VTechWorks Repository :: Browsing by Author "Balota, Maria"

Browsing by Author "Balota, Maria"

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2009-2010 Performance of Sorghum Hybrids in the Virginia-Carolina Region
Balota, Maria; Holshouser, David L.; Dahlberg, Jeff; Padgett, Shelee (Virginia Cooperative Extension, 2011)
This report presents 2009-2010 crop data for Sorghum varieties in North Carolina and Virginia, including data on planting and harvest dates, soil type, irrigation, weed management, nutrient management, pest and disease control, and weather conditions
2009-2011 Performance of Sorghum Hybrids in the Virginia-Carolina Region
Balota, Maria; Herbert, D. Ames Jr.; Holshouser, David L.; Dahlberg, Jeff (Virginia Cooperative Extension, 2013)
This report presents 2009-2011 crop data for Sorghum varieties in North Carolina and Virginia, including data on planting and harvest dates, soil type, irrigation, weed management, nutrient management, pest and disease control, and weather conditions
2011 - 2012 Runner vs. Virginia Peanut Test Results
Balota, Maria (Virginia Cooperative Extension, 2013)
This report provides data on peanut varieties in test plots in 2011-2012, including soil and weather conditions, planting and harvest dates, types of soil, fertilizers, herbicides, insecticides, fungicides.
2020 Peanut Variety and Quality Evaluation Results. I. Agronomic and Grade Data
Balota, Maria; Dunne, Jeffrey; Cazenave, Alexandre Brice; Anco, Dan; Nixon, Wayne (Virginia Cooperative Extension, 2021-02-16)
Due to suitability to the environmental conditions and existence of a strong peanut industry tailored to process primarily the large-seeded Virginia-type peanut, growers in Virginia, North Carolina, and South Carolina generally grow Virginia-type cultivars. In the view of a common interest in the Virginia-type peanut, the three states are working together through a multi-state project, the Peanut Variety Quality Evaluation (PVQE), to evaluate advanced breeding lines and commercial cultivars throughout their production regions. The objectives of this project are: 1) to determine yield, grade, quality, and disease response of commercial cultivars and advanced breeding lines at various locations in Virginia and the Carolinas, 2) develop a database for Virginia-type peanut to allow research-based selection of the best genotypes by growers, industry, and the breeding programs, and 3) to identify the most-suited peanut genotypes for various regions that can be developed into varieties. This report contains agronomic and grade data of the PVQE tests in 2020.
2020 Virginia Peanut Production Guide
Balota, Maria; Jordan, David; Mehl, Hllary; Shortridge, Julie; Taylor, Sally V. (Virginia Cooperative Extension, 2020)
Provides information on peanut varieties, including which kinds to choose for disease and insect resistance. Also discusses weed control, insect control, disease control, irrigation, fertilizers and equipment.
2021 Field Crops PMG
Balota, Maria; Besancon, Thierry E.; Cahoon, Charles W.; Chandra, Rakesh; Currin, John F.; Day, Eric R.; Flessner, Michael; Frame, William Hunter, 1985-; Frank, Daniel; Hines, Tommy; Herbert, D. Ames Jr.; Johnson, Charles S.; Johnson, Quintin; Jordan, David; Koehler, Alyssa; Langston, David B.; Lamb, Curt; Lingenfelter, Dwight; McCoy, Tim; Singh, Vijay; Taylor, Sally V.; VanGessel, Mark; Vollmer, Kurt; Wallace, John M.; Wilson, James (Virginia Cooperative Extension, 2021-02-12)
The Virginia Pest Management Guide (PMG) series lists options for management of major pests: diseases, insects, nematodes, and weeds. These guides are produced by Virginia Cooperative Extension and each guide is revised annually. PMG recommendations are based on research conducted by the Research and Extension Division of Virginia Tech, in cooperation with other land-grant universities, the USDA, and the pest management industry. Commercial products are named in this publication for informational purposes only. Virginia Cooperative Extension does not endorse these products and does not intend discrimination against other products that also may be suitable.
