Sorghum Heads Research Articles

Extraction Optimization, Structural Analysis, and Potential Bioactivities of a Novel Polysaccharide from Sporisorium reilianum.

Sporisorium reilianum is an important biotrophic pathogen that causes head smut disease. Polysaccharides extracted from diseased sorghum heads by Sporisorium reilianum exhibit significant medicinal and edible value. However, the structure and biological activities of these novel polysaccharides have not been explored. In this study, a novel polysaccharide (WM-NP'-60) was isolated and purified from the fruit bodies of S. reilianum and aimed to explore the structural characteristics and substantial antioxidant and antitumor properties of WM-NP'-60. Monosaccharide composition determination, periodate oxidation-Smith degradation, 1D/2D-NMR analysis, and methylation analysis revealed that WM-NP'-60 consisted mainly of β-1,6-D-Glcp, β-1,3-D-Glcp, and β-1,3,6-D-Glcp linkages. The antioxidant assays demonstrated that WM-NP'-60 exhibited great activities, including scavenging free radicals, chelating ferrous ions, and eliminating reactive oxygen species (ROS) within cells. The HepG2, SGC7901, and HCT116 cells examined by transmission electron microscopy (TEM) revealed typical apoptotic bodies. Therefore, a novel fungal polysaccharide (WM-NP'-60) was discovered, extracted, and purified in this experiment, with the aim of providing a reference for the development of a new generation of food and nutraceutical products suitable for human consumption.

Effect of Productive Tillers on Seed Yield and Seed Quality of Sorghum (<i>Sorghum bicolor L</i>.) Varieties in Assosa District, Western Ethiopia

Poor management of sorghum tillers is a significant problem in the Benishangul-Gumuz region of Ethiopia, affecting seed yield and quality. An experiment was conducted to determine the impact of sorghum productive tillers on seed yield and quality. The study involved two Sorghum varieties (Assosa-1 and Adukara) and three plant types per spot. The treatments were aligned as RCBD and CRD in factorial combination, replicated three and four times for field and laboratory experiments respectively. Varieties influenced TSW (P < 0.0001), Number of tiller influenced by number plants head matured for seed production (P ≤ 0.0001), plants height (P ≤ 0.0004), The interaction effects of varieties and number of tillers per plant influenced yields, Panicle length (P < 0.0001). For laboratory experiments varieties influenced Speed of germination (P < 0.0001), number of Dead seeds (P < 0.0001). Number of tiller influenced Speed of germination (P < 0.0001), number of Dead seeds, shoot length (P < 0.004), Vigor index one and Vigor index two (P≤0.05). The interaction effects of varieties and number of tillers per plant influenced Standard germination (P < 0.001). The main shoot plants had the highest number of fertile sorghum heads (86.5), followed by primary tillers (27.08). Secondary tillers had the highest plant height (96.52 cm). The main shoot plant yielded more seeds than primary and secondary tillers, with the shoot exceeding these yields by 302.96% and 1333%, respectively. Primary and secondary tillers had higher percentages of dead seeds than the main shoot plant, 53.5% and 45.2%, respectively. The primary and secondary tillers experienced a decline in seedling vigour index one over different periods, while the main sorghum plant varieties, Adukara and Assosa-1, showed an upward trend. The germination percentages of the primary and secondary tillers were less than the 85% Ethiopian seed standard requirement. Because sorghum tillers lower seed quality, they should be eliminated for seed production. If sorghum is grown for grain production, secondary tillers have the benefit of raising overall yield production.

Comparison of Deep Learning Methods for Detecting and Counting Sorghum Heads in UAV Imagery

