Monitoring carbon dioxide concentration for early detection of spoilage in stored grain Maier, D.E.*, Channaiah, L.H.#, Martinez-Kawas, A., Lawrence, J.S.1, Chaves, E.V., Coradi, P.C., Fromme, G.A.2 Department of Grain Science and Industry, Kansas State University, Manhattan, Kansas 66506, U.S.A..
Email: dmaier@ksu.edu, kantha@ksu.edu
1 Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, Indiana 47907,
U.S.A.,
2 BinTech, Orchard Drive, Louisville, Denver, Colorado 80027, U.S.A.
* Corresponding author
金融管理培训机构
# Prenting author
DOI: 10.5073/jka.2010.425.332
Abstract
Field experiments were conducted in storage silos to evaluate carbon dioxide nsors to monitor spoilage in grain prior to spoilage detection by traditional methods such as visual inspections and temperature cables. Carbon dioxide concentrations in the storage silo were monitored up to eight months and correlated to the prence of stored-product incts, molds and mycotoxin levels in the stored grain. The data showed that safe grain storage was obrved at CO2 concentrations of 400 to 500 ppm. Higher concentrations of CO2 clearly showed mold spoilage or inct activity inside the grain storage silo. Carbon dioxide concentrations of 500 to 1200 ppm indicated ont of mold infection where as CO2 concentrations of 1500 to 4000 ppm and beyond clearly indicated vere mold infection or stored-product incts infestation. The percent kernel infection was in the range of 30% for CO2 concentrations of 500 to 1000 ppm to 90% for CO2 concentrations of 9000 ppm. Fungal concentrations were in the range of 2.0 ×102 colony forming units per gram (cfu/g) at 500 ppm CO2 concentration to 6.5 ×107 cfu/g at 9000 ppm CO2 concentration. Fungi of genera Aspergillus spp., Penicillium spp., and Fusarium spp. were isolated from spoiled grain. High concentration of fungi and prence of mycotoxins (aflatoxin: 2 ppb and Deoxynivalenol (DON): 1 ppm) were correlated with high CO2 concentration in the silos. The findings from this rearch will be helpful in providing more timely information regarding safe storage limits, aeration requirements and costs of spoilage mitigation measures such as turning, aerating and fumigating grain. Additionall
y, it will provide information on preventive stored grain quality management practices that should reduce residue levels of mycotoxins, pesticides and other foreign material in our food supply. The CO2 monitoring technology will increa the quality and quantity of stored grain, while saving the U.S. and global grain production, handling and processing industry millions of dollars annually.
Keywords: Carbon dioxide, Grain storage, Stored-product incts, Mold and mycotoxin
1. Introduction
Temperature, relative humidity and moisture content (m.c.) of the stored grain are the most important factors that influence stored-product inct activity, mold growth and subquent production of mycotoxins in storage. Maintaining optimum temperature, relative humidity and proper moisture content are the challenges faced becau of the asonal and daily climate fluctuations, the economics of drying grain, and the need to process grain at higher moistures. The optimum temperature range for mold growth is 25-30°C, and temperatures above 15°C are ideal for inct growth and reproduction. Inct metabolic activity in dry commodities (below 15% m.c.) can result in heating up to 42°C (Mills 1989). A major contributor to the spoilage of grain is growth of various mold species, including veral that produce mycotoxins. Mycotoxins are natural chemicals produced by f
ungi that are detrimental to the health of both animals and humans. The U.S. Food and Drug Administration has placed an action level for mycotoxins in stored grain and other food products including milk. As a result, millions of dollars are spent each year to screen food that includes stored grain, procesd food, milk and animal feed. The earlier methodologies such as human nsory exposure and temperature cables have their own limitations and drawbacks in monitoring grain spoilage during storage. New management practices are needed that will allow grain processors to maintain high quality grain free of stored-product incts, fungi and mycotoxins. Previous studies have shown that CO2 nsors can be effectively ud to monitor early detection of spoilage during storage (Zagrebenyev et al., 2001; Maier et al., 2002; Bhat et al., 2003;
Maier et al., 2006; Bartosik et al., 2008). The goal of this project was to refine the existing CO2 bad technology for its accuracy and consistency in real time monitoring of grain spoilage prior to detection by traditional methods such as visual, smell and temperature nsors.
