Significant Yield Research Articles

Electrophysiological and Behavioral Responses of Cabbage Aphid (Brevicoryne brassicae) to Rosemary (Rosmarinus officinalis) Volatiles, a Potential push Plant for Vegetable push-pull Cropping System.

The cabbage aphid (Brevicoryne brassicae) is a major pest of kale (Brassica oleraceae var. acephala), an important vegetable that is grown worldwide due to its high nutritional and economic value. Brevicoryne brassicae poses a great challenge to B. oleraceae var. acephala production, causing significant direct and indirect yield losses. Farmers overly rely on synthetic insecticides to manage the pest with limited success owing to its high reproductive behavior and development of resistance. This necessitates a search for sustainable alternatives to mitigate these challenges. This study assessed behavioral responses of B. brassicae to odors from rosemary (Rosmarinus officinalis) and B. oleraceae var. acephala headspace volatiles in a Perspex four-arm olfactometer. We identified and quantified volatiles emitted by each of the two plants and those eliciting antennal response using coupled gas chromatography-mass spectrometry (GC-MS) and GC-electroantennograhic detection(GC-EAD), respectively. Our findings revealed that B. brassicae spent more time in the arms of the olfactometer that contained B. oleraceae var. acephala volatiles compared to the arm that held R. officinalis volatiles. Additionally, B. brassicae spent more time in the olfactometer arms with B. oleracea var. acephala compared to the arms holding B. oleracea var. acephala and R. officinalis enclosed together and clean air. GC-MS analysis revealed diverse and higher quantities of volatile compounds in R. officinalis compared to B. oleraceae var. acephala. GC-EAD analysis showed that antennae of B. brassicae detected Linalool, α-Terpineol, Verbenone, Geraniol, Camphor, and Borneol from the volatiles of R. officinalis, and Sabinene, γ-Terpinene, and β-Caryophyllene from B. oleraceae var. acephala volatiles.Our findings demonstrate the potential of R. officinalis as a repellent plant against B. brassicae and could be utilized as a 'push' plant in an intercropping strategy against this pest.

Significance of clinical-immunological patterns and diagnostic yield of biopsies in microscopic polyangiitis and granulomatosis with polyangiitis.

Microscopic polyangiitis (MPA) and granulomatosis with polyangiitis (GPA) are the two major antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV). To characterize a homogenous AAV cohort and to assess the impact of clinicopathological profiles and ANCA serotypes on clinical presentation and prognosis. Clinical differences in GPA patients according to ANCA serotype and the diagnostic yield for vasculitis of biopsies in different territories were also investigated. This retrospective study (2000-2021) included 152 patients with AAV (77 MPA/75 GPA). MPA patients (96.1% myeloperoxidase [MPO]-ANCA and 2.6% proteinase 3 [PR3]-ANCA) presented more often with weight loss, myalgia, renal involvement, interstitial lung disease (ILD), cutaneous purpura, and peripheral nerve involvement. Patients with GPA (44% PR3-ANCA, 33.3% MPO, and 22.7% negative/atypical ANCA) presented more commonly with ear, nose, and throat and eye/orbital manifestations, more relapses, and higher survival than patients with MPA. GPA was the only independent risk factor for relapse. Poor survival predictors were older age at diagnosis and peripheral nerve involvement. ANCA serotypes differentiated clinical features in a lesser degree than clinical phenotypes. A mean of 1.5 biopsies were performed in 93.4% of patients in different territories. Overall, vasculitis was identified in 80.3% (97.3% in MPA and 61.8% in GPA) of patients. The identification of GPA presentations associated with MPO-ANCA and awareness of risk factors for relapse and mortality are important to guide proper therapeutic strategies in AAV patients. Biopsies of different affected territories should be pursued in difficult-to-diagnose patients based on their significant diagnostic yield.

Resistance management and integrated pest management insights from deployment of a Cry3Bb1+ Gpp34Ab1/Tpp35Ab1 pyramid in a resistant western corn rootworm landscape.