With the rapid development of remote sensing with small, lightweight unmanned aerial vehicles (UAV), efficient and accurate crop spike counting, and yield estimation methods based on deep learning (DL) methods have begun to emerge, greatly reducing labor costs and enabling fast and accurate counting of sorghum spikes. However, there has not been a systematic, comprehensive evaluation of their applicability in cereal crop spike identification in UAV images, especially in sorghum head counting. To this end, this paper conducts a comparative study of the performance of three common DL algorithms, EfficientDet, Single Shot MultiBox Detector (SSD), and You Only Look Once (YOLOv4), for sorghum head detection based on lightweight UAV remote sensing data. The paper explores the effects of overlap ratio, confidence, and intersection over union (IoU) parameters, using the evaluation metrics of precision P, recall R, average precision AP, F1 score, computational efficiency, and the number of detected positive/negative samples (Objects detected consistent/inconsistent with real samples). The experiment results show the following. (1) The detection results of the three methods under dense coverage conditions were better than those under medium and sparse conditions. YOLOv4 had the most accurate detection under different coverage conditions; on the contrary, EfficientDet was the worst. While SSD obtained better detection results under dense conditions, the number of over-detections was larger. (2) It was concluded that although EfficientDet had a good positive sample detection rate, it detected the fewest samples, had the smallest R and F1, and its actual precision was poor, while its training time, although medium, had the lowest detection efficiency, and the detection time per image was 2.82-times that of SSD. SSD had medium values for P, AP, and the number of detected samples, but had the highest training and detection efficiency. YOLOv4 detected the largest number of positive samples, and its values for R, AP, and F1 were the highest among the three methods. Although the training time was the slowest, the detection efficiency was better than EfficientDet. (3) With an increase in the overlap ratios, both positive and negative samples tended to increase, and when the threshold value was 0.3, all three methods had better detection results. With an increase in the confidence value, the number of positive and negative samples significantly decreased, and when the threshold value was 0.3, it balanced the numbers for sample detection and detection accuracy. An increase in IoU was accompanied by a gradual decrease in the number of positive samples and a gradual increase in the number of negative samples. When the threshold value was 0.3, better detection was achieved. The research findings can provide a methodological basis for accurately detecting and counting sorghum heads using UAV.

Improving deep learning sorghum head detection through test time augmentation

The continuous growth of the world’s population requires immediate action to ensure food security. Sorghum is among the five most-produced cereals and is a dietary staple in many developing countries. Therefore, it is of great importance to obtain precise information for improving cereal productivity. An indicator for estimating sorghum yields is the number of crop heads in different branching arrangements. Approaches based on image processing and artificial intelligence have proved useful for automatically and efficiently obtaining this type of information for different crops. However, their application to sorghum crops presents some additional challenges owing to differences in the shape and color of sorghum heads. In this study, a methodology to detect sorghum heads in unmanned aerial vehicle imagery was investigated, and its performance was evaluated using a standard quality index in object detection problems (mean average precision). Specifically, test-time-augmentation (TTA) techniques have been implemented using a set of geometrical and color transformations selected according to the sorghum plant imagery requiring analysis, as well as four different ensemble learning methods. Because these methods are weighted, two different approaches for calculating these weights to improve sorghum head detection have been proposed. The results show that in sorghum head detection, TTA strategies outperform detection based only on individual transformed testing sets. Moreover, these results were improved by the use of different weights during the ensemble of TTA results.

Detecting Sorghum Plant and Head Features from Multispectral UAV Imagery.

In plant breeding, unmanned aerial vehicles (UAVs) carrying multispectral cameras have demonstrated increasing utility for high-throughput phenotyping (HTP) to aid the interpretation of genotype and environment effects on morphological, biochemical, and physiological traits. A key constraint remains the reduced resolution and quality extracted from “stitched” mosaics generated from UAV missions across large areas. This can be addressed by generating high-quality reflectance data from a single nadir image per plot. In this study, a pipeline was developed to derive reflectance data from raw multispectral UAV images that preserve the original high spatial and spectral resolutions and to use these for phenotyping applications. Sequential steps involved (i) imagery calibration, (ii) spectral band alignment, (iii) backward calculation, (iv) plot segmentation, and (v) application. Each step was designed and optimised to estimate the number of plants and count sorghum heads within each breeding plot. Using a derived nadir image of each plot, the coefficients of determination were 0.90 and 0.86 for estimates of the number of sorghum plants and heads, respectively. Furthermore, the reflectance information acquired from the different spectral bands showed appreciably high discriminative ability for sorghum head colours (i.e., red and white). Deployment of this pipeline allowed accurate segmentation of crop organs at the canopy level across many diverse field plots with minimal training needed from machine learning approaches.

