After centuries of conventional tillage practices, sandy loam Coastal Plain soils have been heavily degraded, resulting in severely depleted soil organic carbon (SOC) stocks. This study examined impacts on soil health when transitioning from intensive tillage in vegetable production to no-till (NT) corn (Zea mays L.) and soybean (Glycine max (L.) Merr.) production with cover crops (CC). A long-term cropping system experiment, established in 2014, assessed twelve different crop rotations, including a conventionally tilled (CT) fallow control and various CC treatments, ranging from monocultures to a perennial mixture with corn planted every third year. After nine years, CC treatments increased near-surface SOC concentrations (8.4-10.5 g kg-1 at 0-5 cm) and SOC stocks (4.6-7.3 Mg ha-1) compared to fallow controls (6.4-6.9 g kg-1; 4.6-5.2 Mg ha-1). Soil organic carbon gains were most pronounced in the surface 5 cm and had a positive relationship with cumulative C inputs (R2 = 0.38). Cover crops reduced bulk density by up to 11 %, and SOC stocks were still significantly greater than fallow treatments as SOC concentration gains offset the lower bulk density. Treatments with hairy vetch (Vicia villosa Roth L.) or legume-dominant CC mixes lowered soil pH compared to fallow or grass-based CC treatments, potentially increasing the need for lime applications. Adoption of NT alone, without CCs, did not deliver similar soil health benefits. These results highlight the importance of integrating CCs into crop rotations to enhance SOC and improve soil physical properties in degraded Coastal Plain soils.

Pollination services provided by native bees are vital to the success of flowering plants in agricultural production and natural ecosystems. There are concerns that many native bee species are in decline due to multiple concurrent factors stemming from practices adopted by industrial agricultural production systems, such as the loss of suitable habitat, lack of floral resources and pesticide exposure. Most bee species in North America rear their offspring below ground and are potentially vulnerable to soil management activities, such as tillage operations in row crop settings. We investigated the effects of tillage on ground-nesting bees in a row crop system by intensively sampling bees nesting within treatments representative of standard tillage practices employed in the Southeastern United States. Our study is among the first to investigate how tillage regimes shape entire bee assemblages in intensively managed US croplands; by contrast, most previous research has focused almost exclusively on the squash bee, Eucera (Peponapis) pruinosa (Say, 1837), and has produced mixed results We found strong evidence that ground-nesting bee incidence, abundance and diversity declined to varying degrees in all tilled treatments compared to field edges. Clarifying whether tilled fields act as ecological sinks or are simply avoided as unsuitable habitat will be critical for guiding conservation efforts that prioritise the preservation and enhancement of semi-natural margins in agricultural landscapes.

Insect-associated viruses (viromes) shape insect biology and agroecosystems, yet aphid viromes remain undercharacterized. The cotton aphid, Aphis gossypii, is a globally distributed pest with a broad plant host range and demonstrated virus-vector competence, making it well suited for investigating virome composition at the plant–insect–virus interface. In this study, we profiled the virome of field-collected aphid alates, which were dominated by A. gossypii but included additional aphid species in some samples, across 15 cotton fields in Alabama, USA, to assess taxonomic diversity, relative viral abundance, and focal aphid-associated viruses. Metatranscriptomic sequencing of aphid alates revealed differences in taxonomic composition among county-level libraries, including viruses and diverse prokaryotic and eukaryotic taxa. Fifty-eight viral contigs > 1 kb were assembled, of which 20 were assigned to seven families: Dicistroviridae, Iflaviridae, Mitoviridae, Nudiviridae, Partitiviridae, Phasmaviridae, and Solemoviridae. Representative contigs from six families (all except Phasmaviridae) and five additional family-unassigned viruses were validated by PCR and Sanger sequencing. Three iflaviruses (RrIV, AgIV1, and AgIV2), positive-sense single-stranded RNA viruses, were discovered, including one associated with Rhopalosiphum rufiabdominale and two with A. gossypii. Their complete genomes were determined using PCR-based resequencing and 5′/3′ RACE, each comprising a single open reading frame that encodes a polyprotein. Sequence identity and phylogenetic analyses indicate that the newly identified viruses are putative new species and form a distinct clade together with previously reported aphid iflaviruses within Iflaviridae. AgIV1 and AgIV2, despite being associated with the same host species, were not monophyletic within this clade, consistent with cross-species transmission among aphid hosts. Strand-specific RT-PCR detected negative-strand RNA for AgIV1 and AgIV2, suggesting replication in aphids. Given their low field prevalence, we propose the names Iflavirus furtiva (RrIV), Iflavirus obscurata (AgIV1), and Iflavirus rarivira (AgIV2). The aphid virome is taxonomically diverse and shows county-level differences in relative viral contig abundance. We identified seven viral families and three complete iflavirus genomes, providing a foundation for further investigating their host range, transmission, and potential impacts on aphid biology and cotton production.