In Nebraska USA, many populations of western corn rootworm (WCR), Diabrotica virgifera virgifera LeConte, now exhibit some level of resistance to all corn rootworm-active Bacillus thuringiensis Berliner (Bt) proteins expressed in commercial hybrids. Therefore, a study was conducted in northeast Nebraska from 2020-2022 to reevaluate current corn rootworm management options in continuous maize (consecutive planting for ≥2 years). Results from on-farm experiments to evaluate a standard soil-applied insecticide (Aztec® 4.67G) in combination with non-rootworm Bt or rootworm-active Bt pyramided maize (Cry3Bb1 + Gpp34Ab1/Tpp35Ab1) are reported within the context of WCR Bt resistance levels present. Corrected survival from Bt pyramid single-plant bioassays (<0.3, 0.3-0.49, >0.5) was used to place populations into 3 resistance categories. Variables evaluated included root injury, adult emergence, proportion lodged maize, and grain yield. Key results: A composite analysis of all populations across resistance levels indicated that addition of soil insecticide to Bt pyramid significantly reduced adult emergence and lodging but did not significantly increase root protection or yield. Within and among resistance category analyses of root injury revealed that the Bt pyramid remained highly efficacious at any non-rootworm Bt root injury level when resistance was absent or low. When corrected survival was >0.3, mean Bt pyramid root injury tracked more closely in a positive linear fashion with mean non-rootworm Bt root injury (rootworm density x level of resistance interaction). Similar trends were obtained for adult emergence but not yield. Mean Bt pyramid root injury rating was <0.75 in most populations with Bt resistance, which contributed to no significant yield differences among categories. Results are discussed within the context of IPM:IRM tradeoffs and the need to reduce WCR densities in this system to decrease the impact of the density x resistance interaction to bridge use of current pyramids with new technologies introduced over the next decade.

Impact of Invasive Fall Army Worm on Maize Yield and Return Pattern in India: A Comprehensive Analysis

A study was conducted from 2018 to 2022 to investigate the impact of fall armyworm (FAW) invasion on maize cultivation in Karnataka, India. The financial implications and determinants of maize productivity were also determined. Following FAW invasion, cost of cultivation rose significantly to Rs. 69,747 compared to previous year cost of cultivation Rs.63,283 in absence of FAW, attributed to increased expenses on plant protection chemicals, labor, and fertilizer. Plant protection costs at Rs. 3,450 skyrocketed post FAW invasion compared to Rs. 329 before invasion. Whereas non managed fields had a total cost of Rs 61,760. The findings revealed that FAW caused substantial significant yield reduction of 4.14 q/ha in managed fields and 21.74 q/ha in non-managed fields when compared with yield of 49.54 q/ha prior to invasion. The cost of production found to be substantially high (Rs.2,222/q) after FAW invasion in non-managed fields and managed fields (Rs.1,536/q) when compared to prior FAW (Rs.1,277/q). The farmers in study area could able to realize higher returns per rupee of expenditure (1.54) prior to FAW when compared with after FAW invasion with management (1.28) and without management (0.89). The net profit margin of maize cultivation in the study area prior to FAW invasion stood at 35.19 per cent compared to 22.06 per cent after Fall Armyworm invasion with management and -11.71 per cent, without management practices, respectively. The results also revealed net financial impact of FAW invasion on maize cultivation, at Rs. -13,472/ha post invasion even after employing management practices and positive net financial impact of Rs. 26,987.50/ha for implementing FAW management measures when compared with non-managed fields post invasion. The relation between rainfall and productivity was statistically significant at one per cent level of probability with co-efficient value of 1.72. The coefficient value associated with the infestation event (-406.81) was found to be high, indicating a potentially strong relationship between productivity and infestation event.

Host RNAi-mediated silencing of Fusarium oxysporum f. sp. lycopersici specific-fasciclin-like protein genes provides improved resistance to Fusarium wilt in Solanum lycopersicum.

