Agricultural Crop Fields Research Articles

Conterminous United States crop field size quantification from multi-temporal Landsat data

Abstract Agricultural field size is indicative of the degree of agricultural capital investment, mechanization and labor intensity, and it is ecologically important. A recently published automated computational methodology to extract agricultural crop fields from weekly 30 m Web Enabled Landsat data (WELD) time series was refined and applied to a year of Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhance Thematic Mapper Plus (ETM +) acquisitions for all of the conterminous United States (CONUS). For the first time, spatially explicit CONUS field size maps and derived information are presented. A total of 4,182,777 fields were extracted with mean and median field sizes of 0.193 km 2 and 0.278 km 2 , respectively. The CONUS field size histogram was skewed; 50% of the extracted fields had sizes greater than or smaller than 0.361 km 2 , and there were four distinct peaks that corresponded closely to sizes equivalent to fields with 0.25 × 0.25 mile, 0.25 × 0.5 mile, 0.5 × 0.5 mile, and 0.5 × 1 mile side dimensions. There were discernible patterns between field size and the majority crop type as defined by the United States Department of Agriculture (USDA) National Agricultural Statistics Service (NASS) cropland data layer (CDL) classification. In general, larger field sizes occurred where a greater proportion of the land was dedicated to agriculture, predominantly in the U.S. Wheat Belt and Corn Belt, and in regions of irrigated agriculture. The results were validated by comparison with field boundaries manually digitized from Landsat 5 and Google-Earth high resolution imagery. The validation was undertaken at 48 approximately 7.5 × 7.5 km sites selected across a gradient of field sizes in each of the top 16 harvested cropland areas in U.S. states that together cover 76% of harvested U.S. cropland. Conventional per-pixel confusion matrix based measures that assess pixel level thematic mapping accuracy, and object extraction accuracy measures, were derived. The overall per-pixel crop field classification accuracy was 92.7% and the overall crop field producer's and user's accuracies were 93.7% and 94.9%. Comparing all the reference and extracted field objects, 81.4% were correctly matched and the extracted field sizes were on average underestimated by 1.2% relative to the reference field objects.

NATURAL TRANSFORMATION IN PLANT BREEDING - A BIOTECHNOLOGICAL PLATFORM FOR QUALITY IMPROVEMENT OF ORNAMENTAL, AGRICULTURAL AND MEDICINAL PLANTS

Compactness is a desirable trait in ornamental plant breeding because it is preferred by producers, distributors and consumers. Presently, in ornamental plant production growth of many potted plants is regulated by application of chemical growth retardants, several of which are harmful to both the environment and human health. With the aim to develop an alternative to chemical growth regulators, a biotechnological approach without the use of recombinant DNA technology has been developed. In this method, the soil borne bacterium Agrobacterium rhizogenes inserts T-DNA, containing four root oncogenic loci (rol)-genes rolA, rolB, rolC and rolD among 18 ORFs, into the plant genome. Infection of plants by A. rhizogenes induces hairy roots, from which shoots containing rol-genes can be regenerated. Natural transformation with A. rhizogenes reveals very promising results in several plant species and can be useful in a broader range of application than ornamental breeding. One important aspect of this technology is that the hairy roots can be used directly in the selection process as a primary indicator of a successful transformation. Thus the technology avoids use of undesired antibiotic resistance marker genes. Noteworthy, in Denmark the authorities have confirmed that plant products developed using natural transformation by unmodified strains of A. rhizogenes are not considered as genetically modified (GM) plants according to the European legislation. Generally, rol-genes cause increased rooting, decreased plant height, short internodes, reduced apical dominance and changes in flower characteristics. Several of these traits improve ornamental plant quality and may also benefit characteristics useful in agricultural field crops. In addition, a number of regenerated plants derived from hairy roots contain higher contents of secondary metabolites compared to wild type plants. Hence, this method also has potential as a tool for boosting high value compounds in medicinal plants.