TasselNetV2+: A Fast Implementation for High-Throughput Plant Counting From High-Resolution RGB Imagery.

Plant counting runs through almost every stage of agricultural production from seed breeding, germination, cultivation, fertilization, pollination to yield estimation, and harvesting. With the prevalence of digital cameras, graphics processing units and deep learning-based computer vision technology, plant counting has gradually shifted from traditional manual observation to vision-based automated solutions. One of popular solutions is a state-of-the-art object detection technique called Faster R-CNN where plant counts can be estimated from the number of bounding boxes detected. It has become a standard configuration for many plant counting systems in plant phenotyping. Faster R-CNN, however, is expensive in computation, particularly when dealing with high-resolution images. Unfortunately high-resolution imagery is frequently used in modern plant phenotyping platforms such as unmanned aerial vehicles, engendering inefficient image analysis. Such inefficiency largely limits the throughput of a phenotyping system. The goal of this work hence is to provide an effective and efficient tool for high-throughput plant counting from high-resolution RGB imagery. In contrast to conventional object detection, we encourage another promising paradigm termed object counting where plant counts are directly regressed from images, without detecting bounding boxes. In this work, by profiling the computational bottleneck, we implement a fast version of a state-of-the-art plant counting model TasselNetV2 with several minor yet effective modifications. We also provide insights why these modifications make sense. This fast version, TasselNetV2+, runs an order of magnitude faster than TasselNetV2, achieving around 30 fps on image resolution of 1980 × 1080, while it still retains the same level of counting accuracy. We validate its effectiveness on three plant counting tasks, including wheat ears counting, maize tassels counting, and sorghum heads counting. To encourage the use of this tool, our implementation has been made available online at https://tinyurl.com/TasselNetV2plus.

Potential of Sorghum bicolor L. (Moench) and the Effectiveness of Some Organic Amendments in Remediation of Petroleum Oil-Vitiated Soils of an Automobile Repair Workshop in Urbanite Kampala

Aims: To determine the potential of sweet sorghum (Epuripur 1995) and the effect of organic biostimulators: NPK fertilizer, cow dung and sewage sludge in remediation of petroleum oil-adulterated soils from a garage in Kampala Metropolis, Uganda.
 Place and Duration of Study: The contaminated soils were obtained from New Katanga Boys automobile repair workshop in Wandegeya, Kampala, Uganda. Experiments were conducted between September 2018 to November 2018 at Department of Food Processing Technology, College of Agriculture and Environmental Sciences, Makerere University, Kampala, Uganda.
 Methodology: 50 kg of petroleum oil-contaminated soils were collected from the garage and divided into 5 kg portions; four portions were potted with four sorghum grains with three subjected to 5% w/w amendment using NPK fertilizer, cow dung and sewage sludge under normal growth conditions for 72 days. Representative soil samples were collected from spots at 0-10 cm and 10-20 cm from the potted soils and subjected to Soxhlet extraction. Growth parameters (leaf surface area, root mass and mass of sorghum heads) of the potted plants were measured.
 Results: The sorghum plants grew normally and survived in the petroleum-contaminated soils. Sorghum potted in contaminated soil without any amendment did not flower. Amendment of the vitiated soils with NPK fertilizer, cow dung and sewage sludge biostimulated the phytoremediation capacity of sorghum by 9.1%, 12.5% and 6.3% respectively.
 Conclusion: Addition of cow dung to spent-oil contaminated soils could make such soils fully re-established for agricultural activities. Further research should assess the chemical properties of the investigated vitiated soils and the effectiveness of other biostimulants such as vermicompost in biostimulating phytoremediation by Sorghum bicolor. The potential of other cereals such as corn, barley, rye and millet in phytoremediation of petroleum-adulterated soils should be investigated.

Aerial Imagery Analysis - Quantifying Appearance and Number of Sorghum Heads for Applications in Breeding and Agronomy.