Tomato transgenics expressing dsRNA against FoFLPs act as biofungicides and result in enhanced disease resistance upon Fol infection, by downregulating the endogenous gene expression levels of FoFLPs within Fol. Fusarium oxysporum f. sp. lycopersici (Fol) hijacks plant immunity by colonizing within the host and further instigating secondary infection causing vascular wilt disease in tomato that leads to significant yield loss. Here, RNA interference (RNAi) technology was used to determine its potential in enduring resistance against Fusarium wilt in tomato. To gain resistance against Fol infection, host-induced gene silencing (HIGS) of Fol-specific genes encoding for fasciclin-like proteins (FoFLPs) was done by generating tomato transgenics harbouring FoFLP1, FoFLP4 and FoFLP5 RNAi constructs confirmed by southern hybridizations. These tomato transgenics were screened for stable siRNA production in T0 and T1 lines using northern hybridizations. This confirmed stable dsRNAhp expression in tomato transgenics and suggested durable trait heritability in the subsequent progenies. FoFLP-specific siRNAs producing T1 tomato progenies were further selected to ascertain its disease resistance ability using seedling infection assays. We observed a significant reduction in FoFLP1, FoFLP4 and FoFLP5 transcript levels in Fol, upon infecting their respective RNAi tomato transgenic lines. Moreover, tomato transgenic lines, expressing intended siRNA molecules in the T1 generation, exhibit delayed disease onset with improved resistance. Furthermore, reduced fungal colonization was observed in the roots of Fol-infected T1 tomato progenies, without altering the plant photosynthetic efficiency of transgenic plants. These results substantiate the cross-kingdom dsRNA or siRNA delivery from transgenic tomato to Fol, leading to enhanced resistance against Fusarium wilt disease. The results also demonstrated that HIGS is a successful approach in rendering resistance to Fol infection in tomato plants.

Evaluation and genetic dissection of the powdery mildew resistance in 558 wheat accessions

Powdery mildew, a widespread and destructive wheat disease caused by the fungal pathogen Blumeria graminis f. sp. tritici (Bgt), results in significant yield losses globally. Employing host resistance is the most cost-effective and environmentally sustainable approach to managing this disease. Assessing the resistance levels of wheat germplasms and understanding the genetic underpinnings of this resistance is crucial. In this study, we evaluated the seedling resistance to powdery mildew in 558 wheat accessions, along with the presence of resistance genes Pm1, Pm2, Pm4, Pm5, Pm6, Pm8, Pm12, Pm21, Pm24, Pm41, Pm42, Pm45, Pm47, Pm60, and Pm69 using various Bgt isolates and associated diagnostic markers. The study revealed that out of 558 wheat accessions tested, only 25 showed resistance to the Bgt isolate E09, highlighting a general lack of powdery mildew resistance among the evaluated accessions. Furthermore, these 25 accessions exhibited a significantly different resistance spectrum to 25 additional Bgt isolates. Notably, seven of these accessions were resistant to all the tested isolates, indicating they possess Pm genes with broad-spectrum resistance. Molecular analysis using closely linked or diagnostic markers revealed diverse resistance gene profiles: 249 accessions harbored a single tested Pm gene, 75 accessions possessed combinations of Pm genes, and 234 accessions lacked any of the tested genes. Pm8 was the most frequently detected gene, present in 27.42% of accessions, whereas Pm5, Pm12, Pm24, Pm41, Pm42, Pm45, Pm47 and Pm69 were not detected. Among the seven accessions resistant to all 26 tested isolates, Pm21 was detected in four accessions (HengS29, Chang 4640, Xinong 556, and ML728). Pm2 and Pm60 were identified in Emai 18 and Xinmai 296, respectively. Interestingly, none of the tested genes were detected in Emai 16, suggesting the presence of potentially novel Pm gene(s) conferring broad-spectrum resistance. These findings offer valuable insights for the strategic dissemination of these resistant accessions and for targeted breeding programs aimed at combating powdery mildew.

First report of the maize cyst nematode Heterodera zeae in Sichuan Province of Southwest China.

