Maize Yield Loss Research Articles

Risk analysis of maize yield losses in mainland China at the county level

Food security in China is under additional stress due to climate change. The risk analysis of maize yield losses is crucial for sustainable agricultural production and climate change impact assessment. It is difficult to quantify this risk because of the constraints on the high-resolution data available. Moreover, the current results lack spatial comparability due to the area effect. These challenges were addressed by using long-term county-level maize yield and planting area data from 1981 to 2010. We analyzed the spatial distribution of maize yield loss risks in mainland China. A new comprehensive yield loss risk index was established by combining the reduction rate, coefficient of variation, and probability of yield reduction after removing the area effect. A total of 823 counties were divided into areas of lowest, low, moderate, high, and highest risk. High risk in maize production occurred in Heilongjiang and Jilin Provinces, the eastern part of Inner Mongolia, the eastern part of Gansu-Xinjiang, west of the Loess Plateau, and the western part of the Xinjiang Uygur Autonomous Region. Most counties in Northeast China were at high risk, while the Loess Plateau, middle and lower reaches of the Yangtze River and Gansu-Xinjiang were at low risk.

Exploring entomopathogenic fungi from South Sumatra (Indonesia) soil and their pathogenicity against a new invasive maize pest, Spodoptera frugiperda

Abstract. Herlinda S, Octariati N, Suwandi S, Hasbi. 2020. Exploring entomopathogenic fungi from South Sumatra (Indonesia) soil and their pathogenicity against a new invasive maize pest, Spodoptera frugiperda. Biodiversitas 21: 2955-2965. Fall armyworm (Spodoptera frugiperda) is a new invasive maize pest in Indonesia that can cause maize yield losses of 18 million tons/year. To overcome the pest, local-specific entomopathogenic fungi are needed. This study aimed to explore entomopathogenic fungi from soil in South Sumatra and to determine their pathogenicity against S. frugiperda larvae. The fungi exploration was carried out in the lowlands and highlands of South Sumatra and the pathogenicity of obtained isolates were tested against the third instar larvae. The entomopathogenic fungi found were Metarhizium spp. and were successfully isolated as many as 14 isolates. All of the isolates were pathogenic to S. frugiperda larvae (70.67−78.67% mortality), the most pathogenic caused 78.67% mortality and significantly suppressed the emergence of adults up to 81.2%. Unhealthy larvae had a dry, shrunken, shrinking, odorless body, and its integument was covered in mycelia and conidia like yellowish-white powdery mixed with dark green. The unhealthy pupae and adults were in the abnormal and malformation shape. The abnormal pupae were shorter in size, bent, the to-be wings got wrinkled, and darker color, while the unhealthy adults had folded wings and were unable to fly. The two most pathogenic isolates were found from the lowland (PirOI) and highland (CasPsPGA) soil of South Sumatra. In conclusion, both of these isolates had the potential to be developed into local-specific mycoinsecticides to control pest insects in the highlands and/or lowlands in Indonesia.

Farmers’ perspectives of rodent damage and rodent management in smallholder maize cropping systems of Southern Ethiopia

A survey was conducted in Chano area, Southern Ethiopia, to investigate farmers' viewpoints with regard to rodent pest problems. Farmers (n = 384) were interviewed using semi-structured questionnaire between October 2018 and January 2019. Pests were implied (51%) as the major constraints of cereal crop production followed by shifting to cash crops (20.6%), waterlogged farmlands (15.6%), infertile soils (8.6%) and insufficient rains (4.2%). Farmers experienced rodent outbreaks (83%) and identified maize (98%) as a crop most susceptible to rodent damage. Farmer suffered 23.5% average annual maize loss due to rodents. Being male (OR = 2.82, P < 0.05) and years spent in farming (OR = 1.13, P < 0.001) increased the likelihood of farmers' experience with rodent outbreaks. Seedling stage of maize was identified as the stage most susceptible to rodent damage (64.8%), followed by harvesting (19.3%) and maturity (15.9%) stages. When adjusted for other factors, a year increase in farming as an occupation decreased farmers' estimate of annual maize yield loss due to rodent damage by a coefficient of 0.04 (P < 0.05). An individual's experience (86.5%) was the major factor in deciding the type of rodent pest management. Application of rodenticides was the most frequently used (76%) rodent management method. We recommend awareness creation and extension support to the farmer community to reduce the reliance on toxic rodenticides and shift to community-based integrated rodent management approaches that would reduce the unacceptable damage levels.