Composting Onion (<i>Allium cepa</i>) Wastes with Alfalfa (<i>Medicago sativa</i> L.) and Cattle Manure Assessment

There is growing interest in the potential for using composts in agricultural and horticultural field crops. The aim of this study is to test the mixture efficiency to produce good quality compost. This paper presents a comprehensive analysis of recycling organic wastes through composting. In an area of approximately 1500 ha, situated in the lower valley of the Rio Negro (Black River), onions are produced. 50% of these onions are processed under Good Agricultural Practices (GAP) and under Good Manufacturing Practices (GMP). The packaging for marketing in processing plants has produced huge volumes of wastes that must be managed according to quality standards. These are composed by scales, roots and leaves, with high C/N ratio. In this study the composting process was studied as a way to recycle ecological and cheap onion waste in order to minimize their environmental impact. The onion residues were mixed with alfalfa and cattle manure. An experiment was carried out in order to determine suitable quality compost (organic product high agronomic value). In order to achieve the objectives, composting processes were carried out in two consecutive years. During the process, some physical, chemical and biological properties of the final product were analyzed and evaluated. The mixtures: OMA, onion-manure-alfalfa; OM, onion-manure; OA, onion-alfalfa, showed a similar behavior. The mixtures more efficient were onion-manure and onion-manure-alfalfa with values close to 50%, while onion-alfalfa yielded only 34%. Reuse of onion waste by composting mixed with cattle manure, is a viable alternative in ecological terms. The final compost obtained could be used as amendment in agriculture practices.

Reverse influence of riparian buffer width on herbivorous and predatory Hemiptera

AbstractInsects are major contributors to farmland biodiversity, and their economic roles are also diverse. Many herbivorous species are crop pests, while predatory insects have the potential to act as biological controls against pests. Overall insect diversity has declined as a result of intensified agricultural practices. Riparian buffers may support insect populations in intensively cultivated areas, but their actual impact on the balance between harmful pests and beneficial predators is not known. It can be postulated that this impact may vary depending on the characteristics and location of the riparian buffer itself. We investigated the possibility that the biotic and abiotic attributes of agricultural riparian buffers adjoining crop fields and watercourses can explain the species composition of hemipteran assemblages. In particular, we were interested in the abundances of species belonging to the genus Nabis (generalist predators) and recognized and potential pests of cereal crops. Riparian buffer width and the presence or absence of woody plants were not associated with hemipteran species turnover among riparian buffers. In contrast, differences in the degree of dominance by grasses, in plant species turnover, and in which crop plant was cultivated in the adjacent field, explained a significant proportion of the variance in hemipteran species turnover. The abundance of predatory Nabis species increased with increasing riparian buffer width, whereas the abundance of recognized and potential crop pests decreased. The reverse patterns in the predatory and herbivorous Heteroptera suggest that increasing riparian buffer width might enhance biological control by Nabis predators.

Dynamics of biotypes B and Q of the whitefly Bemisia tabaci and its impact on insecticide resistance

The whitefly Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) is a key pest in many agricultural crops, including vegetables, ornamentals and field crops. B. tabaci is known for its genetic diversity, which is expressed in a complex of biotypes or, as recently suggested, a complex of distinct cryptic species. The biotypes are largely differentiated on the basis of biochemical or molecular polymorphism and differ in characteristics such as host plant range, attraction by natural enemies, secondary symbionts and expression of insecticide resistance. An extensive survey of B. tabaci biotypes and their impact on insecticide resistance was conducted from 2003 to 2012 in cotton fields and other crops from several locations in Israel. Two biotypes of B. tabaci, B and Q, were identified, and some differences in the biotype dynamics were recorded from different areas. In northern Israel from 2003 to 2007, a higher proportion of the B biotype was consistently found in early season. However, by the end of the season a definite rise of the Q biotype was sampled, ranging from 60 to 100%, along with high resistance to the insect growth regulator (IGR) pyriproxyfen and to a lesser extent to the neonicotinoid insecticides. In fields located in the central part of Israel, the Q biotype was predominant throughout the seasons, with high resistance to pyriproxyfen. Since 2009, a significant shift in the biotype ratios has been observed: the B biotype has come to predominate over the Q biotype ranging up to 90% or more in most fields. At the same time, resistance to the IGR pyriproxyfen was reduced considerably. The possible reasons for the change in the dynamics of B. tabaci biotypes, and its implications for resistance management, are discussed. Strong B. tabaci resistance to pyriproxyfen in Israel has been associated with the Q rather than with the B biotype. The B biotype is more competitive than the Q biotype under untreated conditions. Reduction in the acreage of cotton fields during recent years, along with a decrease in insecticide use, especially pyriproxyfen, has resulted in the expansion of the B biotype.