Maize is the largest crop planted in China. Nine species of cyst nematodes have been reported to affect maize production. Heterodera zeae, H. avenae and Punctodera chalcoensis can cause significant maize yield losses annually (Luc et al. 2005). In 1971, the maize cyst nematode H. zeae was first detected in Rajasthan, India (Koshy et al. 1971). Subsequently, it has been reported in many other countries such as the United States, Greece, Pakistan, and Egypt. In China, H. zeae was first identified in the maize fields of Laibin City, Guangxi Zhuang Autonomous Region (Wu et al., 2017). Cui et al. (2020) identified H. zeae in a maize field of Yuzhou City, Henan Province of Central China in 2018. From 2018 to 2022, a survey of cyst-forming nematodes was conducted in Southwest China. Fifteen soil samples of about 500 g each were collected from Luding County, Ganzi Prefecture of Sichuan Province. No major aboveground symptoms were shown on maize, but a few females were observed on the roots of maize in one field. The cysts and second-stage juveniles (J2s) were collected from each soil sample using Cobb's screening gravity method. A total of 8.50±2.0 cysts per 100 ml of soil on the average were observed in the field. A thin subcrystalline layer was discernible only in young cysts. Morphological and molecular studies of cysts and J2s indicated that the nematodes were identified to be H. zeae in a maize-field. Morphologically, the cysts were in a lemon shape, light brown or pearly white in color. The vulval cone was prominent. Fenestra ambifenestrate, and semifenestra were separated by a fairly wide vulval bridge, fenestral length and width were variable, and the cyst wall was shown in a zigzag pattern. The J2s' body was in a vermiform, tapering at both ends, with a hyaline tail. Stylet was strongly developed with round or slightly anteriorly directed knobs. Morphological measurements of the cysts (n = 9) determined that the mean body length was 417.2 μm (403.6 to 439.4 μm), body width was 429.7 μm (397.6 to 456.9μm); length-width ratio was 1.4 (0.75 to 3); fenestra length was 525.3 μm (498.5 to 570.7 μm); and the mean semifenestra width was 458.6 μm (403.6 to 546.3 μm). Morphometric measurements of second-stage juveniles (n = 20) showed a body length of 419.7μm (355.8 to 492.5 μm); a stylet length of 20.8 μm (19.51 to 23.3μm); a tail length of 41.5 μm (20 to 49.4 μm); and a hyaline tail length of 20.7 μm (16.6 to 24 μm). The main morphological characteristics and measured values were basically consistent with those described by Cui et al. (2022), and all of which were similar to those of H. zeae. Amplification of DNA from random single cysts (n = 5) was conducted using the protocol described by Cui et al. (2022). The rDNA-internal transcribed spacer (ITS) was amplified and sequenced using a pair of universal primers TW81 (5'-GTTTCCGTAGGTGAA CCTGC-3') and AB28 (5'-ATATGCTTAAGTTCAGCGGGT-3'). The ITS sequences were deposited at GenBank with the accession number OR811029.1. Alignments of sequences showed an identity of 98% with H. zeae sequences from China (OP692769.2, MW785772.1) and the USA (GU145616.1), which were confirmed using a pair of species-specific primers HzF1 (5'-GGGGAGGTGAATGTGGG-3') and HzR1 (5'-CCTTTGGCAATCGGTGA-3') of H. zeae with a targeted PCR fragment of 393 bp (Cui et al. 2022). Pathogenicity was conducted and confirmed by infection and reproduction on maize. Seeds (cv. Zhengda 619) were sown in three pots that contained 150 ml of a sterile soil mixture (loamy soil: sand=1:1), and 5 cysts (103 eggs/cyst on the average) were inoculated in each pot at 25/30°C, under a 12-h dark/12-h light condition (Cui et al. 2023). Fifteen days after sowing, third- and fourth-stage juveniles were observed in the rootstained with acid fuchsin, and a total of 32 cysts per maize plant on the average were collected at 40 days after sowing. The new cysts' morphological and molecular characteristics were identical to the cysts from the original soil samples. To the best of our knowledge, this is the first report of H. zeae as a pathogen on maize in Sichuan Province, Southwest China. Our findings will be useful for management and further research of maize cyst nematodes.

Crescimento e produção do feijão-caupi sob estresse hídrico e cobertura de solo

ABSTRACT Cowpea is a crop of high socioeconomic importance for the semi-arid region of Brazil, although facing significant yield losses due to drought, requiring management strategies to overcome this scenario. From this perspective, this study aimed to evaluate the growth and yield of cowpea genotypes under drought in different cultivation systems. The statistical design was randomized blocks arranged in a 2 × 4 × 2 factorial scheme corresponding to two cowpea genotypes (BRS Pujante and Costela de Vaca), four levels of crop evapotranspiration (40, 60, 80, and 100%), and two cultivation systems (with and without soil mulching). The BRS Pujante showed a higher leaf area and 100-grain weight than Costela de Vaca under all levels of crop evapotranspiration. The cowpea yield parameters showed the best results at 80 and 100% crop evapotranspiration. Regardless of the genotype, soil mulching provided higher cowpea 100-grain weight values. Soil mulching combined with 80% crop evapotranspiration is an appropriate strategy for cowpea production.