2021 Home Grounds and Animals PMG - Index
Balota, Maria; Besancon, Thierry E.; Cahoon, Charles W.; Chandran, Rakesh; Currin, John F.; Day, Eric R.; Flessner, Michael; Frame, William Hunter; Frank, Daniel; Hines, Tommy; Herbert, Ames Jr.; Johnson, Charles S.; Johnson, Quintin; Jordan, David; Koehler, Alyssa; Langston, David B.; Laub, Curt; Lingenfelter, Dwight; McCoy, Tim; Singh, Vijay; Taylor, Sally V.; VanGessel, Mark; Vollmer, Kurt; Wallace, John M.; Wilson, James (Virginia Cooperative Extension, 2021-02-12)
This is a chapter of the 2021 Field Crops PMG. The Virginia Pest Management Guide (PMG) series lists options for management of major pests: diseases, insects, nematodes, and weeds. These guides are produced by Virginia Cooperative Extension and each guide is revised annually. PMG recommendations are based on research conducted by the Research and Extension Division of Virginia Tech, in cooperation with other land-grant universities, the USDA, and the pest management industry. Commercial products are named in this publication for informational purposes only. Virginia Cooperative Extension does not endorse these products and does not intend discrimination against other products that also may be suitable.
2021 Virginia Peanut Production Guide
Balota, Maria; Jordan, David; Langston, David B.; Shortridge, Julie; Taylor, Sally V. (Virginia Cooperative Extension, 2021-02-09)
This publication included a guide for peanut growers including agronomic, insect, disease management along with weed control, and irrigation and safety information. Archived Peanut Production Guides can be accessed from: http://www.sites.ext.vt.edu/newsletter-archive/peanut-production/index.html
Aerial high-throughput phenotyping of peanut leaf area index and lateral growth
Sarkar, Sayantan; Cazenave, Alexandre-Brice; Oakes, Joseph C.; McCall, David S.; Thomason, Wade E.; Abbott, A. Lynn; Balota, Maria (Springer Nature, 2021-11-04)
Leaf area index (LAI) is the ratio of the total one-sided leaf area to the ground area, whereas lateral growth (LG) is the measure of canopy expansion. They are indicators for light capture, plant growth, and yield. Although LAI and LG can be directly measured, this is time consuming. Healthy leaves absorb in the blue and red, and reflect in the green regions of the electromagnetic spectrum. Aerial high-throughput phenotyping (HTP) may enable rapid acquisition of LAI and LG from leaf reflectance in these regions. In this paper, we report novel models to estimate peanut (Arachis hypogaea L.) LAI and LG from vegetation indices (VIs) derived relatively fast and inexpensively from the red, green, and blue (RGB) leaf reflectance collected with an unmanned aerial vehicle (UAV). In addition, we evaluate the models’ suitability to identify phenotypic variation for LAI and LG and predict pod yield from early season estimated LAI and LG. The study included 18 peanut genotypes for model training in 2017, and 8 genotypes for model validation in 2019. The VIs included the blue green index (BGI), red-green ratio (RGR), normalized plant pigment ratio (NPPR), normalized green red difference index (NGRDI), normalized chlorophyll pigment index (NCPI), and plant pigment ratio (PPR). The models used multiple linear and artificial neural network (ANN) regression, and their predictive accuracy ranged from 84 to 97%, depending on the VIs combinations used in the models. The results concluded that the new models were time- and cost-effective for estimation of LAI and LG, and accessible for use in phenotypic selection of peanuts with desirable LAI, LG and pod yield.
Agronomic and Economic Comparison of Full-Season and Double-Cropped Small Grain and Soybean Systems in the Mid-Atlantic USA
Browning, Phillip W. (Virginia Tech, 2011-05-02)
Increased demand for barley has changed the proportion of crops grown in Virginia and the Mid-Atlantic USA. Winter wheat is the predominant small grain crop, but barley can be a direct substitute, although much less of it is grown. Soybean is grown full-season and double-cropped after both small grains. Historically, wheat was the primary small grain in the soybean double-crop rotation because of its greater profitability. The barley-soybean cropping system is not a new concept in the region, but the literature is outdated. New agronomic and economic data that directly compares full-season soybean, barley-soybean, and wheat-soybean systems using modern cultivars and management practices is needed. The objectives of this research were to: i) determine soybean yield and compare cropping system profitability of the three cropping systems; ii) perform a breakeven sensitivity analysis of the three cropping systems; and iii) determine the effect of planting date and previous winter crop on soybean yield and yield components. Soybean grown after barley yielded more than full-season soybean in two of six locations and more than soybean double-cropped after wheat in three of six locations. Net returns for the barley-soybean system were the greatest. These data indicate that soybean double-cropped after barley has the potential to yield equal to or greater than full-season soybean or double-cropped soybean following wheat, but its relative yield is very dependent on growing conditions. The profitability comparison indicated that the barley-soybean cropping system was generally more profitable than the full-season soybean and double-cropped wheat-soybean systems. This conclusion was supported by the breakeven sensitivity analysis, but remains dependent on prices that have been extremely volatile in recent years. In another study, soybean yields declined with planting date at two of four locations in 2009, a year that late-season rainfall enabled later-planted soybean to yield more than expected. In 2010, soybean yield decline was affected by the delay in planting date at both locations. Winter grain did not affect soybean yield in either year. Yield component data reinforced these results and indicated that the lower seed yield in the later planting dates was due primarily to a decrease in the number of pods.