Context: Corn (Zea mays, L.) generates significant surface residue, which can require intensive surface tillage and increased N fertilizer rates to optimize subsequent wheat (Triticum aestivum, L.) production. However, surface tillage degrades soil health benefits, while unnecessary N applications reduce profits. Therefore, identifying the correct surface tillage level and N rate combination is critical to optimize wheat yields and profits following corn production. Methods: A split plot treatment restriction in a randomized complete block design with three blocks was used to evaluate surface tillage levels and N fertilizer combinations for wheat following corn over four non-consecutive growing seasons (2016-17, 2017-18, 2019-20, 2020-21) on a Decatur silt loam (fine, kaolinitic, thermic Rhodic Paleudult) in northern Alabama, USA. Tillage systems [conventional tillage (CT), mulch tillage (MT), light disk (LD), and no tillage (NT)] were main plots and fall and spring N rate (67, 101, and 134 kg N ha- 1) combinations applied as urea-ammonium nitrate 28% solution were subplots to evaluate early season wheat growth (tiller density, tiller biomass, and tiller N uptake), in-season wheat growth (biomass and N uptake), wheat yields, nitrogen use efficiency (NUE), and net returns. Results: Fall N increased early season wheat growth parameters up to 25%. In-season N uptake varied across tillage systems with inconsistent responses to split applications across N rates. The CT, MT, and LD systems yielded 23% greater than the NT system across N treatments and growing seasons. Grain NUE averaged 38.7% across growing seasons for all tillage and N treatments. Average net returns were US$733 ha- 1 (MT), US $643 ha- 1 (LD), US$601 ha- 1 (CT), and US$468 ha- 1 (NT). Conclusions: Wheat growth and production declined when planted into corn residue as surface tillage decreased. This effect was further exacerbated with low N applications. Fall N applications enhanced early season wheat growth, but a split application of the remaining N did not increase wheat yields compared to the corresponding single rate application. Therefore, split N applications did not benefit wheat production following corn compared to single N applications across N rates and conditions examined in this experiment. Applying 134 kg N ha- 1 maximized wheat yields and net returns for NT, but results indicated greater N rates above current recommendations across all tillage systems following corn could be justified.

High-throughput sequencing (HTS) has expanded our perspective on the distribution and diversity of plant viruses. Furthermore, improvements in HTS and decreasing sample costs have enabled the discovery of novel plant viruses in field-collected samples. This study examined the putative virome of cotton samples collected from fields across the southern United States. Leaf samples were collected, and total RNA was extracted. Library preparation was performed from pooled samples within locations before sequencing on an Illumina platform. Sequenced libraries were mapped to the cotton reference genome, and the resulting sequences were de novo assembled. A metatranscriptomics analysis revealed complete genome contigs of cotton leafroll dwarf virus in all tested samples. Additionally, 29 putative families of RNA and DNA plant viruses co-infecting cotton were found. Seven families of RNA viruses were more prevalent across all locations. These families included Botourmiaviridae, Hypoviridae, Mitoviridae, Narnaviridae, Partitiviridae, Solemoviridae, and Totiviridae. The information obtained in this investigation will help develop a broader perspective on cotton virus diversity and whether co-infections of viruses can influence (negatively or positively) plant physiology, product quality, and yield.

Accurate and high spatiotemporal resolution soil moisture (SM) monitoring in cropland is important for water resource management, drought forecasting, and nutrient transport estimation at the field scale for sustainable crop production. Although recent research has applied machine learning (ML) to downscale coarse-resolution satellite SM products, most of this past work has focused only on surface SM estimation, and the performance of rootzone SM products has not been intensively evaluated in cropland. This study introduces a novel framework that integrates multi-source satellite-based ML models with the Layered Green and Ampt Infiltration with Redistribution (LGAR) model to produce high-resolution (100 m, hourly) SM products for both the surface layer (0-5 cm) and rootzone (0-100 cm) across cropland in the contiguous United States (CONUS). First, six ML models were trained using multiple high-resolution remote sensing datasets (Sentinel-1, Sentinel-2, and Landsat) to predict surface and rootzone SM. These ML predictions were then assimilated into the LGAR model using the ensemble Kalman filter (EnKF). The framework was developed and validated using an eight-fold cross-validation scheme with in-situ data from 431 cropland sites across CONUS, sourced from three networks (SCAN, USCRN, and PSA). The 100-m hourly SM data from this framework surpasses existing products (9-km SMAP L4, SMAPbased 1-km thermal hydraulic disaggregation of SM product) in spatial and temporal resolution and captures rootzone SM that is not available in the SMAP-HydroBlocks SM product. It achieves good performance, with median bias-corrected root mean squared error (ubRMSE) of 0.053 m3/m3 and median Kling-Gupta efficiency (KGE) of 0.379 in the surface layer, and median ubRMSE of 0.027 m3/m3 and median KGE of 0.302 in the rootzone. While the framework demonstrates strong performance, its accuracy varies across climatic regimes, with surface SM performing better in non-humid areas (median KGE = 0.375 versus median KGE = 0.416) and rootzone SM in humid regions (median KGE = 0.313 versus median KGE = 0.127). This high-resolution cropland SM product can potentially benefit multiple agricultural applications, such as irrigation management and nutrient leaching estimation, and provide valuable insights to support farmers and land managers in decision-making processes.