First Report of Fusarium culmorum Causing Crown Rot on Wheat in Jordan

First Report of <i>Fusarium culmorum</i> Causing Crown Rot on Wheat in Jordan

Identification of Resistance to Target Spot of Tomato Caused by Corynespora cassiicola in Wild Tomato Accessions

Tomato (Solanum lycopersicum) is an important vegetable crop and a valuable source of nutrients for the human diet. The southeast is the main fresh market tomato producer of the United States, with much of the production concentrated in Florida. However, production in this region is threatened by plant diseases such as target spot of tomato (TS) caused by Corynespora cassiicola, a multitrophic fungus widely distributed in tropical and subtropical areas. TS can infect foliage and fruit, often resulting in significant yield losses in conductive environments. There are no known TS-resistant cultivars, and control relies entirely on fungicidal sprays. However, several studies have demonstrated that the fungus is developing resistance to commonly used fungicides which further complicates disease management. The objective of this work was to identify sources of resistance to TS from wild Solanum accessions. Initial screens of 83 accessions informed the selection of 24 accessions for a more robust screening in which six diverse C. cassiicola isolates were used for single-isolate inoculation experiments. The results from a broad-sense mixed-model analysis including data from all six experiments demonstrated that all 24 accessions had significantly lower disease severities compared with the susceptible controls, suggesting that all accessions potentially harbor resistance quantitative trait loci (QTLs). Solanum cheesmaniae accession LA0524, S. galapagense accessions LA0483 and LA0532, and S. pimpinellifolium accession LA2093 were among the most resistant accessions tested and may be particularly useful for introgression of resistance into cultivated germplasm and for mapping of TS resistance QTLs.

Biocontrol strategies against Botrytis cinerea in viticulture: evaluating the efficacy and mode of action of selected winemaking yeast strains.

Botrytis cinerea poses a recurring threat to viticulture, causing significant yield losses each year. The study explored the biocontrol capabilities of commercially used winemaking yeasts as a strategy to manage B. cinerea in grape berries. The winemaking yeast strains-Saccharomyces cerevisiae ES181, Saccharomyces pastorianus KBG6, S. cerevisiae BCS103, Lachancea thermotolerans Omega, and Torulaspora delbrueckii TD291-reduced B. cinerea growth and conidiation in vitro. Furthermore, they demonstrated a decreased disease severity and number of conidia in grape berries. Among these strains, S. cerevisiae BCS103 was the most effective, inducing the expression of the defense-related gene PR4 in berries. Its diffusible compounds and volatile organic compounds also reduced the expression of BcLTF2, a positive regulator of B. cinerea conidiogenesis. The examined winemaking yeast strains, especially S. cerevisiae BCS103, demonstrated effective inhibition of B. cinerea in vitro and in grape berries, influencing key defense genes and reducing BcLTF2 expression, offering potential solutions for disease management in viticulture. The study underscores the promise of commercially available winemaking yeast strains as eco-friendly tools against B. cinerea in viticulture. Leveraging their safety and existing use in winemaking offers a potential avenue for sustainable disease management.

Identification and characterization of novel resistant genotypes of Gymnema sylvestre (Retz.) R. Br. ex Sm. against invasive mealybug species, Phenacoccus solenopsis Tinsley and Paracoccus marginatus Williams and Granara de Willink for sustainable pest management