Alternative and Improved Cropping Systems for Virginia
Chim, Bee Khim (Virginia Tech, 2016-04-27)
Feed grain consumption in Virginia and the mid-Atlantic region is more than double the total production. Producing more feed grains in this region could generate more profit for grain growers and lower costs for end-users. Increased feed grain production in this region will necessitate improved corn (Zea mays L.) management techniques and adoption of alternative feed grains such as grain sorghum (Sorghum bicolor L.). In order to achieve our overall objective of increased corn and grain sorghum production in the region, experiments were conducted to assess tools with the ability to increase the efficiency of sidedress nitrogen (N) application for corn and to test the performance of grain sorghum in both full season and double-crop rotations in this region. For the corn studies, seven field experiments were established in 2012-2014 with four replications in a randomized complete block design. Treatments included a complete factorial of four different preplant N rate (0, 45, 90, 134 kg ha-1) with three different approach simulation model-prescribed rates (Virginia Corn Algorithm, Maize-N, Nutrient Expert-Maize) and the standard Virginia yield-goal based approach. No differences in corn yield were found between the different simulation model and preplant N rate, however the prescribed sidedress N rate varied significantly due to the simulation model, preplant N rate and the interaction between them. The nitrogen use efficiency (NUE) was estimated based on partial factor productivity (PFP) of nitrogen. The greatest PFP resulted from use of the Virginia Corn Algorithm (VCA), which produced 68 kg grain kg N-1 compared with 49 kg grain kg N-1 for the yield-goal based approach. While the VCA shows promise as a tool for improving NUE of sidedress applications in corn, more research is needed to validate performance. Soybean (Glycine max L.) is often double-cropped after small grain in the mid-Atlantic region. Growing grain sorghum in this niche in the cropping system instead could result in greater overall feed grain production. In order to assess the performance of grain sorghum as an alternative in common cropping systems, four field experiments were established at the Southern Piedmont Agriculture Research and Extension Center (SPAREC) and Tidewater Agriculture Research and Extension Center (TAREC), near Blackstone and Holland, Virginia, respectively. The experiments were conducted using a split plot design with four replications and fourteen treatments. Main plot was winter small grain crop; either barley (Hordeum vulgare L.), triticale (x Triticosecale.), wheat (Triticum aetivum L.) or winter-fallow and the subplot either soybean or sorghum. In three of four instances, full season sorghum yields were greater than double-cropped sorghum after small grain. At two locations, sorghum yields following triticale were lower than when following barley, possibly indicating an antagonistic or allelopathic effect of triticale. The most profitable cropping system was wheat-soybean based on the price assumptions and measure yields in this experiment. Among the sorghum cropping system, the most profitable system was also wheat-sorghum. Sorghum can be successfully grown in both full-season and double-crop systems and offers good potential to increase feed grain production in this region.
Characterization and management of major fungal diseases and mycotoxin contamination of grain sorghum in the mid-Atlantic U.S.
