Crop Loss Assessment Research Articles

Improvement and Validation of NASA/MODIS NRT Global Flood Mapping

The remote-sensing based Flood Crop Loss Assessment Service System (RF-CLASS) is a web service based system developed and managed by the Center for Spatial Information Science and Systems (CSISS). The system uses Moderate Resolution Imaging Spectroradiometer (MODIS)-based flood data, which was implemented by the Dartmouth Flood Observatory (DFO), to provide an estimation of crop loss from floods. However, due to the spectral similarity between water and shadow, a noticeable amount of false classification of shadow can be found in the DFO flood products. Traditional methods can be utilized to remove cloud shadow and part of mountain shadow. This paper aims to develop an algorithm to filter out noise from permanent mountain shadow in the flood layer. The result indicates that mountain shadow was significantly removed by using the proposed approach. In addition, the gold standard test indicated a small number of actual water surfaces were misidentified by the proposed algorithm. Furthermore, experiments also suggest that increasing the spatial resolution of the slope helped reduce more noise in mountains. The proposed algorithm achieved acceptable overall accuracy (>80%) in all different filters and higher overall accuracies were observed when using lower slope filters. This research is one of the very first discussions on identifying false flood classification from terrain shadow by using the highly efficient method.

Effect of initial infestation on population fluctuation and spatial distribution of Panonychus citri (Acari: Tetranychidae) on Thomson navel orange in Ghaemshahr, Iran

Citrus red mite (CRM), Panonychus citri (McGregor) (Acari: Tetranychidae) is one of the important citrus pests in different parts of the world including northern Iran. Population fluctuation and spatial distribution pattern of this pest was studied in Ghaemshahr, northern Iran during 2016–2017 in different initial infestation treatments (paired-treatment and multiple-treatment experiments) that had been designed for crop loss assessment caused by CRM. Taylor's Power Law and Iwao's Patchiness Regression methods were used to determine the spatial distribution pattern of CRM. The results showed that the highest population density of the pest was during summer of 2016 and 2017 with an average of 127.3 and 91.15 CRM per leaf, respectively, and the population declined in the fall with an average of near zero mites per leaf. The spatial distribution pattern of CRM in both years and both methods was aggregated with an exception in which it was random. It could be concluded that initial infestion with different densities of the pest affected the population fluctuation of the pest during the growing season and somewhat the spatial distribution pattern of CRM.

Multiple-Disease System in Coffee: From Crop Loss Assessment to Sustainable Management.

Assessment of crop loss due to multiple diseases and pests (D&P) is a necessary step in designing sustainable crop management systems. Understanding the drivers of D&P development and yield loss helps identify leverage points for crop health management. Crop loss assessment is also necessary for the quantification of D&P regulation service to identify promising systems where ecosystem service provision is optimized. In perennial crops, assessment of crop losses due to D&P is difficult, as injuries can affect yield over years. In coffee, one of the first perennials in which crop loss trials were implemented, crop losses concurrent with injuries were found to be approximately 50% lower than lagged losses that originated following the death of productive branches due to D&P. Crop losses can be assessed by field trials and surveys, where yield reduction factors such as the number of productive branches that have died are quantified, and by modeling, where damage mechanisms for each injury are considered over several years.

Predicting potato tuber yield loss due to early blight severity in the Midwestern United States