Madhunashini, Gymnema sylvestre R. Br. ex Sm. (F: Asclepiadaceae) is an important industrial medicinal plant that has various pharmacological properties like antidiabetic, antiobesity, anticarcinogenic and neuroprotective. The invasive mealybugs, i.e., Phenacoccus solenopsis and Paracoccus marginatus, are causing significant yield losses to G. sylvestre in India. The identity of the mealybug species, P. solenopsis and P. marginatus, were confirmed both morphologically and molecularly by using Cytochrome c oxidase subunit I (COI) gene with (GenBank Accession No. OQ349395 and OQ358124). The pest incidence occurs throughout the year, but its peak activity was observed during the summer months (April to August). In the current investigation, 30 genotypes were examined for their resistance against mealybugs in their natural field environment for three consecutive years from 2019 to 2021 in the geographical region of Anand, Gujarat, India. The pooled analysis showed that the severity of infestation ranged between 0.41 and 3.57. Our study results revealed that 10% of the genotypes i.e. DGS-18, DGS-26, and DGS-28, were highly resistant. Furthermore, 16.66% of the genotypes, i.e. DGS-13, DGS-15, DGS-22, DGS-30, and DGS-33 were categorized as resistant. The novel resistant genotypes identified in the present study will be helpful for the management of P. solenopsis and P. marginatus, in G. sylvestre. The resistant genotypes have excellent scope for reducing the use of pesticide usage as well as help in mitigating pesticide residue.

Mitigation of water stress by compost and arginine application and its impacts on barley production

BackgroundWater-scarce locations necessitate the deployment of creative and sustainable techniques for managing water for agricultural production. Field experiment was conducted at the Experimental Research Farm of National Research Centre, Nubaria region, Egypt to alleviate the harmful effect of water stress on the yield of Mediterranean barley varieties (Giza 125, Tombari, Ksar Megrine and Tamellat) by compost (0.0, 2.0, 4.0, 6.0-ton fed−1) and arginine application (0.00 and 1000 ppm) under deficit irrigation. The amounts of irrigation water applied were “900 and 450” m3 fed−1 to sufficient irrigation and deficit irrigation, respectively.ResultsThe greatest and most significant values of the chlorophyll values and relative water content values obtained at the treatment supplied with 6.0-ton compost fed−1 and sprayed with Arginine. There was a significant dramatic decrease in proline content with increasing compost application rates and treated barley plants by Arginine for all the studied barley varieties under both studied irrigation treatments. Increasing compost application rate is associated with significant increase in number of spike m−2 without or with arginine. Barley Tombari variety received 6.0-ton compost fed−1 gained changes to give a greatest significant value of grain (ton fed−1) under sufficient irrigation and Tamellat under deficit irrigation situation. The significant maximum values of the grain yield (1.96- and 2.09-ton fed−1) were attained at Tombari and Tamellat varieties which received 6.0-ton fed−1 compost with or without arginine under sufficient irrigation. The increases in compost rate increment changes to incremented grain yield values with arginine application more than untreated one. The greatest and significant grain yield was found at the treatment received 6.0-ton compost fed−1 with arginine foliar application.ConclusionCompost application has an important role in maintaining greatest water use efficiency for plant and arginine application reported to contribute in reduction in destructive effects of a biotic stress thus their importance in increasing the barley production under water stress.

The mechanisms behind the contrasting responses to waterlogging in black-grass (Alopecurus myosuroides) and wheat (Triticum aestivum).

Black-grass (Alopecurus myosuroides ) is one of the most problematic agricultural weeds of Western Europe, causing significant yield losses in winter wheat (Triticum aestivum ) and other crops through competition for space and resources. Previous studies link black-grass patches to water-retaining soils, yet its specific adaptations to these conditions remain unclear. We designed pot-based waterlogging experiments to compare 13 biotypes of black-grass and six cultivars of wheat. These showed that wheat roots induced aerenchyma when waterlogged whereas aerenchyma-like structures were constitutively present in black-grass. Aerial biomass of waterlogged wheat was smaller, whereas waterlogged black-grass was similar or larger. Variability in waterlogging responses within and between these species was correlated with transcriptomic and metabolomic changes in leaves of control or waterlogged plants. In wheat, transcripts associated with regulation and utilisation of phosphate compounds were upregulated and sugars and amino acids concentrations were increased. Black-grass biotypes showed limited molecular responses to waterlogging. Some black-grass amino acids were decreased and one transcript commonly upregulated was previously identified in screens for genes underpinning metabolism-based resistance to herbicides. Our findings provide insights into the different waterlogging tolerances of these species and may help to explain the previously observed patchiness of this weed's distribution in wheat fields.