Acharya, Bhupendra (Virginia Tech, 2019-06-11)
Industry demand for local sources of grain for animal feed has increased sorghum production in the mid-Atlantic region of the U.S. Sorghum anthracnose (causal agent Colletotrichum sublineola) and the grain mold complex, which includes mycotoxin-producing Fusarium spp., limit the yield and quality of grain sorghum in humid climates worldwide. A majority of U.S. grain sorghum production is in arid regions, and management strategies have not been developed for the mid-Atlantic U.S. where warm, wet conditions favor disease. The specific objectives of this research were to: (1) determine the effectiveness of fungicides and their application timing for the management of sorghum foliar anthracnose, (2) compare five grain sorghum hybrids for their susceptibility to foliar anthracnose, grain mold and mycotoxin contamination under field conditions, (3) integrate host resistance and fungicide application to manage anthracnose and grain mold, and (4) identify Fusarium spp. associated with grain mold and mycotoxin contamination of sorghum in the mid-Atlantic U.S. For Objective 1, it was determined that a single application of pyraclostrobin-containing fungicide no later than flowering reduced anthrancose, protected yield and maximized farm income. Objective 2 focused on sorghum hybrid selection as a disease management tactic, and it was determined that hybrids with high yield potential and moderate disease resistance should be selected for mid-Atlantic sorghum production in order to maximize grain yield and quality while minimizing the need for fungicide inputs. Objective 3 focused on integrated management and demonstrated that under moderate disease pressure, a high-yielding susceptible hybrid required a single application of pyraclostrobin-based fungicide to minimize fungal diseases and maintain acceptable yields, whereas under high disease pressure it was necessary to integrate hybrid resistance and judicous applications of fungicides. The aim of Objective 4 was to characterize potential causal agents of mycotoxin contamination in mid-Atlantic sorghum, and thirteen phylogenetically distinct Fusarium species (F. lacertarum, F. graminearum. F. armeniacum, F. proliferatum, F. fujikuroi, F. verticillioides, F. thapsinum and several in Fusarium incarnatum-equiseti species complex) were found to be associated with grain mold and fumonisin and/or deoxynivalenol contamination of sorghum grain. This work has provided insights into the impacts of fungal diseases on grain sorghum yield and quality in the mid-Atlantic and has aided in development of best management practices for the region.
Comparing Regression and Classification Models to Estimate Leaf Spot Disease in Peanut (Arachis hypogaea L.) for Implementation in Breeding Selection
Chapu, Ivan; Chandel, Abhilash; Sie, Emmanuel Kofi; Okello, David Kalule; Oteng-Frimpong, Richard; Okello, Robert Cyrus Ongom; Hoisington, David; Balota, Maria (MDPI, 2024-04-30)
Late leaf spot (LLS) is an important disease of peanut, causing global yield losses. Developing resistant varieties through breeding is crucial for yield stability, especially for smallholder farmers. However, traditional phenotyping methods used for resistance selection are laborious and subjective. Remote sensing offers an accurate, objective, and efficient alternative for phenotyping for resistance. The objectives of this study were to compare between regression and classification for breeding, and to identify the best models and indices to be used for selection. We evaluated 223 genotypes in three environments: Serere in 2020, and Nakabango and Nyankpala in 2021. Phenotypic data were collected using visual scores and two handheld sensors: a red–green–blue (RGB) camera and GreenSeeker. RGB indices derived from the images, along with the normalized difference vegetation index (NDVI), were used to model LLS resistance using statistical and machine learning methods. Both regression and classification methods were also evaluated for selection. Random Forest (RF), the artificial neural network (ANN), and k-nearest neighbors (KNNs) were the top-performing algorithms for both regression and classification. The ANN (R²: 0.81, RMSE: 22%) was the best regression algorithm, while the RF was the best classification algorithm for both binary (90%) and multiclass (78% and 73% accuracy) classification. The classification accuracy of the models decreased with the increase in classification classes. NDVI, crop senescence index (CSI), hue, and greenness index were strongly associated with LLS and useful for selection. Our study demonstrates that the integration of remote sensing and machine learning can enhance selection for LLS-resistant genotypes, aiding plant breeders in managing large populations effectively.
Description and Performance of the Virginia-Market-Type Peanut Cultivars
Balota, Maria; Isleib, Thomas G.; Chapin, Jay W. (Virginia Cooperative Extension, 2010)
Describes Virginia-type peanut cultivars and their crop performance in Virginia and the Carolinas.