Sorghum (Sorghum bicolor L. Moench) is a C4 tropical grass that plays an essential role in providing nutrition to humans and livestock, particularly in marginal rainfall environments. The timing of head development and the number of heads per unit area are key adaptation traits to consider in agronomy and breeding but are time consuming and labor intensive to measure. We propose a two-step machine-based image processing method to detect and count the number of heads from high-resolution images captured by unmanned aerial vehicles (UAVs) in a breeding trial. To demonstrate the performance of the proposed method, 52 images were manually labeled; the precision and recall of head detection were 0.87 and 0.98, respectively, and the coefficient of determination (R2) between the manual and new methods of counting was 0.84. To verify the utility of the method in breeding programs, a geolocation-based plot segmentation method was applied to pre-processed ortho-mosaic images to extract >1000 plots from original RGB images. Forty of these plots were randomly selected and labeled manually; the precision and recall of detection were 0.82 and 0.98, respectively, and the coefficient of determination between manual and algorithm counting was 0.56, with the major source of error being related to the morphology of plants resulting in heads being displayed both within and outside the plot in which the plants were sown, i.e., being allocated to a neighboring plot. Finally, the potential applications in yield estimation from UAV-based imagery from agronomy experiments and scouting of production fields are also discussed.

Effective Control of a Field Population of Helicoverpa armigera by Using the Small RNA Virus Helicoverpa armigera Stunt Virus (Tetraviridae: Omegatetravirus)

The first comprehensive field trial using an insect small RNA virus as a control agent on a cropping system was conducted with the Helicoverpa armigera stunt virus (family Tetraviridae, genus Omegatetravirus, HaSV). The virus was semipurified, quantified, and applied at two rates, 4 x 10(15) and 4 x 10(14) virus particles/ha, with minimal formulation on sorghum against the bollworm Helicoverpa armigera (Hübner). For comparison, a commercial preparation of Helicoverpa zea single-nucleopolyhedrovirus (HzSNPV, Gemstar) was applied at the same time at 9.27 x 10(11) polyhedral inclusion bodies/ha. The HaSV application rates were determined by a novel procedure using laboratory LC50 bioassay data for HaSV and HzSNPV and calibration to the known field application rate of the HzSNPV. The baculovirus and the higher rate of HaSV produced statistically equivalent reductions in the larval populations of around 50% at both 3 and 6 d postapplication (dpa) compared with untreated plots. The 10-fold lower rate of HaSV reduced the larval population by 50% at 3 dpa and approximately 30% at 6 dpa. Persistence of HaSV over a 72-h period was found to be similar to that of HzSNPV, although the amount of HaSV available on the sorghum heads increased at 130 h postapplication, due most likely to dispersal of newly produced virus from cadavers and frass. The results from this trial indicate that HaSV could be used as an effective biopesticide for the control of H. armigera in sorghum and the ramifications for its broader use are discussed.

Does the Systemic Insecticide Imidacloprid (Gaucho) Have a Direct Effect on Yield of Grain Sorghum?