The diagnostic yield of a 2-h versus a 30-min electroencephalogram for patients with altered mental status in neurological intensive care unit

BackgroundThe continuous electroencephalogram (cEEG) monitoring is recommended for critical ill patients with altered mental status, The cEEG detects seizure activity and nonconvulsive status epilepticus (NCSE) more efficiently than routine electroencephalogram (rEEG). Yet, cEEG is not widely available in many neurological intensive care units (NICU) in limited resource countries. Ideal study duration, and whether cEEG is useful and cost-effective in terms of patient outcome compared to (rEEG), is still questions under research. The main objective in our study was the relative diagnostic yield of the 2 h, prolonged EEG recording, compared to the 30-min rEEG recording in the NICU.ResultsThere was no significant diagnostic yield for the 2-h electroencephalogram (EEG) over the 30-min EEG for patient with altered mental status in the NICU. Being with altered mental state in an NICU carries a poor outcome, we found that death occurred in 68.9% of patients. Acute ischemic stroke is the most common cause of altered mental status in NICU by about 53.3% of patients. Less than half of the patients (42.2%) were receiving anti-seizure medications (ASM).ConclusionsAs long as the cEEG is not available in the NICU, the 30-min EEG has a good diagnostic yield and it is almost equivalent to the prolonged 2-h EEG, and if the EEG is recommended for a longer duration, we recommend a long-term EEG more than 2 h.

Transcriptomic analysis identifies candidate genes for Aphanomyces root rot disease resistance in pea

BackgroundAphanomyces euteiches is a soil-borne oomycete that causes root rot in pea and other legume species. Symptoms of Aphanomyces root rot (ARR) include root discoloration and wilting, leading to significant yield losses in pea production. Resistance to ARR is known to be polygenic but the roles of single genes in the pea immune response are still poorly understood. This study uses transcriptomics to elucidate the immune response of two pea genotypes varying in their levels of resistance to A. euteiches.ResultsIn this study, we inoculated roots of the pea (P. sativum L.) genotypes ‘Linnea’ (susceptible) and ‘PI180693’ (resistant) with two different A. euteiches strains varying in levels of virulence. The roots were harvested at 6 h post-inoculation (hpi), 20 hpi and 48 hpi, followed by differential gene expression analysis. Our results showed a time- and genotype-dependent immune response towards A. euteiches infection, involving several WRKY and MYB-like transcription factors, along with genes associated with jasmonic acid (JA) and abscisic acid (ABA) signaling. By cross-referencing with genes segregating with partial resistance to ARR, we identified 39 candidate disease resistance genes at the later stage of infection. Among the genes solely upregulated in the resistant genotype ‘PI180693’, Psat7g091800.1 was polymorphic between the pea genotypes and encoded a Leucine-rich repeat receptor-like kinase reminiscent of the Arabidopsis thaliana FLAGELLIN-SENSITIVE 2 receptor.ConclusionsThis study provides new insights into the gene expression dynamics controlling the immune response of resistant and susceptible pea genotypes to A. euteiches infection. We present a set of 39 candidate disease resistance genes for ARR in pea, including the putative immune receptor Psat7g091800.1, for future functional validation.

CDC Kernen oilseed flax

CDC Kernen, a late maturing oilseed flax ( Linum usitatissimum L.), was registered in 2021 by the Crop Development Centre, University of Saskatchewan, Saskatoon, Saskatchewan. This cultivar had a significant yield advantage (107%) compared to CDC Glas (the yield check) in all soil zones of the Northern Prairies. The yield of CDC Kernen was 115%, 98%, and 105% of CDC Glas in the Black, Brown, and Black and Grey soil zones of Western Canada, respectively. This cultivar has medium (45.1%) oil content, oil quality (iodine value (IV) 192; alpha linolenic acid content 57.1%), equivalent to CDC Glas (the seed quality standard) coupled with larger seed size (thousand seed weight 6.1 g) than CDC Glas. It is immune to North American rust (race 371) caused by Melampsora lini and moderately resistant to wilt caused by Fusarium oxysporum f. sp. lini and powdery mildew caused by Oidium lini.