Although early blight is among the most damaging foliar diseases of potato, the information available on the disease-yield relationship is scarce. Twenty-three field trials were conducted from 2003 to 2016 across North Dakota and Minnesota potato growing regions to study the relationships among disease severity estimated from tuber initiation (TI) to early bulking (growth stage III to IV) and late bulking/tuber maturation (growth stage IV to V) and yield. The strength of the association and the functional relationships between crop and disease variables were assessed based on estimates of the Fisher’s Z transformation of Pearson correlation r, the intercept (β0) and slope(β1) for each trial, which were combined and analyzed using meta-analytic models. At TI to early bulking stage, random-effect model estimated a slope of 0.20 mt/ha/%−1 for an expected yield (intercept) of 61.88 mt/ha. Each unit increase in percent severity at this growth stage would result in a 32 percentage point (pp) yield reduction. During late bulking/tuber maturation crop growth stage, the random-coefficients β0 and β1 were 65.89 mt/ha and 0.13 mt/ha/%−1, respectively. In relative terms, yield would be reduced by 19 pp. for each unitary percentage increase in early blight severity. Based on these meta-analysis results, growers are able to predict potential yield loss for each percentage increase of early blight severity at two growth stages, which can be useful for crop-loss assessments.

Assessment of crop loss due to leafhopper, (Empoasca kerri Pruthi) in pigeonpea

An experiment was conducted at Agriculture Research Station, Kalaburagi, Karnataka, India during kharif, 2015-16 to understand the effect of differential population of leafhoppers, on growth and yield parameters of pigeonpea under field conditions with seven level of population load. Maximum of 26.16 hoppers/3 leaves were found at 12 pairs release plot which was at par with 10 pairs (22.21) and 8 pairs (24.96) released which were statistically significant. The average hopper count @ 4 and 6 pairs released plots were 13.14 and 16.15 per 3 leaves respectively and were at par among themselves and significantly higher than 2 pairs release and lower than 8 pairs release plots. This was a clear indication that the differential population of leafhopper had impact in reduction of growth and yield parameters with. Reduction in yield to the tune of 3.12, 5.29, 10.05, 17.99, 24.63 and 31.91 % at 2, 4, 6, 8, 10 and 12 pairs released plots, respectively. From the present investigation it was clear that the 5.59 to 5.77 leafhoppers aggregated in top leaf at 90 to 120 days aged crop of medium duration variety will cause 10 per cent reduction in yield.

RF-CLASS: A remote-sensing-based flood crop loss assessment cyber-service system for supporting crop statistics and insurance decision-making

Floods often cause significant crop loss in the United States. Timely and objective information on flood-related crop loss, such as flooded acreage and degree of crop damage, is very important for crop monitoring and risk management in agricultural and disaster-related decision-making at many concerned agencies. Currently concerned agencies mostly rely on field surveys to obtain crop loss information and compensate farmers' loss claim. Such methods are expensive, labor intensive, and time consumptive, especially for a large flood that affects a large geographic area. The results from such methods suffer from inaccuracy, subjectiveness, untimeliness, and lack of reproducibility. Recent studies have demonstrated that Earth observation (EO) data could be used in post-flood crop loss assessment for a large geographic area objectively, timely, accurately, and cost effectively. However, there is no operational decision support system, which employs such EO-based data and algorithms for operational flood-related crop decision-making. This paper describes the development of an EO-based flood crop loss assessment cyber-service system, RF-CLASS, for supporting flood-related crop statistics and insurance decision-making. Based on the service-orientated architecture, RF-CLASS has been implemented with open interoperability specifications to facilitate the interoperability with EO data systems, particularly the National Aeronautics and Space Administration (NASA) Earth Observing System Data and Information System (EOSDIS), for automatically fetching the input data from the data systems. Validated EO algorithms have been implemented as web services in the system to operationally produce a set of flood-related products from EO data, such as flood frequency, flooded acreage, and degree of crop damage, for supporting decision-making in flood statistics and flood crop insurance policy. The system leverages recent advances in the remote sensing-based flood monitoring and assessment, the near-real-time availability of EO data, the service-oriented architecture, geospatial interoperability standards, and the standard-based geospatial web service technology. The prototypical system has automatically generated the flood crop loss products and demonstrated the feasibility of using such products to improve the agricultural decision-making. Evaluation of system by the end-user agencies indicates that significant improvement on flood-related crop decision-making has been achieved with the system.