Automated crop field extraction from multi-temporal Web Enabled Landsat Data

An automated computational methodology to extract agricultural crop fields from 30m Web Enabled Landsat data (WELD) time series is presented. The results for three 150×150km WELD tiles encompassing rectangular, circular (center-pivot irrigation) and irregularly shaped fields in Texas, California and South Dakota are presented and compared to independent United States Department of Agriculture (USDA) National Agricultural Statistics Service (NASS) cropland data layer (CDL) classifications. Coherent fields that are visually apparent were extracted with relatively limited apparent errors of omission or commission compared to the CDL classifications. This is due to several factors. First, the use of multi-temporal Landsat data, as opposed to single Landsat acquisitions, that enables crop rotations and inter-annual variability in the state of the vegetation to be accommodated for and provides more opportunities for cloud-free, non-missing and atmospherically uncontaminated surface observations. Second, the adoption of an object-based approach, namely the variational region-based geometric active contour method that enables robust segmentation with only a small number of parameters and that requires no training data. Third, the use of a watershed algorithm to decompose connected segments belonging to multiple fields into coherent isolated field segments and a geometry-based algorithm to detect and associate parts of circular fields together. A preliminary validation is presented to gain quantitative insights into the field extraction accuracy and to prototype a validation protocol including new geometric measures that quantify the accuracy of individual field objects. Implications and recommendations for future research and large-area applications are discussed.

Cyanobacteria and agricultural crops

Cyanobacteria are photosynthetic Gramnegative prokaryotes and have the ability to grow in a variety of aquatic and terrestrial environments. They occur freely or in symbiotic associations with a wide range of lower and higher plants or in microbial mats. Cyanobacteria are well known for having nitrogen fixing ability and other agriculturally important potentialities. This review focuses mainly on importance of cyanobacteria in agricultural field crops (especially paddy crop). These organisms may be exploited for boosting agriculture as they can fix nitrogen; produce various plant growth regulators (auxins, gibberellins, cytokinins etc.); enhance soil fertility by adding organic matter, nitrogen and phosphorus to soil; degrade various agrochemicals (pesticides and herbicides) and control pathogenic effects of other microorganisms and plants. The role of cyanobacteria in sustainable agriculture is discussed here.

Adsorption of imazethapyr on six agricultural soils of Morocco: Evaluation of the impact of soil properties

Imazethapyr herbicide [5-ethyl-2-(4-isopropyl-4-methyl-5-oxo-2-imidazolin-2-yl) nicotinic acid] is widely used on agricultural field crops in Morocco. It is reported that soil properties largely enhance the sorption of the herbicide in soils, however understanding their impact in soils of Morocco is needed. The present article investigates the sorption behavior of imazethapyr herbicide toward six agricultural soils from Morocco in batch equilibrium experiments at pH 5 and evaluates the effect of the organic matter, the clay content, and the cation exchange capacity (CEC) on the sorption by applying simple and multiple linear regressions. Freundlich isotherm model described well the dynamic of imazethapyr sorption in all studied soils under the experimental conditions. The linear regressions showed significant differences between the soil properties and their impact on the sorption. While simple regression revealed strong positive correlations between the sorption and both the soil clay content (R2=0.91) and CEC (R2=0.92), the multiple regression revealed a noteworthy influence of soil organic matter when combined with clays. Our findings showed a weak adsorption of imazethapyr on the selected Moroccan soils, in addition to a potential role of clay minerals and CEC in the retention of the herbicide compared to the organic matter. The low adsorptive capacity of the Moroccan soils urges the necessity of minimizing herbicide application rates in agricultural regions to prevent environmental detrimental impacts.

An artificial neural network approach to identify fungal diseases of cucumber (Cucumis sativus L.) plants using digital image processing

Nowadays, artificial intelligence solutions such as digital image processing and artificial neural networks (ANN) have become important applicable techniques in phytomonitoring and plant health detection systems. In this research, an autonomous device was designed and developed for detecting two types of fungi (Pseudoperonospora cubensis, Sphaerotheca fuliginea) that infect the cucumber (Cucumis sativus L.) plant leaves. This device was able to recognise the fungal diseases of plants by detecting their symptoms on plant leaves (downy mildew and powdery mildew). For leaves of cucumber inoculated with different spores of the fungi, it was possible to estimate the amount of hour post inoculation (HPI) by extracting leaves’ image parameters. Device included a dark chamber, a CCD digital camera, a thermal camera, a light dependent resistor lightening module and a personal computer. The proposed programme for precise disease detection was based on an image processing algorithm and ANN. Three textural features and two thermal parameters from the obtained images were measured and normalised. Performance of ANN model was tested successfully for disease recognition and detecting HPI in images using back-propagation supervised learning method and inspection data. Such this machine vision system can be used in robotic intelligent systems to achieve a modern farmer’s assistant in agricultural crop fields.