Identification and Fine Mapping of qSCR4.01, a Novel Major QTL for Resistance to Puccinia polysora in Maize

Southern corn rust (SCR) is a prevalent foliar disease that can lead to severe yield losses in maize. Growing SCR-resistant varieties is the most effective way to control the disease. To identify major quantitative trait loci (QTLs) for SCR resistance, a recombinant inbred line population derived from a cross between CIMBL83 (resistant) and Lx9801 (susceptible) was analyzed. The resistance to SCR had high heritability within the population, and a major QTL on chromosome 4 (qSCR4.01), which can explain 48 to 65% of the total phenotypic variation, was consistently detected across multiple environments. Using a progeny-based fine-mapping strategy, we delimited qSCR4.01 to an interval of ∼770 kb. In contrast to other major QTLs for SCR resistance previously reported on the short arm of chromosome 10, qSCR4.01 is a novel QTL and, therefore, a desirable source of SCR resistance in maize breeding programs.

Improved plant yield efficiency alleviates the erratic optimum density in maize

AbstractPlant yield efficiency (PYE) reflects the ability of the single‐plant to respond to additional inputs and is fully expressed at the nil‐competition regime (an ultra‐low density to preclude inter‐plant interference for inputs). The purpose of this study was to determine if PYE could prevent the erratic optimum plant density–yield interaction effect in maize (Zea mays L.). Seven hybrids were evaluated across five environments at four densities, under both the normal‐input regime (NIR) and low‐input regime (LIR). Plant yield efficiency was measured at the lowest density approaching the nil‐competition regime (0.74 plants m–2), while crop (per area) yield potential was estimated at the highest density corresponding to the typical farming density in the NIR (8.89 plants m–2). In terms of optimum density, the hybrids varied extensively in the NIR (6.64–8.81 plants m–2) but performed similarly in the LIR (5.11–5.61 plants m–2). The hybrid displaying the highest PYE also had high harvest index (HI) and low anthesis to silking interval (ASI) and was proved the most stable according to various stability statistics including the genotype and genotype by environment (GGE) biplot model. In conclusion, crop yield by density interaction is a matter of hybrid. Hybrids with low PYE have inconsistent optimum density, which is a causal factor of yield loss in rainfed maize. High PYE improves hybrid flexibility and performance at low densities ultimately enhancing crop resilience to extremely fluctuating environments.

Yield and economic losses in maize caused by ambient ozone in the North China Plain (2014–2017)

Maize is the second most important crop per harvested area in the world. The North China Plain (NCP) is a highly populated and relevant agricultural region in China, experiencing some of the highest ozone (O3) concentrations worldwide. It produces ~24% of the total maize production of China in years 2014–2017. For these years, we used observational O3 data in combination with geostatistic methods to estimate county-level production and economic losses due to O3 in the NCP. AOT40 (accumulated ozone exposure over an hourly threshold of 40 ppb) values during the maize growing season (90 days before maturity) progressively increased in the four consecutive years: 13.7 ppm h, 15.4 ppm h, 16.9 ppm h and 22.7 ppm h. Mean relative yield losses were 8.2% in 2014, 9.2% in 2015, 10.4% in 2016 and 13.4% in 2017. These yield losses, derived from exposure-response functions, resulted in crop production losses of 530.3 × 104 t, 617.8 × 104 t, 713.8 × 104 t, and 953.4 × 104 t, as well as economic losses of 2343 million USD, 2672 million USD, 1887 million USD, and 2404 million USD from 2014 to 2017. The NCP is a key area in China for monitoring the effectiveness of the clean air action policies aiming at reducing emissions of air pollutants. Despite these measures, O3 concentrations have increased in NCP, and reduction of this pollutant are challenging. We suggest an increase in the number of rural air quality stations for better characterizing O3 trends in cropland areas, as well as the application of different mitigation measures. They may involve more stringent air quality regulations and changes in crops, breeding tolerant cultivars and a crop management taking into account O3 pollution.