Stalk rot fungi affect grain sorghum yield components in an inoculation stage-specific manner

Although stalk rots are among the most prevalent and destructive diseases of sorghum, no systematic crop loss assessment has been reported for these diseases under controlled-inoculations. The objective of this study was to assess the impacts of Fusarium stalk rot and charcoal rot on grain sorghum yield components when plants were inoculated at two growth stages (GS). Four genotypes were field evaluated against three Fusarium spp. (F. thapsinum, F. proliferatum, F. andiyazi) and Macrophomina phaseolina. Inoculations were performed at GS1 (30 d after emergence) and GS3 (14 d after flowering). Panicles were harvested at physiological maturity and assessed for total seed weight (TSW), 100-seed weight (100-SW), and total seeds per panicle (TSP). The total number of reproductive sites and unfilled spikelets were counted per rachis (TRSR and NUSR, respectively) and panicle (TRSP, NUSP) bases. Length and nodes crossed by the lesion in split stems were measured to evaluate disease severity. Pathogens significantly reduced TSW in comparison to the control at both GS1 and GS3. The four pathogens, on average, caused greater TSW reductions when inoculated at GS1 (52%) than at GS3 (37%). All pathogens reduced TSP upon GS1 inoculation and 100-SW upon GS3 inoculations. All pathogens significantly reduced seed set percentage when plants were inoculated at GS1 while inoculations at GS3 did not have a significant impact. GS1 inoculations significantly decreased TRSP, demonstrating pathogen interference with head formation resulting in smaller heads than control. Although inoculations at GS1 had a greater impact on yield, inoculations at GS1 and GS3 did not significantly differ in disease severity. This study revealed inoculation stage-specific effects of stalk rot pathogens on yield parameters and provided insights into key yield traits to be emphasized in sorghum breeding programs to produce stalk rot tolerant sorghum genotypes.

Aerial multispectral imaging for crop hail damage assessment in potato

Crop loss assessment after an event of hailstorm can be inaccurate, subjective, and time consuming with the conventional method. Low-altitude, high-resolution aerial imaging using an unmanned aerial vehicle can be utilized for rapid assessment of target crops in a large scale, which can potentially improve the evaluation procedure. The goal of this study was to evaluate the feasibility of rapid and accurate assessment of crop damage due to simulated hailstorms using aerial multispectral imaging. Field experiments were conducted during two seasons in two potato varieties (Russet Norkotah, Ranger Russet) with three levels of mechanical defoliation (33%, 66%, and 99%) at three growth stages (tuber initiation, early bulk, and late bulk). All defoliation treatments were compared to the non-treated control plots (0% defoliation). Aerial multispectral images were collected between 77 and 108days after planting (0–60days after damage). Vegetation indices such as green normalized difference vegetation index (GNDVI), normalized difference vegetation index, and soil-adjusted vegetation index were calculated from replicate plots of different treatments. Results from two seasons showed similar trends in GNDVI values, with maximum effect of hail damage observed in early bulk stages. The mean GNDVI value was significantly lower in crops with the severe damage (99% defoliation) than others upon hail damage at the early bulk stage, with imaging after 10days after damage. The difference in GNDVI for crops with 33–66% damage could be detected within 10days after damage, and crop regrowth after that time period removed the effects of defoliation. The 99% defoliation damage at the early bulk stage also affected the crop yield significantly. Correlation analysis between vegetation indices and yield data indicated a strong relationship (r=0.77–0.90) for damage at the early bulk stage than other stages.

Plant Diseases and Management Approaches in Organic Farming Systems.

Organic agriculture has expanded worldwide. Numerous papers were published in the past 20 years comparing plant diseases in organic and conventional crops. Root diseases are generally less severe owing to greater soil health, whereas some foliar diseases can be problematic in organic agriculture. The soil microbial community and nitrogen availability play an important role in disease development and yield. Recently, the focus has shifted to optimizing organic crop production by improving plant nutrition, weed control, and plant health. Crop-loss assessment relating productivity to all yield-forming and -reducing factors would benefit organic production and sustainability evaluation.

