Estimated Yield Loss Research Articles

Impact of Gibberella Ear Rot on Grain Quality and Yield Components in Maize as Influenced by Hybrid Reaction.

The impact of Gibberella ear rot (GER; caused by Fusarium graminearum) on deoxynivalenol (DON) contamination of grain and yield components in maize were investigated using data from 30 environments in Ohio (3 years by 10 locations). Fifteen hybrids, later classified as susceptible (SU), moderately susceptible (MS), or moderately resistant (MR), based on the magnitude of differences in mean arcsine square-root-transformed GER severity (arcSEV) and log-transformed DON (logDON) relative to a reference SU check, were planted in each environment, and 10 ears per hybrid were inoculated with a spore suspension of F. graminearum. Relationships between GER severity and DON were well described by a Kono-Sugino-type nonlinear equation. Estimated parameters representing height (A) and steepness (β) of the curves were significantly higher for SU than MS and MR hybrids but A was not significantly different between MS and MR. Results from a surrogacy analysis showed that GER was a moderate trial- and individual-level surrogate for DON. Both grain weight per ear and ear diameter decreased with increasing arcSEV but the regression slopes varied among resistance classes. The rates of reduction in both yield components per unit increase in arcSEV were significantly greater for SU than for MS and MR. An estimated 50% reduction in grain weight occurred at 62% GER severity for SU, compared with 77% severity for MS and 83% for MR. These results show that GER severity can be used as a surrogate for early estimation of DON contamination and yield loss to help guide grain handling and marketing decisions.

Detection of fusarium head blight in wheat under field conditions using a hyperspectral camera and machine learning

Fusarium head blight (FHB) is among the most devastating fungal diseases in cereal crops, reducing yield, and affecting human and livestock health through the production of mycotoxin. Despite application of fungicides, complete eradication of disease is virtually impossible in the field. There is a need for a disease detection technology during late growing stage for estimation of yield affected with FHB and for potential selective harvesting. Most published studies have focused on FHB detection during the milk growth stage using hyperspectral cameras. This preliminary study attempted to fill the knowledge gap by detecting FHB at the ripening stage. A spectral library of healthy and infected ears was collected with a hyperspectral camera in the visible and near-infrared region, over the canopy of eight different wheat varieties. The ears were segmented from the background using a simple linear iterative clustering (SLIC) superpixel algorithm on the normalized difference vegetation index (NDVI) images. Three different machine learning methods, namely, support vector machine (SVM), artificial neural network (ANN), and logistic regression (LR), were utilized for classification. To visualize the FHB distribution in the hypercube, the best performing model was applied for predicting the infected ears in the canopy images. The percentage area coverage of FHB for each hypercube was estimated. Results showed that the SVM algorithm produced the best classification accuracy (CA) of 95.6 % in the test set, followed successively by ANN and LR with CA values of 82.9 and 82.5 %, respectively. Interestingly, the preliminary study shows significant differences in spectral reflectance according to the variety of different resistance levels. The study also proves the feasibility of FHB detection using the developed prediction model during late growth stage with the potential of yield loss estimation before harvest.

Impact of Pratylenchus penetrans on Soybean Grown in Wisconsin, U.S.A.

Models were developed to quantify the impact of Pratylenchus penetrans to the early season growth and yield of soybean in field and greenhouse environments and to estimate yield loss because of P. penetrans in Wisconsin. There was a negative linear relationship between initial nematode population densities (Pi) and shoot and total plant weight at V2 and yield, pod number, seed number, and seed mass at harvest in the field. Relative yield loss, modeled for the second year of the field experiment, suggested a loss of 4.5% for yield and between 2.4 and 2.8% for yield components at the mean field Pi value. Negative linear relationships were demonstrated for the relative loss in those variables as well as for harvest index and shoot, root, and total plant weight at harvest in the greenhouse. Stress imposed by P. penetrans began within 2 weeks after planting and continued through harvest. Estimates of the percent loss attributed to each nematode Pi value were 0.020% for yield, 0.015% for pod number, and 0.017% for seed number. Pratylenchus spp. was the most widely prevalent pest nematode among samples submitted to a statewide nematode testing program. Molecular identification of a subset of 63 samples suggested 15% were infested with P. penetrans at a mean Pi value of 197 P. penetrans per 100 cm3 soil. Yield loss because of P. penetrans, estimated from prevalence data and our empirical greenhouse model, ranged from 0.23 to 2.76% among Wisconsin's agricultural districts. The cumulative impact for all Pratylenchus spp. is likely much greater, given this loss estimate does not account for the monoecious species present in 79% of the samples.