Opportunities and Scope for Botanical Extracts and Products for the Management of Fall Armyworm (Spodoptera frugiperda) for Smallholders in Africa

Fall Armyworm (FAW) (Spodoptera frugiperda) is a polyphagous and highly destructive pest of many crops. It was recently introduced into Africa and now represents a serious threat to food security, particularly because of yield losses in maize, which is the staple food for the majority of small-scale farmers in Africa. The pest has also led to increased production costs, and threatens trade because of quarantines imposed on produce from the affected countries. There is limited specific knowledge on its management among smallholders since it is such a new pest in Africa. Some synthetic insecticides have been shown to be effective in controlling FAW, but in addition to the economic, health and environmental challenges of pesticide use insecticide resistance is highly prevalent owing to years of FAW management in the Americas. Therefore, there is a need for the development and use of alternatives for the management of FAW. These include plant-derived pesticides. Here we review the efficacy and potential of 69 plant species, which have been evaluated against FAW, and identify opportunities for use among small-scale maize farmers with a focus on how pesticidal plants might be adopted in Africa for management of FAW. The biological activities were diverse and included insecticidal, insectistatic (causing increased larval duration), larvicidal, reduced growth and acute toxicity (resulting in adverse effects within a short time after exposure). While most of these studies have been conducted on American plant taxa many South American plants are now cosmopolitan weeds so these studies are relevant to the African context.

A spatially explicit analysis of wheat and maize yield sensitivity to changing groundwater levels in Hungary, 1961–2010

Groundwater (GW) in many regions is essential for agricultural productivity, especially during drought periods. The shrinking of GW is an important but rarely documented component of the recent global environmental crisis and may threaten food security. The problem cannot be put in proper perspective, because we rarely have datasets long and detailed enough to scrutinise the unfolding effects at regional scales. To address this knowledge gap, we used a 50-y long (1961–2010) and spatially extensive (283 GW wells) dataset from Hungary to examine the GW trends and the sensitivity of the yields of two important crops to GW fluctuations. During 1986–2010, GW levels were significantly (0.21–0.60 m) lower than during 1961–1985 in every region of Hungary and every month of the year. The decrease was 2.24 cm y−1 at the country level. Linear and bootstrap resampling tests indicated weak relationship between GW levels and wheat yields but decreasing GW levels accounted for 18–38% of maize yield variability during the ‘climate change affected’ period of 1986–2010. Calculating the impact of GW on potential food production, a 100 mm higher GW levels would have increased annual maize yields by 0.23 t ha−1 on the Hungarian Plain. However, the registered GW decrease caused an estimated maize yield loss of 0.65 t ha−1, i.e. 11.6% of the average annual yield during 1986–2010. GW level fluctuations on the plain showed a significant correlation with August–October soil moisture gridded data over much of the agricultural landscapes of Central and Western Europe, indicating a similar situation in a wider European context. To mitigate the cumulative negative impact of GW decrease and the rising temperature, GW recharge via infiltration of retained water would be an adequate solution. Areas of former floodplains with low agroecological suitability, amounting to almost a quarter of the Hungarian Plain could serve as such water retention areas.