Estimation of yield loss in sunflower due to new sunflower leaf curl virus disease at different stages of crop growth

An experiment was carried out to assess the crop loss due to sunflower leaf curl virus (SuLCV) disease. The crop loss assessment in terms of growth and yield components was recorded at first appearance of symptoms of SuLCV at 30 days to 90 days during the crop growth. The SuLCV disease infection in sunflower significantly affected the plant height (72.60 to 157cm), size of the head (8.60 to 18.78cm), 100 seed weight (2.20 to 6.32g), oil content (31.24% to 38.26%), and weight of seeds/10 heads (77.20 to 372.2g) as compared to the healthy control plants. In the plants, first appearance of symptoms at 30 DAS was recorded the seed yield loss of 79.25 per cent.

Crop loss assessment of diseases for various barley cultivars in golestan province, iran

Crop loss assessment of diseases for various barley cultivars in golestan province, iran

Meta-analysis of the relationship between crop yield and soybean rust severity.

Meta-analytic models were used to summarize and assess the heterogeneity in the relationship between soybean yield (Y, kg/ha) and rust severity (S, %) data from uniform fungicide trials (study, k) conducted over nine growing seasons in Brazil. For each selected study, correlation (k=231) and regression (k=210) analysis for the Y-S relationship were conducted and three effect-sizes were obtained from these analysis: Fisher's transformation of the Pearson's correlation coefficient (Zr) and the intercept (β0) and slope (β1) coefficients. These effect-sizes were summarized through random-effect and mixed-effect models, with the latter incorporating study-specific categorical moderators such as disease onset time (DOT) (<R1 or ≥R1 reproductive crop stage), disease pressure (DP) (high=>70%, moderate=>40 and ≤70%, and low=≤40% S the check treatment), and growing season. The overall mean for r- (back-transformed Z-r) was -0.61, based on the random-effects model. DOT and DP explained 14 and 25%, respectively, of the variability in Z-r. Stronger associations (r-=-0.87 and -0.90) were estimated by mixed-effects models for the Zr data from studies with highest DP (DP>70%) and earliest rust onset (DOT<R1), respectively. Overall means (based on a random-effect model) for the regression coefficients β-0 and β-1 were 2,977 and 18 kg/ha/%(-1), respectively. In other words, S as low as 3% would reduce 60 kg/ha for an expected Y of 3,000 kg/ha. In relative terms, each unitary percent increase in S would lead to a 0.6 percentage point (pp) reduction in Y. The three categorical moderator variables explained some (5 to 10%) of the heterogeneity in β-1 but not in β-0 The estimated relative reduction in Y was 0.41 to 0.79 pp/%(-1) across seasons. Highest relative yield reductions (>0.73 pp/%(-1)) were estimated for studies with DOT<R1 and DP>70%; the latter possibly due to high fungicide efficacy when DP is low, thus leading to higher yield differences between fungicide-protected and nontreated plots. The critical-point meta-analytic models can provide general estimates of yield loss based on a composite measure of disease severity. They can also be useful for crop loss assessments and economic analysis under scenarios of varying DOT and weather favorableness for epidemic development.

Disease Risk Curves

Disease risk curves are simple graphical relationships between the probability of need for treatment and evidence related to risk factors. In the context of the present article, our focus is on factors related to the occurrence of disease in crops. Risk is the probability of adverse consequences; specifically in the present context it denotes the chance that disease will reach a threshold level at which crop protection measures can be justified. This article describes disease risk curves that arise when risk is modeled as a function of more than one risk factor, and when risk is modeled as a function of a single factor (specifically the level of disease at an early disease assessment). In both cases, disease risk curves serve as calibration curves that allow the accumulated evidence related to risk to be expressed on a probability scale. When risk is modeled as a function of the level of disease at an early disease assessment, the resulting disease risk curve provides a crop loss assessment model in which the downside is denominated in terms of risk rather than in terms of yield loss.