Cotton leafroll dwarf virus (CLRDV) is a polerovirus transmitted by Aphis gossypii Glover. Factors contributing to cotton (Gossypium hirsutum L.) yield losses caused by CLRDV infection remain unclear, but results from previous studies indicate that the environmental component of the disease triangle may significantly influence yield loss outcomes. This 3-year study was conducted to compare yield and yield components, fiber quality, root weight, and other morphological parameters of CLRDV-infected and noninfected plants grown under high heat conditions. Potted plants were grown in an insect-proof screen house covered with plastic, and data were collected on a per-plant basis. Plants did not exhibit obvious symptoms during any year of the study. CLRDV infection significantly reduced lint yield, number of seeds, number of bolls in the first fruiting position, seed index, and root dry weight. Fiber quality analysis showed that there was a reduction in the content of short fibers in CLRDV-infected plants. Possible interference of CLRDV on translocation of photoassimilates in the phloem, along with changes in net photosynthesis and other physiological processes, may explain how this virus affected some of the parameters evaluated, especially lint yield, yield components, and root dry weight.Copyright (c) 2026 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Soil compaction negatively impacts soil physical properties and crop yields and is influenced by organic matter inputs and tillage management. We evaluated cone index (CI) in five long-term organic and conventional cropping systems at the Farming Systems Project in Beltsville, MD (39.0 degrees N, 76.9 degrees W), to understand how different management systems influence soil strength. Measurements were collected prior to planting corn in 2017 using a tractor-mounted hydraulic five-probe penetrometer for three depths (0-15, 15-30, 30-50 cm) and three positions relative to the crop row (0, 22.5, and 45 cm). The two conventional systems, No-till (NT) and Chisel Till (CT), were both 3-yr corn-rye cover crop/soybean-wheat/soybean rotations. The three organic systems were comprised of: (Org2) 2-yr hairy vetch cover crop/corn-rye cover crop/soybean; (Org3) 3-yr hairy vetch cover crop/corn-rye cover crop/soybean-wheat; and (Org6) 6-yr corn-rye cover crop/soybean-wheat-alfalfa-alfalfa-alfalfa. Org2 and Org3 exhibited the lowest CI in the 0-15 cm depth, due to fall tillage before cover crop planting and weed control in the prior crop. In contrast, surface soil compaction in Org6 was similar to that in the conventional systems, attributed to alfalfa harvest machinery traffic over the past three years and absence of any tillage. At deeper depths (15-30 cm and 30-50 cm), the NT system consistently demonstrated lower CI compared to other systems. For tilled systems, maximum CI values at 15-30 cm were near or exceeded the root-restricting threshold of 2.5 MPa. The NT system potentially provided a larger rooting volume for water and nutrient uptake than tilled systems. Machinery traffic increased compaction, particularly at 22.5 cm from the crop row, likely due to tire sidewall pressure. Overall, the study found moderate effects of contrasting management system practices on soil strength.

Image resolution and size of the soil core can impact X-ray computed tomography (CT)-derived soil morphological properties. An improved understanding of soil physical properties can help elucidate contaminant transport processes through the soil profile. The main goal of this study was to compare the influence of CT scanning resolution and soil core diameter on the estimated soil pore properties. Cylindrical soil cores, with diameters of 76 and 150 mm and length of 640 mm, were collected from the loamy sand soil in a cotton field located in Alabama, USA. Soil cores were collected from conventional tillage and strip tillage portions of the field, in the fall, following cotton harvest and before planting a cover crop (season 1), and in the spring, after the cover crop had matured (season 2). Specific objectives were 1) to quantify the effect of voxel resolution (0.35 mm × 0.35 mm × 0.625 vs. 0.1875 mm × 0.1875 mm × 0.625 mm) on detected soil physical properties, 2) to determine the impact of soil core diameter (150 mm vs. 76 mm) on detected soil macropore properties, and 3) to determine the effect of chosen region of interest for image analysis (140 mm vs. 96 mm diameter region of interest) on estimated soil pore properties. Results on change in derived soil pore properties as a function of soil core diameter and resolution show that a smaller field of view, which gave higher resolution, showed a greater number of isolated pores with greater values of anisotropy. The 76 mm soil core diameter had significantly fewer detected pores compared to 150 mm diameter cores, but the connectivity of pores was greater for the 76 mm diameter cores. Most of the significant differences were found among the cores, which were collected from the conventional tillage treatment in season 2. Image resolution and sample size impacted the estimated properties of the soil pores. Finer resolution achieved using a smaller field of view showed a greater number of isolated pores with greater values of anisotropy. For a similar field of view, the larger diameter core had greater pore number density and surface area density as compared to the smaller diameter core. Future research should employ high-resolution X-ray CT scanners to quantify the impact of resolution on derived soil pore properties.

In 2017, cotton (Gossypium hirsutum L.) leafroll dwarf virus (CLRDV) was first reported in the United States. One CLRDV inoculum source includes the previous year's cotton stalks; hence, destroying cotton stalks could be effective for CLRDV management. However, tillage-intensive stalk destruction methods (SDMs) can degrade southeastern soils, but a cover crop may provide short-term benefits and reduce CLRDV incidence. Therefore, we examined three SDMs (Tillage, Pull, Mow) across two cover crop levels (no cover and rye [Secale cereale L.]/clover [Trifolium incarnatum L.] mixture) and two cotton varieties to determine how cotton growth, soil penetration resistance (PR), and two CLRDV incidence sample times (pre-harvest and post-harvest) were affected across six environments during the 2021 and 2022 growing seasons. None of the SDMs affected any factors examined in this experiment, except soil PR and cotton yield. The Pull and Mow SDMs both increased soil PR compared to the Tillage SDM. An 8% yield increase (Pull > Mow) was observed, but the Tillage SDM yield did not differ from Pull or Mow SDMs. The rye/clover mixture also increased soil PR. Although cotton stands were 15% greater with no cover crop, subsequent cotton yield and fiber quality were minimally affected by cover crops. The rye/clover mixture increased post-harvest CLRDV incidence, and cotton yields were equal between cover crops. Pre-harvest CLRDV incidence probability was 0.23, but post-harvest CLRDV incidence probability was 0.71. Continuing to identify and evaluate cultural practices that reduce CLRDV incidence is imperative to prevent negative impacts.