Detecting and counting sorghum aphid alates using smart computer vision models

Sorghum aphid [Melanaphis sorghi (Theobald)] is considered an economic pest causing significant yield losses in susceptible sorghum in the southern U.S. Infestations start with the migration of alates (i.e., winged adults) to sorghum and establishing aphid colonies. In favorable conditions, sorghum aphid can exponentially reproduce via asexual reproduction. A suggested strategy is to monitor alates to determine initial infestations and take preventive strategies, which can result in more efficient pest monitoring and management. To reduce the time of monitoring and better understand of alate establishment under field conditions, we propose using computer vision models, specifically deep learning, to detect and count alates using field-collected images. During pest monitoring, we captured 2527 images and assessed the performance of five models within the YOLOv5 architecture family using two different image sizes, including input resolutions of 640 × 640, and 1280 × 1280 pixels. We trained models to detect and count individual alates, which ranged between 1 and 100 alates/leaf. Among models, the YOLOv5l Pytorch detection model had the best overall performance at 1280 × 1280 input pixel resolution. The YOLOv5l model is a candidate model for quantifying alates on sorghum leaves using deep learning with a precision of 83.80%, 85.60% recall, and 89% mAP@0.5 with a lower mean percent error of misdetection. To enable the use of our best deep learning model by the research community, we developed a web-based application that is freely available to the public. Using this application, users can upload images to detect and count alates with a low error of misdetection.

Gradual Emergence of East African cassava mosaic Cameroon virus in Cassava Farms in Côte d’Ivoire

Cassava mosaic disease (CMD) and cassava brown streak disease (CBSD) are endemic threats to cassava production, causing significant yield losses. They are caused respectively by begomoviruses and ipomoviruses that are transmitted by whiteflies and infected cuttings. This study aimed to monitor and characterize viruses responsible for these diseases in order to fill existing gaps in understanding their epidemiology in Côte d’Ivoire. Field surveys were conducted in 2016, 2017, and 2020, and no CBSD symptoms were observed. However, an increase in CMD incidence was noted from 45.95% in 2016 to 51.37% in 2020, while CMD severity remained moderate over the years with a mean value of 2.29. The number of whiteflies was relatively low and decreased over the years. Molecular diagnostics carried out on cassava leaf samples allowed the detection of East African cassava mosaic Cameroon virus (EACMCMV) that occurs in single as well as in mixed infection with African cassava mosaic virus (ACMV). Single EACMCMV infection, which was detected only in three agroecological zones of eastern Côte d’Ivoire in 2016, spread throughout the country in 2017 and became more widespread in 2020 with a preponderance in central and southern zones, whereas ACMV and EACMCMV coinfection has spread to the entire zones. Phylogenetic analysis of the viral isolates showed that they are closely related to those from Burkina Faso, Ghana, and Nigeria. This changing population of cassava virus species constitutes a serious threat to cassava cultivation. Understanding the evolutionary dynamics of these viruses could help in adopting better disease management strategies to control the disease.

Enhancing plant leaf disease detection: Integrating krill herd optimization-surf features and deep belief network

A plant disease that attacks the leaf causes significant yield and market value losses. A professional plant pathologist should be able to visually identify the disease by looking at the affected plant leaves, but this is unlikely to result in a more accurate diagnosis. Disease symptoms should be immediately recognisable in order to stop the spread of the illness. To find plant diseases, steps should be taken using computer assisted technologies. Numerous methods for identifying plant diseases using machine learning (ML) and deep learning (DL) have been developed and tested in numerous studies. Machine learning has the disadvantages of having a small dataset, taking longer, and requiring more time for results interpretation. Deep learning is suggested as a solution to this. This study compares the effectiveness of both ML&amp;DL for plant leaf disease identification with more recent investigations. The common deep learning technique involves utilising the Krill Herd Optimisation Algorithm (KHO) to segment images and the Speeded up Robust Features (SURF) to extract the images. The Artificial Bee Colony (ABC) then chooses the features. Then, a Deep Belief Network (DBN) can be used to classify the chosen image. Multiple diseases can be identified on the same leaf using this method. This study demonstrates that deep learning outperforms machine learning in terms of results. The outcome demonstrates that the deep learning method is superior for the diagnosis of plant disease when there is sufficient data available. Using this technique, the validity and consistency were also examined.