Spatiotemporal yield loss assessment in corn due to common rust caused by Puccinia sorghi Schw.

A field experiment was carried out in deep black soil at Main Agricultural Research Station, College of Agriculture, University of Agricultural Sciences, Dharwad, Karnataka during kharif 2010, under rain-fed condition. The yield losses due to common rust were found directly related to disease severity. The avoidable yield losses due to disease were in the range of 11.75 to 60.53% in different spray schedule. Crop loss assessment at different fungicide spray schedule revealed that there was significant reduction in yield when disease severity was more than 50%. Six sprays of the Hexaconazole at 0.1% completely controlled the disease and contributed to increased yield. Key words: Maize, common rust, Puccinia sorghi, yield loss.

Crop loss analysis and global food supply: focusing now on required harvests.

Abstract Historically, the path of crop loss assessment research has known three phases: exploratory, development and implementation. These phases took place at different periods of agricultural research, with a common thread to improve our knowledge of the impact of diseases on crop yield quantity and quality. In this review, we provide a discussion on these phases. In particular, we emphasize the seminal research that has laid a foundation for a new phase to develop. We do this through an examination of the measurement of injury and crop losses, the current statistical models used to define thresholds and damage functions, and what is currently known regarding qualitative losses. Crop loss research enters a fourth phase of crop loss assessment, the multi-criteria assessment phase. In the latter portion of the review, we provide a brief discussion on the efforts, the concepts, and the necessary multidisciplinary dialogue, that the multi-criteria assessment phase requires in order for crop loss assessment to truly change the ways diseases are managed and how management itself is truly seen among the disciplinary fields that contribute to sustainable agricultural development.

Assessing the potential economic impact of Bacillus thuringiensis (Bt) maize in Kenya

The Insect Resistant Maize for Africa (IRMA) project is currently developing Bt maize for Kenya. So far, Bt genes with resistance to Ch ilo partellus, Chilo orichalcociliellus, Eldana sacharina , and Sesamia calamistis , four of the five major stemborers were successfully incorporated into elite CIMMYT maize inbred line (CML216) and tested in insect bioassays in Kenya. Participatory Rural Appraisals showed that stem borers are indeed major pest problems for farmers. Four seasons of on-farm crop loss assessment showed an average crop loss of 13.5%, or 0.4 million tons, valued at US$ 80 million. If the project manages to find a Bt gene that is effective to the fifth stemborer, Busseola fusca, adoption rates are likely to be high, and therefore the returns. Under standard assumptions, the economic surplus of the project is calculated at $ 208 million over 25 years (66% of which is consumer surplus) as compared to a cost of $5.7 million. Geographically, the project should focus on the high production moist-transitional zone. However, if such gene cannot be found, Bt maize technology would only be effective in the low potential areas, and adoption rates would be fairly low, although benefits would still exceed costs. Key words : Maize, genetically modified crops, Bacillus thuringiensis, adoption, economic impact.

Leaf-eating caterpillar ( Opisina arenosella)-induced yield loss in coconut palm

Coconut is one of the major crops of commercial importance among the palms. The leaf-eating caterpillar Opisina arenosella Walker is the most important lepidopteran pest of coconut palm in India and Sri Lanka. Assessment of crop loss is essential for a realistic planning for research and developmental policies. Information on the yield loss in coconut due to O. arenosella attack is very meagre. In the present study, results of investigations carried out on leaf-eating caterpillar-induced yield loss in coconut palms in Kerala, India, for a period of 4 years (2002-2005) are presented. A maximum crop loss of 45.4% in terms of nut yield was recorded from infested palms in the succeeding year of severe pest incidence. The infested palms also showed reduction in bunch and leaf production to the tune of 21.0 and 13.8%, respectively. The pest-attacked palms regained their normal yield potential by the fourth year after heavy pest infestation.