Soil macropores can enhance the loss of phosphorus (P) and metals via preferential flow pathways in soils fertilized with broiler litter. Cover crops can enhance soil macropores and contribute to preferential flow pathways. Our objective was to determine the effect of cover crops on total P (TP), colloidal P (CP), dissolved reactive P (DRP), dissolved P (DP), total metals, dissolved metals, and colloidal metals in leachate from loamy sand soil cores consisting of soil macropores and fertilized with broiler litter. The cover crop, a mixture of cereal rye and crimson clover, was planted in the late fall in the field. The main crop, planted the following spring, was strip-tillage cotton. Following cotton harvest, intact undisturbed cylindrical soil cores (15 cm diameter and 50 cm depth) were collected from cover crop (CC) and no cover (NC) parts of the field. In the laboratory, for half of the leachate trials with the CC soil cores and half of those with the NC soil cores, we broadcasted broiler litter on the soil surface of the cores using a 10 Mg/ha application rate. For the other half of the trials with the CC cores and the other half with the NC cores, no litter was applied. Rainfall simulations were conducted on each core, and leachate was collected after it flowed down through each soil core. The leachates collected during the rainfall simulations were analyzed for TP, CP, DRP, DP, total metals, dissolved metals, and colloidal metals. The TP, CP, and DP concentrations were significantly greater from CC cores fertilized with broiler litter, than from NC cores fertilized with broiler litter. The mean leachate concentration of TP in soil cores fertilized with broiler litter was 4.07 and 1.54 mg L- 1 for CC and NC, respectively. Application of broiler litter resulted in CP loss, which was less than 10 % of TP. Similar trends were observed in dissolved and total trace metal losses. The preferential flow through soil macropores increased the mobility and velocity of solute movement in the cover cropping system.

This report contains the first molecular record of the cotton jassid, Amrasca biguttula (Hemipter: Cicadellidae), in the United States. Nymphs across multiple instars and adult specimens were collected from a cotton ( Gossypium hirsutum ) field in Macon County, Alabama, in August 2025. While distinct paired dark spots were observed on forewings of adult specimens, this trait was present on wing pads of some nymphs but absent in others. Cytochrome oxidase I (COI) DNA barcoding confirmed the specimen identity. The United States sequence shared > 99% identity with Asian A. biguttula references and clustering placed the sequence within the A. biguttula clade with 100% posterior probability support in phylogenetic analysis. Although this pest was previously reported in 2023 from Puerto Rico based solely on morphological traits, our findings provide the first DNA-confirmed evidence of its presence in the continental United States. Given its well-documented role in damaging cotton across Asia and Africa, this report underscores the urgent need for monitoring and development of management strategies in United States cotton-growing regions. ### Competing Interest Statement The authors have declared no competing interest.

