship with the AUDPC for ELS, and LLS. On the other hand, NGRDI and VARI derived from images taken at R5, and physiological maturity (R7) had negative relationships with AUDPC for ELS, and LLS. In 2021, when the disease was observed to have set in early (at R3) also in medium duration population, a negative relationship was observed between NGRDI and VARI and AUDPC for ELS and LLS, respectively. We found consistently negative relationships of NGRDI and VARI with AUDPC for ELS and LLS, respectively, within the short duration population in both years. Canopy cover (CaC), green area (GA), and greener area (GGA) only showed negative relationships with AUDPC for ELS and LLS when the disease caused yellowing and defoliation. The rankings of some genotypes changed for NGRDI, VARI, CaC, GA, GGA, and crop senescence index (CSI) when lesions caused by the infections of ELS and LLS became severe, although that did not affect groupings of genotypes when analyzed with principal component analysis. Notwithstanding, genotypes that consistently performed well across various reproductive stages with respect to the vegetation indices constituted the top performers when ELS, LLS, haulm, and pod yields were jointly considered.

Peanut (Arachis hypogaea L.) is an important food crop for the U.S. and the world. The Virginia-Carolina (VC) region (Virginia, North Carolina, and South Carolina) is an important peanut-growing region of the U.S and is affected by numerous biotic and abiotic stresses. Identification of stress-resistant germplasm, along with improved phenotyping methods, are important steps toward developing improved cultivars. Our objective in 2017 and 2018 was to assess the U.S. mini-core collection for desirable traits, a valuable source for resistant germplasm under limited water conditions. Accessions were evaluated using traditional and high-throughput phenotyping (HTP) techniques, and the suitability of HTP methods as indirect selection tools was assessed. Traditional phenotyping methods included stand count, plant height, lateral branch growth, normalized difference vegetation index (NDVI), canopy temperature depression (CTD), leaf wilting, fungal and viral disease, thrips rating, post-digging in-shell sprouting, and pod yield. The HTP method included 48 aerial vegetation indices (VIs), which were derived using red, blue, green, and near-infrared reflectance; color space indices were collected using an octocopter drone at the same time, with traditional phenotyping. Both phenotypings were done 10 times between 4 and 16 weeks after planting. Accessions had yields comparable to high yielding checks. Correlation coefficients up to 0.8 were identified for several Vis, with yield indicating their suitability for indirect phenotyping. Broad-sense heritability (H2) was further calculated to assess the suitability of particular VIs to enable genetic gains. VIs could be used successfully as surrogates for the physiological and agronomic trait selection in peanuts. Further, this study indicates that UAV-based sensors have potential for measuring physiologic and agronomic characteristics measured for peanut breeding, variable rate input application, real time decision making, and precision agriculture applications.