Estimating the threshold value and loss distribution: Rice damaged by typhoons in Taiwan

We apply extreme value theory to determine the over-threshold peaks of the data and then use the Kolmogorv-Smirnov and Anderson-Darling goodness of fit tests to show that the generalized Pareto distribution fits the heavy-tailed distribution better than the Lognormal, Gamma, Weibull and Normal distributions in rice damaged by typhoons. The appropriate of the threshold value and probable maximum loss can be calculated as one of reference indexes on risk retention or/and crop insurance associated with the natural systematic risk of major agricultural disasters. The properties we found are useful in crop loss assessment and in the decision making of government's risk financing for major agricultural disasters. Our method may be applied to other disasters and other countries. Key words: Natural disasters, generalized Pareto distribution, heavy-tailed distribution, threshold value, probable maximum loss.

Fairy Ring Disease of Cranberry: Assessment of Crop Losses and Impact on Cultivar Genotype.

Fairy ring is a disease of cultivated cranberry common in the eastern growing regions of the United States, especially New Jersey and Massachusetts. Rings may persist for many years, and current control recommendations are costly and largely ineffective. The goal of this study was to accurately assess the impact of this disease on cranberry, a long-lived, high-value, perennial crop. The rate of fairy ring expansion, rate of formation of new rings, and distribution of rings across three cultivars were determined using a geographical information system (GIS) database that incorporated aerial and satellite imagery. Ring growth rates, estimated from imagery collected over a 10-year period in cv. Ben Lear, averaged 0.455 m in radius per year. Rings were observed in 'Ben Lear' three times more frequently than in either 'Early Black' or 'Stevens' cultivars. Direct sampling showed that estimates for yield within rings were 22 to 68% less than unaffected areas of the field for cv. Ben Lear. These estimates included the effects of fruit rot, which was elevated within rings to 18 to 29% of the total harvest. The impact on yield of 'Stevens' and 'Early Black' was lower than in 'Ben Lear'. Most cranberry cultivars are clonal and variation in fruit morphology within rings, particularly in 'Ben Lear', prompted an analysis of vine genotype. Areas affected by fairy ring in 'Ben Lear' showed an increase in genetic diversity at least 0.4 to 4 times that of unaffected areas. Therefore, it appears that fairy ring not only directly reduces yield but also can increase the host genetic diversity. This likely is due to increased seedling establishment resulting from seed drop when fruit decompose. Because seedlings typically yield less than the parental cultivar, the increase in genetic diversity also may contribute to long-term reduction of productivity in a cranberry field.

Evaluating mechanical wounding as a surrogate for aspen shoot blight caused by Pollaccia americana in the assessment of crop loss

It is difficult to maintain, in trembling aspen (Populus tremuloides), controlled levels of aspen shoot blight (ASB) caused by Pollaccia americana, under field conditions. Thus, simulating the disease by mechanical wounding may be useful in crop-loss assessment. Three treatments were compared to evaluate the suitability of decapitation as a surrogate for ASB: (1) artificial inoculation with P. americana causing ASB and (2) cutting of the shoot between the fifth and sixth expanded leaves (decapitation), both these treatments being later referred to as injury treatments, and (3) no injury (control). The three treatments were applied to trees from four different seed lots, which subsequently grew under field conditions, and to two different clones held in a growth chamber at soil temperatures of 6, 12, or 20 °C. Leader length, frequency of axillary-shoot development, and lateral- and axillary-shoot lengths were evaluated. Trees infected with ASB and trees that were decapitated responded very similarly and had significantly longer leaders and more axillary shoots than did control trees. Although there were significant differences in branching patterns among seed lots, and significant clone and temperature effects on infection, the effects of treatments were typically consistent across all levels of clone, seed lot, and temperature. These results indicate that decapitation could be used to simulate ASB in assessing crop loss.