Development of high-throughput phenotyping methods and evaluation of morphological and physiological characteristics of peanut in a sub-humid environment
Sarkar, Sayantan (Virginia Tech, 2021-01-05)
Peanut (Arachis hypogaea L.) is an important food crop in the USA and worldwide with high net returns but yield in excess of 4500 kg ha-1 is needed to offset the production costs. Because yield is limited by biotic and abiotic stresses, cultivars with stress tolerance are needed to optimize yield. The U.S. peanut mini-core germplasm collection is a valuable resource that breeders can use to improve stress tolerance in peanut. Phenotyping for plant height, leaf area, and leaf wilting have been used as proxies for the desired tolerance traits. However, proximal data collection, i.e. measurements are taken on individual plants or in the proximity, is slow. Remote data collection and machine learning techniques for analysis offer a high-throughput phenotyping (HTP) alternative to manual measurements that could help breeding for stress tolerance. The objectives of this study were to 1) develop HTP methods using aerial remote sensing; 2) evaluate the mini-core collection in SE Virginia; and 3) perform a detailed physiological analysis on a sub-set of 28 accessions from the mini-core collection under drought stress, i.e. the sub-set was selected based on contrasting differences under drought in three states, Virginia, Texas, and Oklahoma. To address these objectives, replicated experiments were performed in the field at the Tidewater Agricultural Research and Extension Center in Suffolk, VA, in 2017, 2018, and 2019, under rainfed, irrigated, and controlled conditions using rainout shelters to induce drought. Proximal data collection involved physiological, morphological, and yield measurements. Remote data collection was performed aerially and included collection of red-green-blue (RGB) images and canopy reflectance in the visible, near infra-red, and infra-red spectra. This information was used to estimate plant characteristics related to growth and drought tolerance. Under objective 1), we developed HTP for plant height with 85-95% accuracy, LAI with 85-88% accuracy, and wilting with 91-99% accuracy; this was done with significant reduction of time as compared to proximal data collection. Under objectives 2) and 3), we determined that shorter genotypes were more drought tolerant than taller genotypes; and identified CC650 less wilted and with increased carbon assimilation, electron transport, quantum efficiency, and yield than other accessions.
Effectiveness of Current Boron Application Recommendations and Practices on Peanut (Arachis hypogaea) in the Virginia - Carolina Region
Benton, Anna Nicole (Virginia Tech, 2016-07-26)
Including peanut (Arachis hypogaea L.) in crop rotations is common for eastern Virginia and the Carolinas, as it thrives in the long growing season and sandy soils. Boron (B) is widely deficient, and is more prone to leeching in sandy soils. Applied B has difficulty reaching growing points as B has reduced phloem mobility in peanuts. Current B fertilization recommendations are based on only three studies from the early 70s. Many changes have been made in cultivar breeding since then. This research examines if recommended B application rates and times are still necessary for optimal yield, plant health and seed quality for current cultivars. Two experiments in seven fields compared four total amounts of B applied (0, 0.3, 0.6, and 1.1 kg ha-1), and application time (planting; beginning peg, R2; full seed, R6; planting and R2; planting and R6), and runner and Virginia market types, newer and obsolete cultivars, with or without B fertilization. Leaf B was elevated only directly after fertilization (p=0.004, p<0.001), and in relation to total B applied (p<0.001), but seed B content was unaffected. Yield was not impacted by B rate or application time. Yield was higher (p=0.012) for newer cultivars when B fertilized, but no different than obsolete cultivars with B. Seed from obsolete cultivars had higher (p=0.010) B, no difference between market types or B fertilization. Germination of all seed was 97%. Based on this research, it is not necessary to apply B for optimal yield, plant health and seed quality for current cultivars.
Effects of Boron Fertilization on Peanut Seed Germination Tested in a Lab Field (TM) Table
Benton, Anna; Balota, Maria; Welbaum, Gregory E. (2017-09-11)
EFFECTS OF BORON FERTILIZATION ON PEANUT SEED GERMINATION TESTED IN A LAB FIELD TABLE Benton A.1, Balota M.1, Welbaum G. E.2 1 Department of Plant Pathology, Physiology, and Weed Science, 2 Department of Horticulture, Virginia Tech, Blacksburg, VA, USA Contact: Greg Welbaum, welbaum@vt.edu Peanut (Arachis hypogaea L.) is an important crop for eastern Virginia (VA) and North Carolina (NC) where it thrives in sandy soils. Boron (B) is not retained in these soils, and seeds with <13mg kg-1 B may have hollow heart and reduced seed quality. Therefore, B is routinely applied as fertilizer regardless of soil test results to prevent deficiencies in peanut seed crops but may contribute to water pollution. A mixture of two market types and newer and older cultivars of peanuts were fertilized with 0, 0.6, 1.1kg ha-1 B at the Tidewater Agriculture Research and Extension Center. Seeds were germinated in sand on a Lab Field table to simulate soil conditions in Eastern VA and NC fields. The peanuts were hand planted on the Lab Field table maintained at a constant sand temperature of 25°C. Mean time to germination (MTG) and germination percentage were recorded to compare treatments. There were no differences in MTG or germination percentage between fertilized and unfertilized plants, market types, or newer and older commercial cultivars on the Lab Field table. Based on this research, B fertilization in the VA and NC production region is not necessary to produce a high quality vigorous peanut seed. The Lab Field table was an effective tool for testing germination under simulated field conditions.