Gaucho1 (imidacloprid; l-[(6-chloro-3-pyridinyl)methyl]-N-nitro-2-imidazolidinimine) is a seed treatment insecticide widely used on sorghum [Sorghum bicolor (L.) Moench] to control a number of pests, including greenbugs [Schizaphis graminum (Rondani)], chinch bugs [Blissus leucopterus leucopterus (Say)], and wireworms (Limonius sp.). A series of tests was conducted at five locations in Kansas during 1996 and 1997 and three locations during 1998 to determine whether a yield response results even in the absence of pests when Gaucho is used as a seed treatment on grain sorghum. Results varied. Gaucho improved yields at Hesston, especially in the June plantings but some hybrids benefited more than others. These differences may have been due to chinch bugs that were observed in the plots and were known to be troublesome in the area. Because their numbers were low, other factors may have played a role. At the other locations and in the absence of chinch bugs, Gaucho had less of an influence on yields. At Garden City, where some greenbugs developed, Gaucho provided early-season control, but infestations were too light to influence yields. At Hays, Gaucho treatments appeared to have some influence on the numbers of corn earworms [Helicoverpa zea (Boddie)] in sorghum heads in one planting, although yield differences were not significant. Overall, this study found no consistent yield increases in fields treated with Gaucho in the absence of observable pest activity. Research Question Gaucho is the trade name for imidacloprid, a systemic insecticide commonly used as a seed treatment on sorghum for control of chinch bugs, greenbugs, and other insects. Its ability to control these insects and protect sorghum yield potential is well documented. However, the effects of Gaucho on sorghum growth, development, and yield in the absence of noticeable insect populations are less well understood. Growers and others using this product have suggested that a yield increase can occur in the absence of insect attack. We were interested in determining whether this is true and under what conditions it would occur. Literature Summary The insect controlling effects of imidacloprid are well documented. The insecticide is registered for control of such pests as greenbug, chinch bug, and wireworms. Other systemic insecticides such as disulfoton and carbofuran have been shown to have direct effects on plant growth and crop yields. For example, yields of peanut, tobacco, and sorghum were increased in soil treated with disulfoton and yields of tobacco, corn silage, corn grain, rice, and grain sorghum were increased with carbofuran soil treatments. However, other studies have shown no yield response to carbofuran by corn or to disulfoton or phorate by soybeans. Study Description Tests were conducted at five locations representing various soil types and agronomic practices in Kansas in 1996 and 1997 and three locations in 1998. Treated and untreated seed of five sorghum hybrids were obtained. Each treated lot was treated with Gaucho at a rate of 4oz. ai/cwt. Additional hybrids were evaluated at one location in 1996 and 1997. Plant stands were recorded at the 2-leaf stage of development. Head counts were made approximately 3 wk after the bloom stage. Plots were harvested with a modified two-row Gleaner combine, and yields and test weights were determined. Plots were examined at various intervals for the presence of insects. When infestations occurred, the numbers per plant were determined by examining several plants in each plot. Applied Questions Were insect populations present in these tests? Small numbers of chinch bugs were detected at Hesston and greenbugs were detected at Garden City but in general insect activity was not detected. When insects were present, did the insecticide treatments have any effect? Imidacloprid gave good control of greenbugs early in the season and caused about a 50% reduction in greenbug numbers late in the season at Garden City. At Hesston, chinch bugs were present but numbers were too low to quantify. Did the insecticide treated plots have a higher yield in the absence of insect attack? In general, no consistent yield increase occurred in Gaucho treated sorghum at five locations in Kansas. The exception was at Hesston, where significant increases were noted with some hybrids in both 1996 and 1997. Recommendation Our study suggests that yield improvement following use of Gaucho in fields with no noticeable pest activity is overrated. A consistent yield response was only observed at one location, which frequently experiences problems with chinch bugs. Low insect numbers were observed in the plots at this location. Some hybrids respond to the Gaucho treatment more than others.

Spread of Ergot of Sorghum (Claviceps africana) in Central Mexico.

By late August 1997, sorghum ergot (Claviceps africana Frederickson, Mantle & De Milliano) had not been detected in the Bajio area in central Mexico, the second-largest sorghum (Sorghum bicolor (L.) Moench) producing area in the country, despite earlier 1997 reports of the disease in the adjacent states of San Luis Potosi, Michoacan, and Jalisco. A mid-September survey was conducted in el Bajio, primarily in the state of Guanajuato, and adjacent areas in the states of Michoacan and Jalisco. Infected sorghum heads showing ergot symptoms of honeydew and white secondary sporulation were observed in commercial grain and hybrid seed fields in all three states. Environmental conditions, late summer rains and early low temperatures promoting abundant dew, as well as extended periods of sorghum blooming, contributed to a low and delayed incidence of ergot in Guanajuato. In Michoacan and Jalisco the higher relative humidity and rainfall (around 750 ml) probably contributed to the observed epidemic of ergot. Johnsongrass (Sorghum halepense (L.) Pers.) florets also showed ergot symptoms. Macroconidia in honeydew were hyaline, oblong to oval, slightly constricted at the center, with an average size of 15 × 7 μm, agreeing with the given description of Sphacelia sorghi McRae (2), the anamorph stage of C. africana. No sclerotia were found on any host. Ergot control in this region of Mexico is being attempted by chemical means and burning of heads, even in commercial fields with minimal incidence of ergot. This report of ergot spread complements an earlier note describing the initial detection of the disease in Tamaulipas, the largest sorghum-producing state in Mexico (1).