2. Materials and methods
2.1. Site lection and installation of CO2 nsors
To monitor CO2 concentration for early detection of spoilage due to mold and stored-product incts,
we lected a corrugated steel bin containing 254 tons of maize located near Manhattan, Kansas. The CO2 nsor box (BinTech Company, Denver, CO, USA) box was installed on the roof of the silo clo to a vent by cutting a 10.7 cm diameter hole using a metal cutter. Care was taken to al the gaps around the nsor box to protect water infiltration and to avoid CO2 leakage. Once the nsor box was installed the CO2 nsor was relead inside the silo by maintaining roughly one meter distance above the stored grain. The control box comprising the battery and display board was mounted on the outside wall of the silo about 1.50 m above ground. The CO2 nsor and the control boxes were connected and tested for wireless telephone signals and its connectivity to the main rver. During grain storage, the CO2 data were transmitted to the main rver (BinTech Company) in the form of digital codes using the wireless telephone network.英语四级考试技巧
mark twain2.2. Monitoring changes in CO2 concentrations东莞南博
Carbon dioxide concentrations in all storage bins were monitored from February to August 2009. The maize samples were collected and analyzed for grain quality parameters, stored-product inct incidence, prence of molds, and mycotoxin contamination. A log book was maintained to document all grain storage activities including information on battery change and dates of sample collection. Furthermore, details of the storage silo including size, number of fans, pesticide usage, st
orage start date and contact details of the cooperator were recorded. The silo was inspected and maize samples were collected bad on high CO2 concentration readings and correlated to mold spoilage or stored-product inct activity in the silo. Two ts of grain samples in replicates were collected by probing with a grain sampler. One t was ud to analyze molds, mycotoxins and incts in the Grain and Feed Microbiology and Toxicology Laboratory (Department of Grain Science and Industry, Kansas State University, Manhattan, KS, USA) while the cond t of grain samples was nt to the Kansas Grain Inspection Service Lab (Topeka, KS, USA) to determine grain quality parameters such as moisture content, dockage and damaged kernels. 2.3. Isolation, enumeration and identification of incts and molds
Grain samples collected during this study were immediately brought to the lab and sieved (480-µm openings) to parate all live incts. The incts were identified, counted and expresd as number of incts per kilogram (kg) of grain. For isolation of molds from grain samples we followed the procedure described by Samson et al. (1996). Twenty five grams of reprentative sample was soaked in 250 mL of sterile peptone (0.1%) water for 30 min before stomaching for two mins. One mL of the sample, rially diluted in 9 mL of peptone water and a 100-µL sample from rial dilutions, was drop-plated on Dichloron Glycerol-18 (DG-18) agar medium (Oxoid Chemicals, Hampsdirty dozen
hire, UK) and incubated at 30°C for 4-5 d in an upright position. After incubation, the colony forming units were recorded to determine the number of molds per gram of grain (cfu/g). To confirm the species level, the isolates were obrved under microscope for the morphology of spores and mycelia. The obrvations were recorded and matched with descriptions given by Samson et al. (1996) to confirm genus and species.
2.4. Detection of mycotoxins using ELISA
The levels of aflatoxin, fumonisin, and Deoxynivalenol (DON) in maize grain samples were quantified using the AOAC International, Gaithersburg, MD, USA) approved method bad on an Enzyme Linked Immmunosorbent Assay (ELISA) (AgraQuant® Mycotoxin ELISA Test Kits, Romer Labs Inc., Union, MO, USA). Twenty grams of reprentative sample was grounded and extracted using
70/30 (v/v) methanol/water. For DON analysis the grains were extracted with 100 mL water. The extract was mixed and added to the antibody-coated microwell. Mycotoxins in samples and control standards were allowed to compete with enzyme-conjugated mycotoxins for the antibody binding sites. After the washing step, an enzyme substrate was added for color (blue) development. A stop solution was added to stop the reaction which changed the color from blue to yellow which was measured optically (450 nm)
using a microplate reader (Stat Fax® 303+ Microstrip Reader, Awareness Technology, Inc., Palm City, FL, USA) to determine the concentration of mycotoxins in a sample which was expresd in ppb or ppm.
3. Results
The storage silo lected for this study had spoilage before the CO2 nsor was installed. It can be obrved in Fig. 1 that high CO2 readings (>3000 ppm) were detected by the nsors in March of 2009. We inspected the bin and found an inch thick of spoiled grain on the surface. We took samples and brought this to the attention of the cooperator and recommended the removal of the moldy grain. As time elapd, CO2 readings remained stable until late May of 2009. As ambient and headspace temperatures incread, CO2 readings in June ro to around 1000 ppm and above, which clearly indicated mold or inct activity. In early July, CO2 readings began to increa up to 5000 ppm and on inspection of the silo, mold development and spoiled grain on the surface layer were noticed. A sudden drop in concentration of CO2 on 8 July, 2009 was the result of an attempt to further clean out the top layer of spoiled grain. This did not work becau CO2 readings shot up even higher than before to 7000 ppm and above. The bin was finally emptied in the middle of August. Samples were analyzed and as expected the maize grain was heavily damaged due to mold. We obrved a strong
correlation between the ri in headspace CO2 concentrations vers mold and stored-product incts activities in stored maize. Analysis showed a high concentration of mold (6.5 × 107 cfu/g) per gram of maize (Table 1). The percent kernel infections assay showed that 90.0% of the maize kernels were infested by molds at CO2 concentrations of 9000 ppm and above.