Assessment of maize yield losses due to the effect of fall armyworm (Spodoptera frugiperda) infestation: the case of Trans-Nzoia County, Kenya

Invasive alien species have emerged as a production constraint, the most recent in Kenya being fall armyworm (FAW) (Spodoptera frugiperda). The pest incidence has resulted in farmer welfare damage by exacerbating the maize yield gap, a principal staple crop in Kenya. Through a field survey, 257 farmers were interviewed. Farmer perceived direct estimates and an iterative bidding procedure were used to assess maize yield losses. The majority of farmers (99%) were aware of fall armyworm and could correctly identify it. Moreover, most of the farmers (94%) ranked fall armyworm as the major pest for the 2018 cropping season, with more than 43% of the farmers describing the resulting yield loss as high. Yield loss estimates ranged between 0.18 to 2.7 tonnes per acre. Farmers adopted a combination of control strategies, to mitigate the effect of FAW. We conclude that FAW is a problematic pest in Kenya, based on the observed significant losses due to this pest. To inform policy on appropriate and prioritization of resources to manage FAW, yield loss estimates are key.

Squash Leaf Curl Virus: Species of Begomovirus as the Cause of Butternut Squash Yield Losses in Indonesia

Curling symptom was found in pumpkin plants in Bali, and the PCR detection result using Begomovirus universal primers indicated Begomovirus infection. Further research was conducted to determine the distribution, molecular character of SLCV, and yield loss of the pumpkins. Sampling was carried out at pumpkin plantations in 9 districts in Bali. Detection and identification were carried out using PCR method, followed by cloning and DNA sequencing. DNA band with the measurement of 900 bp was successfully amplified from several pumpkin samples from Denpasar, Gianyar, and Buleleng. Homology analysis of nucleotide sequences using the database in GenBank of SLCV of Balinese isolates showed the highest homology and kinship of 97.3-98.4% and 98.4-99.3% respectively with East Timor isolates from pumpkin plants. The phylogeny analysis showed that SLCV Indonesian isolates were in the same group as Asian isolates. The result of this study is the first report on infection and molecular characterization of SLCV in pumpkin plants in Indonesia. The yield loss caused by curling disease on individual pumpkin plants was 56.3%, and the disease caused a decrease in the quality of harvest fruits. Yield loss estimation caused by the disease in fields with different levels of disease intensity ranged from 10.02 to 25.83%. It was equal to yield loss ranging from IDR 878,400.00 to IDR 10,826,400.00 depending on the disease intensity. It is found that the correlation between curling disease severity and yield loss was high.

Differential responses of soybean genotypes to off‐target dicamba damage

AbstractSince the commercialization and widespread adoption of dicamba‐tolerant (DT) soybean cultivars across the United States, numerous cases of off‐target damage to non‐DT soybean have been reported. Soybean is naturally highly sensitive to dicamba, a synthetic auxin herbicide. Previous studies have focused on understanding the impact of growth stage, dosage, frequency, and duration of dicamba exposure on the severity of symptomology and yield loss. To date, little research has investigated the effect of genetic components in the observed responses. Therefore, this study was conducted to estimate yield losses caused by prolonged off‐target dicamba exposure and to identify genotypes with varying responses to off‐target damage. A total of 553 soybean genotypes derived from 239 unique biparental populations were evaluated in nine environments over 3 yr. A yield penalty of 8.8% was observed for every increment in damage score on a 1–4 scale with losses as high as 40%. Although the interaction between damage and maturity group (MG) significantly affected yield, genotypes showing the most tolerance had similar yields independent of their MG. This indicated that natural tolerance to off‐target dicamba may be conferred by physiological mechanisms other than the length of the recovery window. Given the widespread adoption of DT systems and potential yield losses in non‐DT soybean genotypes, identification of non‐DT soybean genotypes with higher tolerance to off‐target dicamba may sustain and improve the production of other non‐DT herbicide soybean production systems, including the niche markets of organic and conventional soybean.