Assessment of biomass and yield loss of maize caused by aerosols in heavily polluted agricultural areas of China based on APSIM model

In recent years, with the rapid economic growth, the government and the public pay more and more attention to the environmental effects caused by aerosols. In this study, the effects of aerosols on the biomass and yield of maize from 2001 to 2014 in heavily polluted agricultural areas of China were explored using global AErosol Robotic Network (AERONET) monitoring data, the Second Simulation of a Satellite Signal in the Solar Spectrum radiative transfer (6S) model, and the Agricultural Production Systems sIMulator (APSIM) crop growth model. Beijing, Xianghe, and Taihu stations were selected as research areas. The results showed that the APSIM-maize model was able to accurately simulate the interactions between maize and the climatic constraints in the maize planting areas at Beijing, Xianghe, and Taihu stations. Our results revealed that the aerosols reduced direct solar radiation, and that the decreasing trend was mainly due to the net radiation flux caused by aerosols. The average total radiation from 2001 to 2014 at Beijing, Xianghe, and Taihu stations decreased by 31.95%, 14.74%, and 28.30%, respectively, and the average maize biomass decreased by 34.12%, 20.78%, and 28.41%, respectively. As a result, the average maize yield at Beijing, Xianghe, and Taihu stations declined by 28.44%, 13.43%, and 14.89%, respectively. Our findings, particularly the understanding of the effect of aerosols on crop production, will have important implications for improving climate change impact studies and helping local agricultural production to cope with ongoing climate change. They could also benefit strategic decision-making related to future agricultural adaptation methods in China.

Polymer-coated urea effects on maize yield and nitrogen losses for hilly land of southern China

The rational nitrogen (N) application rate for crops depends not only on yield but also on the environmental cost of N loss to the surrounding ecological environment. To explore the environmental and economic optimal N rate (EEONR) for dryland maize in the hilly areas of southern China, a field experiment was conducted with spring maize from 2015 to 2017. Common urea (CU, control, 240 kg N ha−1) and four polymer-coated urea (PCU) fertilization levels (100PCU, 90PCU, 80PCU, 70PCU, which respectively denotes 0, 10%, 20% and 30% reduction of PCU–N application based on the control) were employed in this trial. Maize yield, N loss and economic return were investigated over 3 years. The results were as follows: (1) relative to CU, a 0–20% reduction in the PCU-N application rate did not significantly affect the maize yield during the three consecutive years, however, a 30% reduction in the PCU-N application rate led to significant yield loss in the third year despite the consistent yields achieved in the first 2 years. (2) PCU application significantly abated N loss to the environment, and as N application rate decreased, N loss significantly reduced. Our results showed that a 0–30% reduction in the PCU-N application rate mitigated N loss by 12.8–46.1% via N2O, NH3, runoff and leaching, and the two main N-loss pathways were leaching (55.2–62.2%) and NH3 volatilization (29.8–36.0%). (3) A 0–30% reduction in the PCU-N application rate resulted in a deficit, ranging from 784 to 2438 CNY ha−1 for increased earnings over CU because of the high purchase price of PCU. The net economic benefit was calculated from the N input cost, yield economic income and environment cost of N lost in the treatments with 0, 10%, 20% and 30% reduction of PCU-N and were − 1820 to 14,479, 402 to 14,612, 2306 to 14,613, and 3941 to 14,205 CNY ha−1, respectively, and the net economic benefit of the CU plot was − 4003 to 14,671 CNY ha−1. In summary, our findings suggest that reducing the PCU-N application rate by 20% is a reasonable EEONR for spring maize cultivation in hilly areas of southern China.

Selection and molecular characterization of Bacillus thuringiensis strains efficient against soybean looper (Chrysodeixis includens) and Spodoptera species

ABSTRACT Soybean looper (Chrysodeixis includens) and Spodoptera group are important defoliators insects responsible for significant yield losses in soybean, cotton and maize in Brazil. Bioinsecticides and transgenic plants expressing insecticidal proteins from Bacillus thuringiensis are among the most used sustainable control methods for pest control in agriculture, especially for several lepidopteran species. To provide new components for insect control, this study aimed to select and characterize B. thuringiensis strains toxic to C. includens, S. cosmioides, S. eridania, and S. frugiperda. We performed initial bioassays with fifty B. thuringiensis strains for C. includens and selected four strains – 1608A, 726, 773, and 775E – that caused high larval mortality (100%) to be tested against Spodoptera species. These strains harbored cry insecticidal genes, megaplasmids, absence of β-exotoxin and showed two major proteins about 65 and 130 kDa in SDS-page attributed to Cry protein classes toxic to lepidopteran species. The 1608A and 775E strains also showed high toxicity to Spodoptera species that demonstrate great potential for B. thuringiensis-based bioproduct development and as sources of new insecticidal genes for transgenic crops for multiple pest control relevant in the Brazilian agricultural system.