Performance evaluation of a machine vision system for insect pests identification of field crops using artificial neural networks

Feature extraction is a crucial part of advanced image recognition systems. In this research, an autonomous detection device was designed and developed for insect pest detection to improve the ability of intelligent systems in order to annihilate harmful insect pests in agricultural crop fields. Device included a dark chamber, a CCD digital camera, a LDR lightening module and a personal computer. The proposed programme for precise insect pest detection was based on an image processing algorithm and artificial neural networks (ANNs). After image acquisition, the insect pests’ images were extracted from original images with Canny filtration. Afterwards, four morphological and three textural features from the obtained images were measured and normalised. Performance of ANN model was tested successfully for Beet armyworm (Spodoptera exigua) recognition in images using back-propagation supervised learning method and inspection data. Results showed that proposed system was able to identify S. exigua in the images from other species. Such this machine vision system can be used in autonomous field robots to achieve a modern farmer’s assistant.

Perspectives of Economically Important Pests and Climatic Changes on Various Agricultural Field Crops: A Review

Perspectives of Economically Important Pests and Climatic Changes on Various Agricultural Field Crops: A Review

THE POPULATION EXTENSION ON THE ACCOUNT OF THE AGRICULTURAL AREAS IN THE COUNTRY SIDE OF AL-RAMADI DISTRICT SECTION (18) AL-TALAH

Section (18) occupies a distinguish location comparison with Al-Ramadi district and because of its location near of Euphrates river, near of the city center and the natural circumstances for rising agriculture makes it an important district for producing most of the agricultural field crops. The study area faces a big problem because of population growth. In section (18) Al-Talah, in 1987, the number of population was (7152) individual and increased in 2007 to (10244) individual. The number of living units were (400) units in 1987 and increased to (1240) units in 2007. that means the living units occupied a big agricultural areas that had the good quality cultivation. This threatens the agricultural production, in addition to that the number of population will reach (13771) persons in 2017 in the section according to the scanning counteraction and the population needs for living units in its both sides, agriculture and animal resources.

Agricultural Resources Allocation and Field Crops Competition

Problem statement: Field crops are considered as essential cash and food crops produced in River Nile State (RNS) of North Sudan include cereal, food-legumes, vegetables and fodders beside the perennial crops. They are the main source of household income and regarded as a major part of the daily diet for the Sudanese. In other words they play an important role in household food security and poverty alleviation. However, resources use efficiency for producing these crops is became critical due to high competition from high population pressure and chronic low and instable crop yields emanating from environmental stresses and poor use of improved technology pose challenges for resource management. Since resources are most essential economical inputs, the target should be when optimizing resources use to obtain maximum productivity per unit. The RNS is considered as one of the main supplier of these cereal and foodlegume crops to the country. The crops are commonly produced under pump irrigation from the River Nile. The production of field crops in the State are faced by numerous constraints namely inefficiency of resources use, low level of productivity and high cost of production. The study aims to assess the allocation of the available resources use over the competitive field crops of the dominant crop combination. Approach: It was on this basis that a study was prepared out in RNS to establish resource combination levels that maximize gross margins from food and cash crops that commonly grown within the combination. Primary data was collected by using structured questionnaires for (70) randomly selected respondents from Elzeidab scheme public irrigated scheme of RNS as a case study. A linear programming technique through the General Algebraic Modeling System (GAMS) program was used to assess the optimally combining resources in the prevalent field crops. Results: The model results revealed that tenants would get higher returns by allocating more resources namely land, water, labor and capital to the food legume crops production. Higher net benefits would be from food legume crops production and least from exclusion them. Conclusion: The RNS tenants should therefore, be guided on how to optimally and efficiently utilize their resources and be encouraged to grow food legume crops that give production and yield advantages, earn high returns and contributed significantly to farm sustainability and alleviates malnutrition in RNS.