Evaluation of Novel Fungicide for the Management of Soybean Anthracnose Disease and Yield Loss Estimation

Background: Soybean anthracnose is currently a severe threat to India’s soybean cultivation. There is limited information about estimated yield loss due to anthracnose and foliar fungicide application for its management. Methods: A novel fungicide, Picoxystrobin 7.05 per cent + Propiconazole 11.71 per cent (w/w) was evaluated for two consecutive years (2018 and 2019) in three different concentrations as a foliar application in combination with commercially available fungicides as standard checks to identify an alternative fungicide for management of soybean anthracnose disease. The yield loss was estimated from the data observed for two years in a row. Result: After three foliar applications of the novel fungicide, Picoxystrobin 7.05 per cent + Propiconazole 11.71 per cent w/w @ 0.20 per cent, the maximum disease control (PDC), the lowest disease index (PDI) and the area under the disease progress curve (AUDPC) were obtained. The maximum gross return was obtained following three foliar applications of Picoxystrobin 22.52 per cent (w/w) SC @ 0.08 per cent, but the maximum B:C ratio was estimated with foliar application of Hexaconazole 5.00 per cent EC @ 0.100 per cent. Anthracnose severity was found to be negatively correlated with soybean grain yield (r = -0.91). In every 1% increase in anthracnose disease severity reduced soybean yield by 115 kg per hectare.

Exploring the influence of weeds on cranberry yield and quality

AbstractThe influence of weeds on cranberry yield and quality is not well known and cannot be extrapolated from other cropping systems given the unique nature of both cranberry production and the weed species spectrum. The work presented here addresses this need with four common weed species across multiple production seasons and systems in Wisconsin, Massachusetts, and New Jersey: Carolina redroot, earth loosestrife, bristly dewberry, and polytrichum moss. The objectives were to use these representative species to quantify the impact of weed density, groundcover, and biomass on several cranberry yield components and related interactions with other cranberry pests, and to determine whether these relationships were consistent enough across seasons to be reliably used in weed management decision-making. The relationships between Carolina redroot and bristly dewberry growth measures and marketable cranberry yield were highly significant (P ≤ 0.001 in 12 of 13 regressions) and consistent across growing seasons, but not significant for similar regressions with earth loosestrife. In particular, the strong relationship between Carolina redroot and bristly dewberry visual groundcover observations and cranberry yield suggests a simple way for growers and crop scouts to reliably estimate yield loss. The relationship between polytrichum moss biomass and cranberry yield was also significant in both years, but not consistent between years. Weed competition also affected cranberry quality, in that Carolina redroot density was strongly related to the percentage of insect-damaged fruit and bristly dewberry growth reduced cranberry color development. On a practical level, this information can be used to educate growers, consultants, agrichemical registrants, and regulators about the impacts of weeds on cranberry yield and quality, and to economically prioritize management efforts based on the weed species and extent of infestation.

Lowland Ecotype Cyperus rotundus L. Affects Growth and Yield of Rice under Flooded Conditions in the Philippines

Lowland ecotype Cyperus rotundus L. has been reported to infest irrigated lowland ricefields in the Philippines. Its effects on the growth and yield of rice under flooded conditions are unknown. Two experimental runs were conducted in a screenhouse to determine the growth of lowland ecotype C. rotundus with transplanted and wet direct-seeded rice at sowing densities of 0, 22, 44, 66, and 88 initial germinating tubers m–2, as well as its effects on the growth and yield of rice. Except for height, growth variables of lowland ecotype C. rotundus were increased with the increase in its germinating tuber densities. Compared with 22 germinating tubers m–2, its number of off-shoots and tubers plus shoot and root biomass at 44–88 germinating tubers m–2 increased by up to three times. Growth variables of rice were reduced by the weed. Grain yield of transplanted rice was reduced by 14–38%, whereas that of wet direct-seeded rice was reduced by 11–28%. The estimated yield losses of transplanted rice per weed plant were 0.8 and 0.1% as germinating tuber density and number of off-shoots approached zero (i) and 75.7 and 66.1% as the variables approached infinity (a). Estimated yield losses of wet direct-seeded rice per weed plant were 0.6 and 0.1% as the two variables approached i and 63.8 and 100% as variables approached a. Results suggest that lowland ecotype C. rotundus can grow well and reduce the growth and yield of rice under flooded conditions. Although the findings were obtained under screenhouse conditions, the results imply the need of developing a holistic weed control strategy against the weed.

Estimating Economic Impacts of Beet Leafhopper1 on Potato and Carrot Crops in the Columbia Basin Region of Oregon and Washington

An expert opinion survey was administered to document use and cost of insecticides applied to manage beet leafhopper, Circulifer tenellus (Baker), on potato, Solanum tuberosum L., and carrot, Daucus carota L., crops in the Columbia Basin region of Oregon and Washington. Estimated total average cost of beet leafhopper management was $56.33 in carrot and $41.71 per hectare in potato. Perceptions of lost yield attributable to damage by beet leafhopper varied greatly. Estimates of yield loss were 0 to 15% in carrot and 0 to 30% in potato.