Proteomic Changes during MCMV Infection Revealed by iTRAQ Quantitative Proteomic Analysis in Maize.

Maize chlorotic mottle virus (MCMV) has been occurring frequently worldwide and causes severe yield losses in maize (Zea mays). To better investigate the destructive effects of MCMV infection on maize plants, isobaric tagging for relative and absolute quantitation (iTRAQ)-based comparative proteomic analysis was performed on MCMV infected maize cv. B73. A total of 972 differentially abundant proteins (DAPs), including 661 proteins with increased abundance and 311 proteins with reduced abundance, were identified in response to MCMV infection. Functional annotations of DAPs and measurement of photosynthetic activity revealed that photosynthesis was decreased, while the abundance of ribosomal proteins, proteins related to stress responses, oxidation-reduction and redox homeostasis was altered significantly during MCMV infection. Two DAPs, disulfide isomerases like protein ZmPDIL-1 and peroxiredoxin family protein ZmPrx5, were further analyzed for their roles during MCMV infection through cucumber mosaic virus-based virus-induced gene silencing (CMV-VIGS). The accumulation of MCMV was suppressed in ZmPDIL-1-silenced or ZmPrx5-silenced B73 maize, suggesting ZmPDIL-1 and ZmPrx5 might enhance host susceptibility to MCMV infection.

Automated Fall Armyworm (Spodoptera frugiperda, J.E. Smith) Pheromone Trap Based on Machine Learning

Maize is the main food crop that meets the nutritional needs of both humans and livestock in the sub-Saharan African region. Maize crop has in the recent past been threatened by the fall armyworm (Spodoptera frugiperda, J.E Smith) which has caused considerable maize yield losses in the region. Controlling this pest requires knowledge on the time, location and extent of infestation. In addition, the insect pest’s abundance and environmental conditions should be predicted as early as possible for integrated pest management to be effective. Consequently, a fall armyworm pheromone trap was deployed as a monitoring tool in the present study. The trap inspection is currently carried out manually every week. The purpose of this paper is to bring automation to the trap. We modify the trap and integrate Internet of Things technologies which include a Raspberry Pi 3 Model B+ micro-computer, Atmel 8-bit AVR microcontroller, 3G cellular modem and various sensors powered with an off-grid solar photovoltaic system to capture real-time fall armyworm moth images, environmental conditions and provide real-time indications of the pest occurrences. The environmental conditions include Geographical Positioning System coordinates, temperature, humidity, wind speed and direction. The captured images together with environmental conditions are uploaded to the cloud server where the image is classified instantly using Google’s pre-trained InceptionV3 Machine Learning model. Intended users view captured data including prediction accuracy via a web application. Once this smart technology is adopted, the labour-intensive task of monitoring will reduce while stakeholders shall be provided with a near real-time insight into the FAW situation in the field therefore enabling pro-activeness in their management of such a devastating pest.