Aphids are among the most destructive insect pests to crops. Based on the degree of their host specialization, aphids, like other herbivorous insects, have been grouped into three categories: monophagous, oligophagous, and polyphagous [1]. Monophagous aphids feed on only one or a few closely related plant species, often of a single genus, oligophagous aphids feed on several plant species of the same family, and polyphagous aphids feed on plants that belong to more than one family. Polyphagous aphids are considered generalist herbivores, comprising less than half of the total aphid species [2; 3]. However, this polyphagous nature allows generalist aphids to disseminate plant pathogens to a wide range of host plants [3; 4].The cotton aphid (or melon aphid), Aphis gossypii Glover, is a highly polyphagous aphid species that can feed on at least 700 plant species in numerous families including Asteraceae, Cucurbitaceae, Malvaceae, Rutaceae, Solanaceae, and Fabaceae [5; 6; 7]. Population studies of A. gossypii have shown that diversity is mainly associated with differences in host plant preference. Moreover, several plant host-specialized biotypes have been documented [8; 9; 10].Other factors including geography, climate, and pesticide use can also contribute to shaping its population structure [11; 12]. Interestingly, profiles of microbial symbionts, on which aphids are dependent in numerous physiological processes, may vary in different A. gossypii biotypes and populations, suggesting specialized interactions evolved between A. gossypii and its microbial symbionts under selection pressure exerted by a variety of environmental factors [13; 14; 15]. Hence, a population-specific microbiome analysis is crucial to understanding aphid-microbe interactions in locally adapted A. gossypii.As a worldwide distributed agricultural pest, A. gossypii is responsible for severe yield losses of many economically important crops such as cotton, cucumber, and citrus [5; 7]. Besides injuring plants directly by sucking the sap, while feeding, it secretes honeydew which fosters growth of sooty mold that can block sunlight and decrease photosynthesis processes within the plant [16]. Moreover, A. gossypii is important for its ability to transmit over 75 plant viruses [17] and was ranked the second most competent aphid species in terms of number of potyviruses it vectors [3]. In cotton, A. gossypii transmits several viruses including cotton leaf roll dwarf virus (CLRDV), cotton anthocyanosis virus, and cotton bunchy top virus, posing a severe threat to cotton production [18; 19; 20].In the Southeast USA, cotton is one of the most economically important crops, and A. gossypii is a major insect pest of cotton and the only known vector of CLRDV. As a primary cotton-growing region in the Southeast, Alabama also reported the first occurrence of CLRDV in 2017 [21]. This virus was later detected throughout the Southeast [22; 23]. Given the significant economic impact of A. gossypii in Alabama, we performed metatranscriptomic and metagenomic analyses on locally collected cotton aphids to decipher their microbiota.These sequencing datasets provide genetic information, at both RNA and DNA levels, of symbiont microbes and their overall community composition in a local A. gossypii population from Alabama, USA. The microbiome data can be used to identify A. gossypii-associated and transmitted plant pathogens and discover insect-infecting microbes for aphid biocontrol. In addition, plant species identified in the sequencing data from the whole aphid, will provide insights into the plant host range of A. gossypii in the locality tested. Library preparation and Illumina sequencing were conducted at Novogene Corp. Inc.(Sacramento, CA, USA).For RNA sequencing, ribosomal RNAs from both eukaryotes and prokaryotes were first depleted from total RNA samples using the Ribo-Zero rRNA removal kit (Illumina, USA). The remaining RNAs were fragmented into ~250 to 300 bp and then reverse-transcribed into doublestranded cDNAs. For metagenomic sequencing, 1 µg of genomic DNA was randomly sheared into short fragments of approximately 350 bp. The double-stranded cDNAs (for RNA sequencing) and sheared genomic DNA fragments (for DNA sequencing) were subsequently end repaired to produce blunt ends, added with a single 'A' nucleotide at the 3' ends, and further ligated with Illumina adapters. After fragment size selection and PCR amplification, the prepared metatranscriptomic and metagenomic libraries were sequenced on the Illumina NovaSeq platform (Illumina, CA, USA) with pair-end 150 mode.To generate a metatranscriptome, RNA raw reads were first preprocessed by trimming adaptors and removing low-quality reads using Trimmomatic (v0.39) in paired end mode [24].Parameters for Illumina clip were seed mismatches = 2, palindrome clip threshold = 30, and simple clip threshold = 10. Other parameters included the sliding window trimming with a window size = 5, required quality = 20, and minimum read length = 50. Clean reads were then aligned to the A. gossypii genome (NCBI accession GCF_020184175.1) [25] using the BWA-MEM mapping tool (v0.7.17) with its default parameters [26]. Unmapped paired reads were assembled to create metatranscriptomic contigs using SPAdes (v3.15.5) in meta mode [27].A metagenomic assembly was similarly generated following these three steps: 1) preprocessing of DNA raw reads, 2) mapping of clean reads to the reference genome, and 3) assembling of unmapped paired reads. For Step 1, Readfq (v8; https://github.com/cjfields/readfq) was used to trim adaptors and remove the low-quality reads that have: a) more than 40 lowquality bases with Q-value < 38, b) more than 10 ambiguous nucleotides "N", or c) more than 15 bp's overlap with adaptors. Step 2 was conducted using BWA-MEM as described above. ForStep 3, Megahit (v1.2.9) was used at the default setting to generate metagenomic contigs [28].Contigs longer than 400 bp were retrieved for taxonomic analysis. Contig sequences were first aligned to a preformatted NCBI non-redundant (NR) reference database downloaded on August 28, 2023, with the BLASTX function by running DIAMOND (v2.1.8) [29]. The output was written in DAA (DIAMOND alignment archive) format, which was then used for Meganization, an approach of performing taxonomic and functional binning of the sequences [30]. The DAA file was run against the MEGAN database 'megan-map-Feb2022.db' in long read mode, using MEGANIZER, a program included in the MEGAN package (v6_25_3) [31]. Lastly, a taxonomic analysis was conducted using MEGAN, in interactive mode, to determine kingdom and genus level assignations for all contigs.Total RNA and DNA extracted from the A. gossypii sample, consisting of 10 fieldcollected alataes, had high purity (OD260/280 > 2.0) and high quality (RIN = 8.3). A total of 88,776,140 and 84,900,570 raw reads were obtained from the Illumina sequencing of RNA (AAL8R) and DNA (AAL8D) samples, respectively, which, after preprocessing to remove adaptors and low-quality reads, yielded 86,527,106 and 84,867,588 clean reads (Table S1). The GC content of DNA reads was lower (26.77%) than the RNA reads (39.00%) but similar to PacBio reads (27.26-27.99%) of the published A. gossypii genome used as reference [25].Mapping of RNA and DNA reads to the A. gossypii genome revealed 49.21% and 98.17% of genome coverage, respectively. left A total of 17,914,277 and 5,563,338 potentially non-host RNA and DNA reads were unmapped, accounting for 20.70% and 6.56% of their total clean read numbers , respectively (Table S1).Two de novo assemblies were generated: one from the AAL8R and the other from the AAL8D non-host reads not mapped to the A. gossypii genome. The AAL8R assembly consisted of 23,101 contigs with an average length of 365 bp and a medium (N50) length of 337 bp. The AAL8D assembly consisted of 11,415 contigs with an average length of 984 bp and a medium length of 1,390 bp (Table S1). Contigs longer than 400 bp, including 3,804 AAL8R contigs and 8,454 AAL8D contigs, were finally selected for taxonomic annotation.Taxonomic analysis of the non-host reads using Kraken2 [32] The acquired metatranscriptomic and metagenomic contigs were annotated at the kingdom and genus levels using the DIAMOND+MEGAN taxonomic analysis approach [30].Over half of the contigs in both RNA and DNA datasets assembled from non-host reads were classified into specific kingdoms. This included 2704 (71%) AAL8R and 4504 (53%) AAL8D contigs (Fig. 1). "Bacteria", "Metazoa", and "Fungi" were the three most abundant kingdoms for AAL8R. "Metazoa", "Bacteria", and "Naldaviricetes" were most abundant for AAL8D. In both the RNA and DNA datasets, a high proportion of sequences received a "Metazoa" assignation. This is likely the result of reads that did not map to the reference genome due to the presence of sequence gaps and as a result were designated as non-host reads [25]. Genetic variation between the reference genome, obtained with aphids collected in China [25], and those used in this experiment, collected in Alabama, may be another factor that led to the designation of some reads as non-host. Contigs assembled from these "non-host" reads consequently received the "Metazoa" assignation.Previous studies showed that the microbiome of A. gossypii can be determined by a variety of factors, including plant host, geography, and life stage [13; 14; 15; 33; 34]. Our genuslevel taxonomic analysis on bacterial contigs indicated that the genus Arsenophonus was the most dominant group of symbionts in both AAL8R and AAL8D samples (Fig. 2A).Arsenophonus species are known as male-killing facultative symbionts found in a broad range of arthropod hosts [35; 36]. Aside from acting as son killers to benefit female offspring [37], some Arsenophonus species were recognized as insect-vectored plant pathogens [38]. In aphids, members of Arsenophonus can also play a role in parasitoid defense [39] and plant host specification [40].Our analysis demonstrated that Pseudomonas was the second most dominant bacterial genus (569 contigs) in the AAL8R sample (Fig. 2A). Like Arsenophonus, Pseudomonas has been Formatted: Indent: First line: 0.5"shown to interact with its insect host in a multifaceted manner: while some species are entomopathogenic, others may be beneficial endosymbionts of insects or insect-vectored plant pathogens [41]. Other bacterial genera with ≥ 10 contigs in either AAL8R or AAL8D included Aureimonas, Buchnera, Hamiltonella, and Serratia (Fig. 2A). Among these, Aureimonas was found in a recent cotton microbiome study [42] but has not been reported as an aphid symbiont.Given that cotton components were likely present in the gut of A. gossypii collected in the cotton field, it is not possible to discriminate whether Aureimonas DNA reads originated from the aphid or the cotton host. By contrast, Buchnera is a well-studied primary endosymbiont present in almost all aphid species [43]. Despite the contig numbers not being the highest, Kraken2 taxonomic analysis indicated that the number of reads assigned to Buchnera comprised 78.79% (7,056,145 reads) and 56.7% (1,577,306 reads) of the non-host RNA and DNA reads, respectively. This suggests that using contig numbers to infer the abundance of a taxon could be inaccurate, as it does not take into account many factors, such as genome size, contig length, and sequencing depth. However, the number of contigs represents a useful metric for initial assessments, providing a general overview of the taxonomic composition within a sample, especially when combined with other analytical methods. Previous studies using 16S rRNA sequencing have confirmed the presence of several bacterial genera in A. gossypii, including Buchnera, Arsenophonus, Pseudomonas, Hamiltonella, and Serratia [13; 14; 15]. Furthermore, research progress on Hamiltonella and Serratia has been made in recent years, and both genera have been identified in the microbial community of A. gossypii [13; 15]. While Hamiltonella was shown to mainly play a role in stress tolerance and parasitoid defense in insects, Serratia has been shown to be symbiotic or pathogenic to its insect host [44; 45; 46]. Two genera of DNA viruses, Alphabaculovirus and Aplhanudivirus, were detected in both RNA and DNA samples (Fig. 2B). Detection of DNA viruses in the RNA sample suggested that they were actively replicating in the host cells. Alphabaculovirus and Aplhanudivirus are double-stranded DNA (dsDNA) viruses that infect insects [47; 48]. Therefore, we suspect that the contigs of these two genera in the samples could correspond to DNA viruses of A. gossypii.Further analysis is needed to determine their biological and molecular properties. We also found sequences of two genera of putative RNA viruses, Goukovirus and Cripavirus (Fig. 2B), whose members are known to infect insects [49; 50]. Although the aphid-transmitted cotton virus, CLRDV, is widely distributed in cotton fields [23], we did not find CLRDV contigs in this study, possibly due to the relatively small aphid sampling size.Taxonomic analysis on the fungal contigs revealed that Conidiobolus, Fibularhizoctonia, Basidiobolus, and Beauveria were the most abundant genera with at least 5 contigs each (Fig. 2C). Notably, Conidiobolus and Beauveria encompass significant entomopathogenic species like B. bassiana, which has been employed as a biological insecticide to manage a diverse array of insect pests [51; 52]. Despite the prevalence of Neozygites fresenii, a naturally occurring fungal pathogen of A. gossypii in the Southeast USA [53; 54], we did not identify any contigs assigned to the Neozygites genus. This may be the result of the small aphid sample size used in this study.Formatted: Font: Italic Formatted: Font: Italic Formatted: Font: Italic Our analysis, mostly from the RNA sample, showed that the highest number of plant contigs were assigned to the genus Gossypium. This is not surprising as the aphids were collected in cotton fields. However, we also detected at least one contig for twelve other plant genera belonging to several families (Fig 2D). We concludeAlthough these spurious hits in the database are not conclusive, that thesethey might represent remains of plant hosts fed upon by the aphids. Should this be true, tThis finding supports the well-established fact that A. gossypii is polyphagous but also suggests that the aphids we collected moved in and out of the cotton field and had fed on a variety of plants. This is of importance because with this movement A. gossypii can potentially transmit viruses, fungi and bacteria to cotton from plants adjacent to commercial cotton fields. The methods presented in this study, on an expanded scale, can be used to monitor pathogens and plant use of A. gossypii in cotton fields.In conclusion, through sequencing A. gossypii alataes collected in Alabama, USA, we generated two de novo assemblies: a metatranscriptome and a metagenome. The DIAMOND+MEGAN taxonomic analyses on these assemblies uncovered putative sequences of a variety of organisms that may form complex interaction networks associated with A. gossypii. These protocols can be applied not only for microbiome analysis but also to investigate the host range of herbivorous insect species. Additionally, the DNA reads can be used for population genomics research, the RNA reads can be used to enhance gene annotation, and both RNA and DNA reads can contribute to refining the assembly of the A. gossypii genome.