Estimation of Yield Loss of Jatropha curcas Due to Aphthona whitfieldi in Burkina Faso

Estimation of Yield Loss of Jatropha curcas Due to Aphthona whitfieldi in Burkina Faso

Economic impacts of reduced fungicide efficacy against downy mildew on slicing cucumber

Fungicides remain the most important tool to manage downy mildew on cucumber. The objective of this study was to estimate yield losses that might occur if fungicides to which Pseudoperonospora cubensis has demonstrated reduced efficacy were applied to slicing cucumber. A downy mildew-susceptible hybrid cultivar was grown in spring and fall 2020, sprayed weekly with one of four oomycete-specific fungicides (cymoxanil, fluopicolide, propamocarb, or oxathiapiprolin + chlorothalonil) applied in alternation with chlorothalonil. Control treatments were chlorothalonil applied biweekly and water. The fluopicolide-chlorothalonil treatment and the water control were repeated in spring 2021. Cucumbers were harvested 12 times, sorted by size, and weighed. Profits were calculated by subtracting production and fungicide application costs from the crop values, which were calculated with prices from terminal markets in the eastern United States during the harvest periods. Treatments performed the same in spring and fall 2020. Area under the disease progress curve (AUDPC) was significantly lower with fluopicolide, propamocarb, and oxathiapiprolin + chlorothalonil than cymoxanil and both controls (P = 0.01). AUDPC was lower with fluopicolide than with oxathiapiprolin + chlorothalonil. Mean marketable weights did not differ among the four fungicide treatments but were greater than in the two control treatments (P = 0.05). Profits also were greater for the four fungicide treatments than the controls, a mean of $8,829/ha versus $2,437/ha, respectively. Results with fluopicolide-chlorothalonil in 2021 confirmed results in 2020. Fungicides with reduced efficacy, like cymoxanil, or fungicides for which resistance has been reported, like propamocarb hydrochloride or fluopicolide, may still protect hybrid slicing cucumber from yield losses due to downy mildew.

Estimating yield loss of faba bean (Vicia faba L.) caused by gall disease in north Shoa, Ethiopia

Faba bean is the most important food legume crop; however, its productivity is threatened by faba bean gall (FBG) disease. Faba bean gall is an emerging and destructive disease in the highlands of Ethiopia. Field experiments were conducted on farmers’ field during the 2018 and 2019 cropping seasons in Bassona Worana district, Ethiopia under natural conditions to estimate yield losses on local cultivar and improved faba bean varieties and to determine fungicides spray schedules. The experiments consisted of two moderately tolerant (Degaga and Gora) faba bean varieties and one susceptible local cultivar, two fungicides [Bayleton 25 WP (Triadimefon 250 g kg−1) and Ridomil Gold MZ 68 WG (Metalaxyl 40 + Mancozeb 640 g kg−1)] and two application schedules (10 and 15 days). The treatments were arranged in randomized complete block design with three replications in factorial combinations. The results showed that use of different faba bean genotypes and applications of fungicides significantly (P < 0.001) reduced FBG disease epidemics and minimized grain yield loss. Variety Gora sprayed with Bayleton at 10 days interval recorded low mean FBG disease severity (26.7 and 13.0%) and AUDPC of 1866.7 and 751.7%-days in 2018 and 2019, respectively. High mean grain yields of 3.7 t ha−1 (2018) and 5.0 t ha−1 (2019) were also obtained from variety Gora sprayed with Bayleton at 10 days interval. High grain yield losses of 62.5% (Degaga), 54.1% (local cultivar) and 50.0% (Gora) were obtained from unsprayed plots of each genotype. Conversely, faba bean genotypes obtained yield increases of 166.4% (Degaga), 100% (Gora) and 121.3% (local cultivar) when treated with Bayleton at 10 days interval in 2018. Similar trends were observed regarding 100-seed weight (HSW) loss and in 2019. Moreover, unsprayed plots of each genotype recorded the highest disease severity and AUDPC and the lowest grain yield in both cropping years. On the other hand, faba bean grain yield and yield components demonstrated an inverse relationship with disease severity. Hence, use of tolerant faba bean varieties like Gora and application Bayleton at a rate of 0.7 kg ha−1 at 10 days interval is essential to manage FBG disease, thereby minimizing yield and HSW losses of faba bean in the study areas.