Carbon dioxide, water vapor, and heat fluxes over agricultural crop field in an arid oasis of Northwest China, as determined by eddy covariance

Fluxes of carbon dioxide, water vapor, and heat were measured above crop canopy using the eddy covariance method during the 2008 maize growing season, over an agricultural field within an oasis located in the middle reaches of Heihe River basin, northwest China. The values for friction velocity, the Monin–Obukhov stability parameter, and energy balance closure indicated that the eddy covariance system at this study site provided reliable flux estimates. Results from measurements showed that the mean sensible heat flux was 70 W m−2 with a maximum value of 164 W m−2 (May) and a minimum value of 45 W m−2 (July) during the maize growing season. In contrast, the mean latent heat was 278 W m−2 with a maximum value of 383 W m−2 (July) and minimum of 101 W m−2 (May). The mean downward soil heat flux was 55 W m−2 with a maximum value of 127 W m−2 (May) and minimum of 49 W m−2 (July). The magnitude of mean daytime net CO2 uptake was −11.50 μmol m−2 s−1 with a maximum value of −28.32 μmol m−2 s−1 (18 and 19 July) and a minimum values of −0.32 μmol m−2 s−1 (18 and 19 May). Correlation was observed between daytime half-hourly carbon dioxide flux and canopy conductance. In addition, the relationship between carbon dioxide flux and photosynthetically active radiation for selected days during different stages of maize growing season indicated the carbon dioxide flux uptake by the canopy was controlled by actual photosynthetic activity related to the variation of green leaf area index for the different growing stages.

Predicting Ground Effects of Omnidirectional Antennas in Wireless Sensor Networks

Omnidirectional antennas are often used for radio frequency (RF) communication in wireless sensor networks (WSNs). Outside noise, electromagnetic interference (EMI), overloaded network traffic, large obstacles (vegetation and buildings), terrain and atmospheric composition, along with climate patterns can degrade signal quality in the form of data packet loss or reduced RF communication range. This paper explores the RF range reduction properties of a particular WSN designed to operate in agricultural crop fields to collect aggregate data composed of subsurface soil moisture and soil temperature. Our study, using simulation, anechoic and field measurements shows that the effect of antenna placement close to the ground (within 10 cm) signi?cantly changes the omnidirectional transmission pattern. We then develop and propose a prediction method that is more precise than current practices of using the Friis and Fresnel equations. Our prediction method takes into account environmental properties for RF communication range based on the height of nodes and gateways.

Comparison of a score‐based approach with risk‐based ranking of in‐use agricultural pesticides in canada to aquatic receptors

AbstractThe purpose of this paper is to present a new risk‐based approach developed by Environment Canada for ranking pesticides and their potential risk to aquatic life. These rankings are compared to those generated using a more traditional score‐based approach. Two hundred and twelve active ingredients registered in Canada for use in agricultural field crops were included in this assessment. For each major aquatic taxon assessed (fish, insects, crustaceans, algae, and macrophytes), risk was calculated by dividing the 96‐h estimated environmental concentration (modeled using parameters such as the application rate and method as well as physicochemical properties) by HC5 values (obtained through calculations of species sensitivity distribution — based toxicity endpoints). The traditional approach assigned scores based on toxicity endpoints in standard test species as well as physicochemical properties associated with the potential for aquatic contamination. A number of similarities were observed between the rankings but also notable differences. Only 22 active ingredients were common to the top 50 ranking positions from both approaches. The main reasons that accounted for the discrepancies between both rankings were the choice of toxicity endpoints, whether based on single or multiple species; the taxonomic breadth of retained data; the use of scores versus risk quotients; and the choices made in situations where multiple data points were available. We conclude that a risk‐based approach that considers a broad representation of species toxicity data and estimates of runoff and drift concentration in receiving aquatic systems (even from generic application scenarios) is a more realistic representation of potential toxicological effects and a superior method of ranking products for the risk they pose to the aquatic environment.

Comparison of a Score-Based Approach with Risk-Based Ranking of In-Use Agricultural Pesticides in Canada to Aquatic Receptors