Changes in soil pore size distribution and connectivity can affect contaminant transport. Climate, soil type, and agricultural management practices can influence these characteristics. Conservation tillage practices, such as strip tillage, have been promoted as agricultural management practices that can help reduce soil erosion and nutrient loss in runoff. However, limited information exists in the literature on the effect of strip tillage on soil pore characteristics. Thus, the objective of this research study was to assess the effects of different tillage practices i.e., conventional tillage (CT) vs. strip tillage (ST), on soil pore properties and quantify change in soil pore characteristics as a function of season. Undisturbed cylindrical soil columns (150 mm diameter and 640 mm length) were collected from a field in Alabama, USA planted with cotton (Gossypium hirsutum L.) under ST and CT treatments during two seasons i.e., fall 2021 and spring 2022. Soil cores were collected from CT and ST portions of the field, in the fall, following cotton harvest and before planting a cover crop (season 1), and in the spring, after the cover crop had matured (season 2). X-ray computed tomography was used to scan the soil cores and quantify soil pore characteristics. Results show that the ST treatment had significantly (p < 0.05) greater macroporosity values, network density, macropore length density, and interconnectivity compared to the CT in season 1. This was attributed to ST being a minimally disturbed treatment: thereby, it has a better chance of preserving cracks and biological activity as compared to CT, which is more prone to destruction of large macropores. The pore properties also showed a drastic decrease in values during season 2, especially for the top 200 mm of the soil profile in response to rainfall induced soil reconsolidation in both the tillage systems. Overall, this study showed that pore morphology can be affected by tillage and seasonal aspects associated with them.