Use of Weather Variables to Quantify Sorghum Ergot Potential in South Africa.

Quantification of resistance to ergot requires that the observed ergot severity within a sorghum line be compared with expected ergot severity (ergot potential) to compensate for differences in environmental favorability for the disease among flowering dates and seasons. The ergot potential required to induce the onset of disease is referred to as the ergot breakdown point of that line. In earlier studies, the ergot potential of a specific flowering date was defined as the mean ergot severity in all sorghum heads over all lines in the nursery which commenced flowering on that date in a genetically broad-based sorghum nursery. In this study, results of field trials enabled accurate prediction of ergot potential by using a multiple regression analysis which included three weather variables-namely, pre-flowering minimum temperature (mean of days 23 to 27 pre-flowering), mean daily maximum temperature, and mean daily maximum relative humidity (mean of days 1 to 5 post-flowering; R2 = 0.90; P = 0.91E-5). Evaluation of predicted and observed ergot severity in an independent data set gave an index of agreement of d = 0.94 and R2 = 0.84 (P = 0.106E-4), showing that ergot severity, assuming the presence of viable inoculum, can be accurately predicted. Low pre-flowering minimum temperature was associated with reduced pollen viability, which appeared to be the primary factor predisposing lines to ergot.

Evaluation of Spray Timing with Lorsban and Asana to Control Sorghum Midge in the Lower Rio Grande Valley, Texas, 1986

Abstract The experiment was conducted in 4 row by 50 ft plots of ‘Pioneer 8244’ variety grain sorghum planted 26 Mar at the TAMU-Hoblitzelle Farm near Mercedes, TX. The experimental design was a randomized complete block with 4 replications. Lorsban 4E and Asana HP were sprayed through a CO2 powered, backpack sprayer calibrated to deliver 10 gal/acre (1 TX6 hollow cone nozzles/row, 40 psi, 2 mph). Lorsban XRM was delivered at 2.5 gal/acre (1 TX2 hollow cone nozzle/row, 40 psi, 2 mph). Asana HP @ 0.0125 and Lorsban XRM @ 0.125 lb (AI)/acre were applied on 3, 4, 5, or 6 day intervals. Lorsban 4E @ 0.25 lb (AI)/acre was applied on 3 and 6 day intervals. The first application for all treatments was made on 31 May. Efficacy was evaluated by cutting 3 sorghum heads from each plot on 13 Jun and holding them in rearing chambers made from 1 qt cardboard ice cream containers. Emergent midges were collected in an 8 ml vial that was inserted into the side of the rearing chamber. Counts of adult midges were recorded daily until emergence had ceased. Sorghum plots were harvested on 16 Jul with a 4-row combine and weighed.

Insecticidal Control of Sorghum Webworm in Louisiana, 1985

Abstract Six insecticides were evaluated for control of the sorghum webworm at the LSU, Idlewild Experiment Station, East Feliciana Parish, LA. Grain sorghum was planted in a conventional manner on 25 May. Insecticide treatments were 50 ft × 1 row with an untreated row between treatments. A completely randomized block design was used with 4 replications, 5 ft alleys between replicates and 38 inch row spacing. Insecticides were applied using a backpack CO2 pressurized sprayer delivering 16 gal/acre at 55 psi through a single Teejet 8002 E nozzle. Sprays were applied approximately 6 inches above the sorghum heads on 6 Aug. The effectiveness of the treatments was evaluated on 9 Aug by counting the number of live webworms on 5 randomly selected sorghum heads from each treatment in each replication. Webworms were counted by clipping and bagging the heads, shaking them over a white porcelain pan, and counting the number of live webworm larvae.