Figure 1Change in headspace CO2 concentration, relative humidity and temperature during grain storage.
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Table 1 Grain quality parameters and incidences of stored-product incts, molds and mycotoxins in maize
during storage
Time Grain Air Relative Stored-product
exact timePercent Kernel Molds Mycotoxins
(2009) Moisture (%) Temperature (ºC) Humidity (%) Incts (No. incts/kg) Infections (%) cfu/g Total aflatoxins (ppb) Fumo-nisins (ppm) Deoxy-
nivalenol
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2March NA 26 60 1 70 5.0 ± 0.1 × 106 0 2 0 April NA 26 50 2 NA 2.2 ± 0.0 × 102 0 0 0 May N
A 33 50 4 NA 2.5 ± 0.2 × 103 0 0 0 June NA 43 52 10 NA NA 0 0 0 July 13.5 50 59 18 80 4.2 ± 0.3 × 106 1 0 0 August 13.7 49 62 27 90 6.5 ± 0.3 × 107 2 0 1 NA: Data not availablebar
We detected 2 ppb of aflatoxins and 1 ppm of DON in the unloaded maize (ending) sample. Mold concentration in the maize correlated with high CO 2 readings in the silo. Also, heavy stored-product inct infestation was noticed. The incts were identified as flat grain beetle , Cryptolestes pusillus (Schönherr) (Coleloptera: Laemophoeidae) which is a mold feeder, and maize weevil, Sitophilus zeamais Motschulsky (Coleoptera: Curculionidae) which feed on the maize. Upon enumeration we noticed 27 live incts per kg of maize (Table 1). Nearly 100 tones (40% of stored maize) of spoiled and damaged maize was parated and ud for animal feed.
4. Discussion
It is esntial for the grain storage industry to have effective management programs to protect against economic loss due to contamination from stored-product incts, molds and mycotoxins. Manual grain inspection (human nsory exposure) and measuring grain temperature are the main tools ud by the farmers and the grain industry for monitoring proper storage conditions (Bartosik et al., 2008). Human nsory exposure literally means having personnel “walk” the grain mass, smell th
topper
e grain, smell the aeration discharge stream and look at the grain. Human nsory exposure for mold spoilage and other quality parameters could be biad and it varies from person to person. Temperature cables are routinely placed in modern grain bins. Unfortunately, a temperature cable will not detect the fungal growth veral feet away from the cable until the size of the spoiling grain mass is large enough to rai the temperature around the volume of the temperature cable. The limitations are overcome with the CO 2 nsors. Fungi and their related mycotoxin contamination problem is one that is not easily resolved by the food, feed and grain processing industry (CAST, 1989; Miller and Trenholm, 1994). Only organic acids are available for controlling fungal growth. Unfortunately, the acids are not suitable for many situations becau they verely limit the number of end us available for the treated grain. Our experiment clearly demonstrated that CO 2 nsors can be effectively ud to detect stored-product incts infestation and grain spoilage due to mold infections well before spoilage detection by traditional methods such as visual inspections, smell and temperature cables. Production of carbon dioxide has been a method ud for many years to predict the storability of grains under laboratory and field conditions (Stroshine and Yang, 1990; Maier et al., 2006). In this study, we successfully ud the CO 2 nsors under field conditions for early detection of spoilage in maize due to molds and stored-product incts. Further, in this study we refined the CO 2 nsor technology that provides accurate and consistent results.
Carbon-dioxide-bad, spoilage-detection devices are expected to save grain producing, handling and processing industry millions of dollars annually. Reducing spoilage would lower residue levels of mycotoxins, pesticides and other foreign materials in our food supply, and maintain the quality and quantity of stored grain, while minimizing storage and handling costs. Such an early warning system would provide more timely information to farmers to make the correct management decision to avoid the costs of spoilage mitigation measures such as turning, aeration, and fumigation. This would help in continuing to store grain or market it early to avoid further quality deterioration.
Acknowledgements
We would like to thank the United States Department of Agriculture’s Small Business Innovation Rearch (USDA-SBIR: 2007-33610-18616) grant program for supporting this project.
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