Maize yield and nitrate loss prediction with machine learning algorithms

Pre-growing season prediction of crop production outcomes such as grain yields and nitrogen (N) losses can provide insights to farmers and agronomists to make decisions. Simulation crop models can assist in scenario planning, but their use is limited because of data requirements and long runtimes. Thus, there is a need for more computationally expedient approaches to scale up predictions. We evaluated the potential of four machine learning (ML) algorithms (LASSO Regression, Ridge Regression, random forests, Extreme Gradient Boosting, and their ensembles) as meta-models for a cropping systems simulator (APSIM) to inform future decision support tool development. We asked: (1) How well do ML meta-models predict maize yield and N losses using pre-season information? (2) How many data are needed to train ML algorithms to achieve acceptable predictions? (3) Which input data variables are most important for accurate prediction? And (4) do ensembles of ML meta-models improve prediction? The simulated dataset included more than three million data including genotype, environment and management scenarios. XGBoost was the most accurate ML model in predicting yields with a relative mean square error (RRMSE) of 13.5%, and Random forests most accurately predicted N loss at planting time, with a RRMSE of 54%. ML meta-models reasonably reproduced simulated maize yields using the information available at planting, but not N loss. They also differed in their sensitivities to the size of the training dataset. Across all ML models, yield prediction error decreased by 10%–40% as the training dataset increased from 0.5 to 1.8 million data points, whereas N loss prediction error showed no consistent pattern. ML models also differed in their sensitivities to input variables (weather, soil properties, management, initial conditions), thus depending on the data availability researchers may use a different ML model. Modest prediction improvements resulted from ML ensembles. These results can help accelerate progress in coupling simulation models and ML toward developing dynamic decision support tools for pre-season management.

Male Sterility in Maize after Transient Heat Stress during the Tetrad Stage of Pollen Development.

Shifts in the duration and intensity of ambient temperature impair plant development and reproduction, particularly male gametogenesis. Stress exposure causes meiotic defects or premature spore abortion in male reproductive organs, leading to male sterility. However, little is known about the mechanisms underlying stress and male sterility. To elucidate these mechanisms, we imposed a moderate transient heat stress on maize (Zea mays) plants at the tetrad stage of pollen development. After completion of pollen development at optimal conditions, stress responses were assessed in mature pollen. Transient heat stress resulted in reduced starch content, decreased enzymatic activity, and reduced pollen germination, resulting in sterility. A transcriptomic comparison pointed toward misregulation of starch, lipid, and energy biosynthesis-related genes. Metabolomic studies showed an increase of Suc and its monosaccharide components, as well as a reduction in pyruvate. Lipidomic analysis showed increased levels of unsaturated fatty acids and decreased levels of saturated fatty acids. In contrast, the majority of genes involved in developmental processes such as those required for auxin and unfolded protein responses, signaling, and cell wall biosynthesis remained unaltered. It is noteworthy that changes in the regulation of transcriptional and metabolic pathway genes, as well as heat stress proteins, remained altered even though pollen could recover during further development at optimal conditions. In conclusion, our findings demonstrate that a short moderate heat stress during the highly susceptible tetrad stage strongly affects basic metabolic pathways and thus generates germination-defective pollen, ultimately leading to severe yield losses in maize.

Do parasitoids reduce cereal losses? Estimating the impact of parasitoids on stem borer pest infestation and maize yield

Chilo partellus (spotted stem borer) is an economically important stem borer pest in Eastern Africa causing high yield losses in maize and sorghum. The larval endoparasitoid, Cotesia flavipes (parasitic wasp) was released in Kenya to manage C. partellus and post release studies showed it had established and stem borer parasitism was steadily increasing. Despite the rise in parasitism, doubts on whether parasitoids can effectively reduce stem borer populations have been raised.Objective: This study was carried out to estimate the impact of C. flavipes on stem borer infestation and the resultant effect on maize yield in Kenya. Methodology and results: Using insecticidal check method, selective insecticides were used to exclude stem borer pests and natural enemies in Treatments A and B respectively with controls designated as Treatment C. Results revealed significant differences in stem borer infestation (F2,9=5.835; p<0.05) and parasitism (F2,9 =91.97; p<0.0001) among the three treatments. Significantly higher infestation was recorded in treatment B (2.0±0.2%) compared to A (0.5±0.3%) and C (1.5±0.4%). Parasitism was significantly higher in treatment C (23.5±6.8%) compared to A (0.0±0.0%) and B (0.3±0.1%). However, there was no significant difference in yield among treatments showing that parasitoid action did not translate into changes in yield. Conclusions and application of findings: The parasitoid C. flavipes has made an important contribution towards suppressing stem borer population. This was shown by high infestation recorded in treatment B which was as a result of partial elimination of parasitoids. This deduction was further supported by the results which showed that pest exclusion using chemicals did not have a significant difference from parasitoid action as shown by insignificant difference in infestation between treatment A and C fields. Percentage infestation and parasitism results obtained from this study thus provide quantitative data on the impact of C. flavipes. Release of C. flavipes can therefore be done in other areas both within and beyond the country’s borders where C. partellus is still a problem. However, since reduced infestation and increased parasitism did not translate into yield increase, more suppressive effect may be achieved if the pest’s multiple developmental stages are targeted, most especially before it reaches the destructive larval stage. There is need to carry out further research on C. partellus’ egg parasitoids. Optimum yield may then be realized.Key words: Classical biological control; Chilo partellus ; Cotesia flavipes; parasitism; insecticidal check technique; Kenya