Control of Pests on Sorghum in Mississippi, 1983

Abstract Populations of sorghum webworm, corn earworm and fall armyworm larvae (4th-5th instars) were observed on 5 Sep feeding on sorghum cv. Dekalb 42 Y (dough stage), planted on 11 Jul in Oktibbeha County, MS. Populations exceeded 47, 11 and 46 per 10 heads selected randomly from the field for sorghum webworm, corn earworm and fall armyworm, respectively. Plots were 1 row wide and 20 ft in length arranged in a randomized complete block with 3 replicates. Insecticides were applied in 10 gal of water per acre with a hand-held compressed air sprayer equipped with a solid-cone nozzle using 30 psi. The time of application was between 3 and 4 p.m. The temperature was ca 89°F. On 9 Sep (day 4 post application) treatment plots were sampled by removing 10 heads randomly from each treatment plot. Sorghum heads for each treatment were placed in paper bags and returned to the lab for examination.

Sorghum Webworm Control, 1983

Abstract Three insecticides were evaluated for control of the sorghum webworm at the LSU, Idlewild Exp. St., East Feliciana Parish, La. Funks 522 DR grain sorghum was planted in a conventional manner on 11 July. Treatments were 50 ft by one row with an untreated row between treatments. A completely randomized block design was used with four replications, 5-ft alleys between replicates and 38 in. row spacing. Insecticides were applied using a back-pack, CO2 pressurized sprayer delivering 16 gal/acre at 55 lb/in2 through a single Teejet 8002 E nozzle. Sprays were applied from approximately 6 in. above the sorghum heads on 14 Sep. A pretreatment count of 100 randomly-selected heads in the test area yielded a mean of 17.9 webworms per head. The effectiveness of the insecticides was evaluated on 16 Sep. by counting the number of webworms shaken from 20 randomly selected heads from each treatment in each replication. The heads were brought into the laboratory, shaken over a white porcelin pan and inspected for live webworms that failed to dislodge.

Sorghum Webworm Control, 1980

Abstract Three tests evaluated various materials in suppressing sorghum webworm populations on grain sorghum heads. All tests were planted with Funk’s G522DR on July 2 by minimal tillage methods following wheat. Plots were 6.1 m x 3 rows and were separated by 1 untreated row or 1 m alley. Treatments were replicated 4 times in a randomized complete block design. Applications were made with compressed-air sprayers calibrated to deliver 50 gal per acre at 30 psi. Spray was directed to opposite sides of heads to insure thorough coverage. One application on Sept 18 was used in Test 1. Low pest population levels did not merit a second application. Two applications were made on Oct 3 and 8 in Tests 2 and 3. Larval populations were estimated on each sampling date by shag-bagging 10 randomly-selected heads from each plot.

Attraction of Sorghum Midge Parasites to Sorghum Heads

Attraction of Sorghum Midge Parasites to Sorghum Heads

Damage to Grain Sorghum by Fall Armyworm and Corn Earworm123

In field tests, no significant loss in yield occurred when whorls of grain sorghum, Sorghum bicolor (L.) Moench, were infested with 2, 4, 8, or 16 first instars of the fall armyworm, Spodoptera frugiperda (J. E. Smith), at 10 or 20 days after planting. However, infestations applied at 30–49 days after planting caused a high yield loss that increased progressively as the number of larvae increased. When similar infestation levels of corn earworms, Heliothis zea (Boddie), were applied, loss was greatest when sorghum heads were infested at 50% bloom. Injury was less when heads were infested 2 wk after bloom. Increasing the number of corn earworm larvae above 2/head did not increase loss of yield significantly.

Resistance to sorghum midge (Contarinia sorghicola Coquillet) in grain sorghum

Standardized levels of infestation of sorghum midge Contarinia sorghicola Coquillet were used to compare the levels of resistance in sorghum cultivars (Sorghum bicolor) in glasshouse experiments at Biloela in Central Queensland. Sorghum heads were reduced to 250 florets and ten female midges were caged over each head on three consecutive days during anthesis. Two breeding lines from the U.S.A., IS 12608C and IS 12664C were superior (P < 0.01) to Alpha and KS 19 in percentage seed set and number of midge progeny produced. The percentage seed set was 50, 54, 22, 12 for IS 12608C, IS 1664C, Alpha and KS 19, respectively. The Indian line Q 13828 was susceptible. Testing with a standardized level of infestation is a useful technique for screening parents in a breeding program aimed at incorporation of midge resistance into agronomically useful hybrid cultivars.