Potential of Multiway PLS (N-PLS) Regression Method to Analyse Time-Series of Multispectral Images: A Case Study in Agriculture

Recent literature reflects the substantial progress in combining spatial, temporal and spectral capacities for remote sensing applications. As a result, new issues are arising, such as the need for methodologies that can process simultaneously the different dimensions of satellite information. This paper presents PLS regression extended to three-way data in order to integrate multiwavelengths as variables measured at several dates (time-series) and locations with Sentinel-2 at a regional scale. Considering that the multi-collinearity problem is present in remote sensing time-series to estimate one response variable and that the dataset is multidimensional, a multiway partial least squares (N-PLS) regression approach may be relevant to relate image information to ground variables of interest. N-PLS is an extension of the ordinary PLS regression algorithm where the bilinear model of predictors is replaced by a multilinear model. This paper presents a case study within the context of agriculture, conducted on a time-series of Sentinel-2 images covering regional scale scenes of southern France impacted by the heat wave episode that occurred on 28 June 2019. The model has been developed based on available heat wave impact data for 107 vineyard blocks in the Languedoc-Roussillon region and multispectral time-series predictor data for the period May to August 2019. The results validated the effectiveness of the proposed N-PLS method in estimating yield loss from spectral and temporal attributes. The performance of the model was evaluated by the R2 obtained on the prediction set (0.661), and the root mean square of error (RMSE), which was 10.7%. Limitations of the approach when dealing with time-series of large-scale images which represent a source of challenges are discussed; however, the N–PLS regression seems to be a suitable choice for analysing complex multispectral imagery data with different spectral domains and with a clear temporal evolution, such as an extreme weather event.

Secondary Metabolites Produced by Xylaria necrophora Are Responsible for Foliar Symptoms Associated with Taproot Decline of Soybean

Taproot decline (TRD) of soybean ( Glycine max [L] Merr.) is an emerging disease caused by Xylaria necrophora and currently observed in the southern United States. X. necrophora infects soybean roots, causing necrosis and foliar interveinal chlorosis followed by necrosis. The most recent estimates of yield losses associated with this disease (0.57 to 1.18 million bushels) highlight its potential to become a major problem for producers in the region. The mechanism by which X. necrophora affects soybean foliage remains unknown, but a plausible explanation is that phytotoxic secondary metabolites (SMs) are produced by X. necrophora in the roots. To test this hypothesis, cell-free culture filtrates (CFCFs) from three X. necrophora strains and one putative Colletotrichum siamense isolate were used to challenge soybean stem cuttings to determine if foliar symptoms of TRD are caused by SMs, tolerance to SMs among potentially resistant soybean cultivars identified in greenhouse and field experiments, and specificity of SMs across plant species (cotton, peanut, tomato, and soybean). Measurements of chlorophyll content and root length were obtained at 7 and 14 days of exposure. Lower chlorophyll content and shorter roots were observed on all soybean cultivars treated with CFCFs of pathogenic isolates, and no effects on other plant species were observed, suggesting that X. necrophora produces SMs that are detrimental to soybean exclusively and resistance upon direct exposure to SMs does not exist. These results suggest that soybean-specific SMs are produced by X. necrophora in the roots, causing the interveinal chlorosis and subsequent necrosis observed on plants affected by TRD.

Estimation of yield loss due to chilli leaf curl disease in chilli (Capsicum annuum L.) at different stages of the crop

Estimation of yield loss due to chilli leaf curl disease in chilli (Capsicum annuum L.) at different stages of the crop

Wheat yield losses from pests and pathogens in China

Wheat is a main food source for more than 40% of the world’s population, while pests and pathogens are widely recognized as a significant obstacle to food security. Assessing the impact of pests and pathogens on yield losses is therefore critical to maintaining global food supply. However, quantitative estimation of wheat yield losses is notoriously challenging. Here, we report on an experiment-based quantitative assessment of wheat yield losses in China caused by pests and pathogens from 2000 to 2018. We found that wheat yield losses caused by pests and pathogens in six main wheat planting regions (the Yellow and Huai River valleys, the middle and lower reaches of the Yangtze River, the Southwest China, the Loess Plateau, the Northeast China and the Xinjiang province) were 16.29%, 7.46%, 11.71%, 12.64%, 6.54% and 4.84%, respectively, of the regional yield. The proportions of yield losses caused by aphids, wheat mites, scab and sharp eyespot have been on the rise, while those of underground pests have declined. Wheat powdery mildews were shown to have increased in the Xinjiang province but declined in the Northeast China. Future breeding research should focus on varieties resistant to rising group like aphids, wheat mites, scab, sharp eyespot and powdery mildews. The greatest yield loss occurred in the Yellow and Huai River valleys which was also the place with the highest wheat yield. More efforts are needed to provide management measures on wheat health management in the Yellow and Huai River valleys. Our results provide an accurate assessment of wheat yield losses in main wheat production regions of China and help devise region-specific agricultural management strategies to secure food supply to an increasingly aging population.