Effects of Drought and Heat on Peanut (Arachis hypogaea, L.) Production
Balota, Maria (Virginia Cooperative Extension, 2012)
Discusses effects of drought and heat on peanut plants and crop yield, and offers advice on if and when to irrigate fields, and for drought-tolerant varieties of peanuts to use in fields with a history of drought.
Effects of Selenium Application on Heat Tolerance in Peanut Seedlings
Benton, Chad (Virginia Tech, 2012-12)
Peanut production faces many challenges in the world today, and one such issue is heat stress. One of the implications of heat stress on the plants is oxidative stress, which is detrimental to plant health and physiological function. A method to combat oxidative stress could be through the use of antioxidants such as Selenium (Se), which is thought to increase growth and development of plant material. This experiment evaluated tolerance to heat stress in four-week-old seedlings from a set of diverse peanut genotypes. Additionally, the antioxidant activity of Selenium was examined to determine if a) it allowed for increased heat tolerance, and b) if it was associated with specific genotypes. At the conclusion of the treatments, SPAD chlorophyll measurements and fresh-weights were taken, with dry-weights being calculated after seedlings were oven-dried at 80˚C for 48 hours. The experiment concluded that Se did not produce a significant change in tolerance to heat stress. Genotype had a significant effect on SPAD chlorophyll readings and dry-weight. Additionally, temperature did not have a significant effect on dry-weight, but did on SPAD chlorophyll readings and fresh-weight. The effect of temperature on SPAD readings is of interest as the above optimal temperature of 39˚C produced higher relative chlorophyll contents than the 26˚C normal temperature. Due to this result, seedling total leaf area (LA) was further measured to determine if a potential trend could exist. Even though not statistically significant, LA was slightly smaller for seedlings at 39˚C treatment compared to the 26˚C treatment. In summary, the experiment did not discover genotypes that allowed for a significant improvement in tolerance to above-optimal temperatures or validate Se as an additive for increased tolerance to heat stress and improved seedling growth. However, it did demonstrate the ability of peanut seedlings to withstand an increase in temperature at an early stage without significant detrimental impacts.
Effects of Storage Conditions of Aspergillus Growth and Aflatoxin Production in Peanuts. A Study in Ghana
Darko, Clara Bernice (Virginia Tech, 2017-02-13)
Peanuts (Arachis-hypogaea) are one of the staples in Ghana, Sub-Saharan Africa, and other developing countries. This leguminous crop is frequently contaminated with aflatoxins, which are secondary metabolites of some Aspergillus fungi, mostly Aspergillus. flavus and Aspergillus parasiticus. Aflatoxins in foods are known to cause liver cancer, stunted growth in children, immune system disorders and economic losses. Aflatoxin contamination of peanuts during storage is worse in the tropics because climatic storage conditions there are almost the same as the optimum conditions for Aspergillus growth: temperature conditions of about 26-43 °C and relative humidity of 62-99%. This study investigated the growth of Aspergillus and the production of aflatoxin in shelled peanuts under varying treatment and packaging conditions. In addition, the appropriate pre-storage treatments and packaging needed to reduce aflatoxin production and to maintain quality of shelled and in-shell peanuts in storage under tropical environments were studied. Another aim was to determine the impact of the switch to hermetic storage on peanut farming and marketing profitability in Ghana. Different peanut treatments, with and without Aspergillus flavus fungi, were packaged in different systems; specifically, polypropylene woven sacks and hermetic packaging. Peanuts were analyzed for fungi growth, aflatoxin production and lipid oxidation (peroxide value and p-Anisidine value). Partial roasting and blanching of peanuts eliminated aflatoxigenic fungi and halted aflatoxin production in stored peanuts, increased the effectiveness of peanut sorting and, hence, helped reduce or eliminate aflatoxin levels along the peanut value chain. Additionally, the results of this study demonstrated that hermetic storage, by suppressing aflatoxin production, has the potential for maintaining peanut quality vis a vis polypropylene woven packaging. Profitability analysis conducted as part of this study revealed that the use of the hermetic storage system would not only improve farmer and trader profits, but also reduce the incidence of various ailments attributed to aflatoxins.

Browsing by Author "Balota, Maria"

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