The purpose of this paper is to present a new risk-based approach developed by Environment Canada for ranking pesticides and their potential risk to aquatic life. These rankings are compared to those generated using a more traditional score-based approach. Two hundred and twelve active ingredients registered in Canada for use in agricultural field crops were included in this assessment. For each major aquatic taxon assessed (fish, insects, crustaceans, algae, and macrophytes), risk was calculated by dividing the 96-h estimated environmental concentration (modeled using parameters such as the application rate and method as well as physicochemical properties) by HC5 values (obtained through calculations of species sensitivity distribution-based toxicity endpoints). The traditional approach assigned scores based on toxicity endpoints in standard test species as well as physicochemical properties associated with the potential for aquatic contamination. A number of similarities were observed between the rankings but also notable differences. Only 22 active ingredients were common to the top 50 ranking positions from both approaches. The main reasons that accounted for the discrepancies between both rankings were the choice of toxicity endpoints, whether based on single or multiple species; the taxonomic breadth of retained data; the use of scores versus risk quotients; and the choices made in situations where multiple data points were available. We conclude that a risk-based approach that considers a broad representation of species toxicity data and estimates of runoff and drift concentration in receiving aquatic systems (even from generic application scenarios) is a more realistic representation of potential toxicological effects and a superior method of ranking products for the risk they pose to the aquatic environment.

Organic marker compounds in surface soils of crop fields from the San Joaquin Valley fugitive dust characterization study

Fugitive dust from the erosion of arid and fallow land, after harvest and during agricultural activities, can at times be the dominant source of airborne particulate matter. In order to assess the source contributions to a given site, chemical mass balance (CMB) modeling is typically used together with source-specific profiles for organic and inorganic constituents. Yet, the mass balance closure can be achieved only if emission profiles for all major sources are considered. While a higher degree of mass balance closure has been achieved by adding individual organic marker compounds to elements, ions, EC, and organic carbon (OC), major source profiles for fugitive dust are not available. Consequently, neither the exposure of the population living near fugitive dust sources from farm land, nor its chemical composition is known. Surface soils from crop fields are enriched in plant detritus from both above and below ground plant parts; therefore, surface soil dust contains natural organic compounds from the crops and soil microbiota. Here, surface soils derived from fields growing cotton, safflower, tomato, almonds, and grapes have been analyzed for more than 180 organic compounds, including natural lipids, saccharides, pesticides, herbicides, and polycyclic aromatic hydrocarbon (PAH). The major result of this study is that selective biogenically derived organic compounds are suitable markers of fugitive dust from major agricultural crop fields in the San Joaquin Valley. Aliphatic homologs exhibit the typical biogenic signatures of epicuticular plant waxes and are therefore indicative of fugitive dust emissions and mechanical abrasion of wax protrusions from leaf surfaces. Saccharides, among which α- and β-glucose, sucrose, and mycose show the highest concentrations in surface soils, have been proposed to be generic markers for fugitive dust from cultivated land. Similarly, steroids are strongly indicative of fugitive dust. Yet, triterpenoids reveal the most pronounced distribution differences for all types of cultivated soils examined here and are by themselves powerful markers for fugitive dust that allow differentiation between the types of crops cultivated. PAHs are also found in some surface soils, as well as persistent pesticides, e.g., DDE, Fosfall, and others.

Determination of starch and maltose content in some hybrid maize varieties by using HPLC

In this research, starch and maltose content were determined by using the HPLC method for different dent maize hybrids, grown in Tekirdag ecological conditions. Experimental materials were obtained from Tekirdag Faculty of Agricultural Field Crops Department. The starch and maltose content of the thirty-five selected maize varieties were studied. Starch contents of OSSK 644 (84.73%), Karacay (84.39%) and AG 9242 (84.09%) were found to be higher than the other varieties. The lowest starch content (45.02%) was obtained from variety DK-647. The maltose content of maize hybrids was varied from 0.83% (Pegaso) to 2.71% (AG 9229). Negative and insignificantly correlation was obtained between starch and maltose content (r 2 −0.150).

The Role of Uncomposted Materials, Composts, Manures, and Compost Extracts in Reducing Pest and Disease Incidence and Severity in Sustainable Temperate Agricultural and Horticultural Crop Production—A Review

This review evaluates evidence of the impactof uncomposted plant residues, composts, manures, and liquid preparations made from composts (compost extracts and teas) on pest and disease incidence and severity in agricultural and horticultural crop production. Most reports on pest control using such organic amendments relate to tropical or arid climates. The majority of recent work on the use of organic amendments for prevention and control of diseases relates to container-produced plants, particularly ornamentals. However, there is growing interest in the potential for using composts to prevent and control diseases in temperate agricultural and horticultural field crops and information concerning their use and effectiveness is slowly increasing. The impact of uncomposted plant residues, composts, manures, and compost extracts/teas on pests and diseases is discussed in relation to sustainable temperate field and protected cropping systems. The factors affecting efficacy of such organic amendments in preventing and controlling pests and disease are examined and the mechanisms through which control is achieved are described.