Most plants produce large amounts of seeds to disperse their progeny in the environment. Plant viruses have evolved to avoid plant resistance mechanisms and use seeds for their dispersal. The presence of plant pathogenic viruses in seeds and suppression of plant host defenses is a major worldwide concern for producers and seed companies because undetected viruses in the seed can represent a significant threat to yield in many economically important crops. The vertical transmission of plant viruses occurs directly through the embryo or indirectly by getting in pollen grains or ovules. Infection of plant viruses during the early development of the seed embryo can result in morphological or genetic changes that cause poor seed quality and, more importantly, low yields due to the partial or ubiquitous presence of the virus at the earliest stages of seedling development. Understanding transmission of plant viruses and the ability to avoid plant defense mechanisms during seed embryo development will help identify primary inoculum sources, reduce virus spread, decrease severity of negative effects on plant health and productivity, and facilitate the future of plant disease management during seed development in many crops. In this article, we provide an overview of the current knowledge and understanding of plant virus transmission during seed embryo development, including the context of host-virus interaction.

State-level cooperative extension services provide fertilizer recommendations for row crops in the United States. Of these, nitrogen (N) recommendations are arguably the most important because N is the most common yield-limiting nutrient in nonlegume crop production systems. Throughout the peanut ( Arachis hypogaea L.) growing region of the United States, Cooperative Extension Services generally recommends 22–67 kg N/ha credit to crops following peanut, likely due to the assumption that peanut, being a legume, contributes N to the following crop. The body of peer-reviewed literature indicates that N credits from peanut to the subsequent crop are negligible. Recent literature indicates that apparent differences in yield following peanut compared to a nonlegume are a result of nonlegume crop residue favoring N immobilization rather than N mineralization from peanut residue. Taken together, recent research corroborates the few previous scientific publications addressing the issue, namely, that cooperative extension service recommendations to reduce N fertilization to crops after peanut are not supported by the peer-reviewed literature. Future field research should include summer fallows to determine if yield differences between legumes and nonlegumes are due to N credits by the legume or N immobilization by nonlegumes. Data on N loss pathways following peanut are needed to identify management strategies that can mitigate N losses after peanut harvest. In conclusion, the preponderance of peer-reviewed science does not support current Extension recommendations regarding peanut N credits to the following crop.

Winter cover crop performance metrics (i.e., vegetative biomass quantity and quality) affect ecosystem services provisions, but they vary widely due to differences in agronomic practices, soil properties, and climate. Cereal rye (Secale cereale) is the most common winter cover crop in the United States due to its winter hardiness, low seed cost, and high biomass production. We compiled data on cereal rye winter cover crop performance metrics, agronomic practices, and soil properties across the eastern half of the United States. The dataset includes a total of 5,695 cereal rye biomass observations across 208 site-years between 2001–2022 and encompasses a wide range of agronomic, soils, and climate conditions. Cereal rye biomass values had a mean of 3,428 kg ha−1, a median of 2,458 kg ha−1, and a standard deviation of 3,163 kg ha−1. The data can be used for empirical analyses, to calibrate, validate, and evaluate process-based models, and to develop decision support tools for management and policy decisions.