Improving a pest management tool for scenario analysis of economic populations of Globodera pallida

Summary Globodera pallida is the most damaging pest of potato in the UK. This work underpins enhancement of a well-established, web-based scenario analysis tool for its management by recommending additions and modifications of its required inputs and a change in the basis of yield loss estimates. The required annual decline rate of the dormant egg population is determined at the individual field sample level to help define the required rotation length by comparing the viable egg content of recovered cysts to that of newly formed cysts for the same projected area. The mean annual decline was 20.4 ± 1.4% but ranged from 4.0 to 39.7% annum−1 at the field level. Further changes were based on meta-analysis of previous field trials. Spring rainfall in the region where a field is located and cultivar tolerance influence yield loss. Tolerance has proved difficult to define for many UK potato cultivars in field trials but uncertainty can be avoided without detriment by replacing it with determinacy integers. They are already determined to support optimisation of nitrogen application rates. Multiple linear regression estimates that loss caused by pre-plant populations of up to 20 viable eggs (g soil)−1 varies from ca 0.2 to 2.0% (viable egg)−1 (g soil)−1 depending on cultivar determinacy and spring rainfall. Reliability of the outcomes from scenario analysis requires validation in field trials with population densities over which planting is advisable.

Brown and Yellow Rust of Wheat in India –Significance of Climate on It’s Races and Resistance

Wheat is one of the most important staple food crops having global economic significance. Grown globally around 215 million hectares area with production of more than 600 million tons. Wheat is constrained in its production due to several biotic factors, among them yellow rust of wheat, Puccinia striiformis Westend. f.sp. tritici Eriks and Henn. (Pst) and brown rust of wheat, Puccinia recondita f.sp. tritici (Eriks. and E. Henn.) D.M. Henderson (Ptr) continues to be a serious threat and dominant factor limiting its yield potential globally. The estimated yield losses range from 10-70%, while in a severe epidemic the grain damage can be as great as 100%. Pathogens are considered to be favoured by the cooler areas but current races are more adaptable to high temperatures causing significant yield reduction in wheat. In India, prevalent pathotypes for yellow rust include 46S119, 110S119, and 238S119. Yr5, Yr10, Yr15, YrSp, and YrSk genes are resistant to Pst pathotypes in Indian conditions, while in the case of leaf rust of wheat, prevalent pathotypes are 77-5, 77-9, and 104-2. Lr9, Lr19, Lr24, Lr25, Lr29, Lr32, Lr39, Lr45, and Lr47 are the genes having resistance to Ptr pathotypes in Indian conditions. This publication provides a comprehensive overview of the stripe and leaf rusts of wheat in India and their virulent races, types of host resistance and provides a tool for effective management of wheat rust disease.

Reductions in crop yields across China from elevated ozone

Exposure of crops to high concentrations of ozone can cause substantial reductions in yield that pose a serious threat to global food security. Here we provide comprehensive estimates of yield losses for key crops across China between 2014 and 2017 attributed to ozone using a number of new approaches. We use an air quality model at 5 km resolution and crop-specific dose-response functions developed for both concentration- and flux-based metrics. We bias correct modelled ozone concentrations and metrics using observations from more than 1000 locations. We find that on a 4-year average basis, production losses of key crops are 34–91 million metric tonnes (Mt/yr), dependent on the approach used, with highest losses in Henan province. At a national level, loss of winter wheat production derived using a China-specific dose-response function increased by 82% from 2014 to 2017, with large interannual variations in the North China Plain and in eastern China. Winter wheat losses estimated using flux-based functions, which require robust simulation of stomatal conductance and underlying vegetation physiology, are significantly lower, at 30 Mt/yr. We show that the definition of the growing season may have a greater impact on estimated losses than small biases in ozone surface concentrations. Although uncertainties remain, our findings demonstrate that increasing ozone concentrations have substantial adverse impacts on crop yields and threaten food security in China. It is important to control ozone concentrations to mitigate these negative impacts.