Best management practices that optimize agronomic performance and make Brassica carinata production compatible with existing cropping systems are crucial for the establishment of a carinata supply chain in the southeastern United States. To this end, research was carried out to quantify land preparation method (conventional, no-till, broadcast-disc, and ripper-roller) and seeding rate effects on (1.12, 5.60, 10.09, and 14.57 kg seed ha(-1)) on B. carinata physiology, yield, and seed chemical composition. Data were collected on days to 50% flowering; canopy cover; gaseous exchange parameters (leaf net photosynthesis, stomatal conductance, transpiration, intercellular CO2, and water use efficiency); leaf area index; root weight; shoot weight; aboveground biomass; yield; and seed chemical composition. Leaf net photosynthesis was affected by land preparation treatment, being greater under the ripper-roller treatment, particularly during bolting. On the other hand, a decrease in photosynthesis, stomatal conductance, and water use efficiency was observed as seeding rate increased, especially during bolting. Carinata seed under the ripper-roller land preparation had the greatest oil content but lowest glucosinolates and protein contents. Yield did not respond to land preparation. Yield was minimized (732 kg seed ha(-1)) at the 1.12 kg ha(-1) seeding rate and maximized (1087 kg seed ha(-1)) at the 5.6 kg ha(-1) seeding rate. No land preparation by seeding rate interaction was observed for gas exchange parameters and LAI during any of the growth stages, nor was any interaction observed for yield. Carinata's physiological response to seeding rate did not depend on land preparation method employed.

Introducing integrated crop-livestock systems into row crop production promotes income diversification and potential soil health benefits through cover crop grazing on degraded soils of the southeastern United States, but effects of these practices on crop yields and soil health in Coastal Plain soils are not well established. A 4-year study was performed to evaluate the effects of grazing a multi-species winter cover crop on soil health and crop yields under mid-February, mid-March, and mid-April cattle removal dates and a non-grazed control within an annual cotton (Gossypium hirsutum L.) and peanut crop rotation (Arachis hypogaea L.). Chemical soil health indicators (soil organic carbon and permanganate oxidizable carbon), physical soil health indicators (water-stable aggregates and penetration resistance), biological soil health indicators (microbial biomass carbon, soil respiration, and arbuscular mycorrhizal fungi colonization), crop yield, and cover crop biomass were evaluated. Cover crop biomass at termination was reduced by 3660, 5250, and 5610 kg ha-1 for the mid-February, mid-March, and mid-April cattle removal treatments compared to the non-grazed control. No grazing treatment effects were observed for biological soil properties. Soil organic carbon was higher in the non-grazed treatment than the mid-April grazing treatment across 0- to 30-cm depth. Penetration resistance across 0- to 50-cm depth and water-stable aggregates at the 0- to 30-cm depth were both negatively impacted by increased grazing period lengths. Results from this study suggest that longer cover crop grazing periods have little effect on biological and chemical soil health indicators in the short term but can negatively impact some physical soil health indicators. Grazing cover crops has minimal effects on biological soil health indicators. Longer grazing periods can have more negative effects on soil physical health indicators. Improvements in soil organic carbon levels were highest in the non-grazed treatment.

Cover crops have been used as an effective soil management practice to enhance soil health. However, this practice may create connected soil pore networks that can cause preferential transport of contaminants to the groundwater or surface water via subsurface flow pathways. The main objective of this study was to compare the effect of cover crops on the soil macropore characteristics in the soil profile. The study was conducted on soil columns collected from E.V. Smith Research Center, Shorter, AL, USA. This study evaluated the influence of cover crop (CC) vs. no cover crop (NC) on soil pore characteristics in strip-tillage cotton (Gossypium hirsutum L.). The cover crop treatment consisted of a mixture of cereal rye (Secale cereale L.) and crimson clover (Trifolium incarnatum L.). Six replicated intact undisturbed soil cores (150 mm diameter and 500 mm deep) were collected for the column study from each treatment class, i.e., CC and NC, and subjected to non-invasive X-ray computed tomography (CT) scanning, giving 0.35-mm-resolution images. The high-resolution images were analyzed in ImageJ to determine all the soil pore characteristics. The results of the comparison of pore characteristics as a function of treatments showed that soil columns under CC had comparatively higher values of porosity and pore number density for the top 100 mm of soil. Pore geometry metrics such as tortuosity did not show significant differences among the treatments (CC vs NC). Connection probability was significantly higher for CC in the subsurface depth class (200–400 mm). Significant correlations were also observed between CT-derived pore characteristics and root characteristics from which it can be inferred that cover crop roots influenced the X-ray CT-derived pore properties. Cover cropping significantly impacted the macropore properties of the strip-till cotton field. This was attributed primarily to the influence of root networks on macropores. Our study’s correlations between root properties and macropore characteristics also indicated that larger root volumes were significantly correlated with complex and irregularly shaped macropores. These variables are critical for a better understanding of the flow dynamics of contaminants through the soil profile and for developing appropriate management strategies.