Farmer perception of fall armyworm (Spodoptera frugiderda J.E. Smith) and farm-level management practices in Zambia.

BACKGROUNDThis paper documents farmer perceptions and management practices for fall armyworm (Spodoptera frugiderda J.E. Smith), providing a baseline for the development of sustainable pest management strategies.RESULTS91% of farmers correctly identified fall armyworm, and reported it as the most important maize pest during 2016/2017 cropping season, affecting nearly half of cultivated area. Estimated maize yield loss during the season, attributed to fall armyworm was 28%. A majority of farmers (60%) used pesticides for fall armyworm control, along with other cultural/physical practices – hand picking and crushing egg masses/caterpillars (36%), and application of ash/sand in the funnel (19%). Farmers used various pesticide active ingredients, and protective measures were inadequate; >50% of farmers did not use any protective measures while spraying. Significantly more male than female farmers used pesticides (P = 0.05), and the reverse was true for cultural practices. Significant maize yield differences (P = 0.001) were observed by gender, attributed to differences in utilization of production inputs/practices. At least 77% of farmers received and shared agricultural advice, which can be optimized to spread information on fall armyworm management options.CONCLUSIONIncreased use of pesticides to manage fall armyworm poses health and environmental risks, besides the high cost for farmers and governments. Research into cultural and indigenous practices used by farmers will offer opportunities for alternative and sustainable management practices. Research efforts should pay attention to gender differences in access to resources and inputs. Tackling fall armyworm at the farm level, and averting yield losses will require integrated messaging addressing other production risks. © 2019 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Narrow‐wide‐row planting pattern increases the radiation use efficiency and seed yield of intercrop species in relay‐intercropping system

AbstractPlanting arrangements affect radiation use efficiency (RUE) and competitiveness of intercrop species in intercropping systems. Here, we reveal that narrow‐wide‐row planting arrangement in maize‐soybean relay‐intercropping system increases the dry matter and competitiveness of soybean, increased the RUE of maize and soybean, and compensates the yield loss of maize by substantially increasing the yield of soybean. In this field study, maize was planted with soybean in different planting arrangements (P1, 20:180, P2, 40:160; P3, 60:140, and P4, 80:120) of relay intercropping, all the relay‐intercropping treatments were compared with sole crops of maize (SM) and soybean (SS). Results showed that P1 improved the total RUE 3.26 g/MJ (maize RUE + soybean RUE) of maize and soybean in relay‐intercropping system. Compared to P4, treatment P1 increased the soybean competition ratio (CR) values (by 55%) but reduced the maize CR values (by 29%), which in turn significantly improved the yield of soybean by maintaining the maize yield. Generally, in P1, soybean produced 82% of SS yield, and maize produced 88% of SM yield, and it achieved the land equivalent ratio of 1.7. These results suggest that by maintaining the appropriate planting distances between maize and soybean we can improve the competitiveness and yield of intercrop species in relay‐intercropping system.

Excessive rainfall leads to maize yield loss of a comparable magnitude to extreme drought in the United States.

Increasing drought and extreme rainfall are major threats to maize production in the United States. However, compared to drought impact, the impact of excessive rainfall on crop yield remains unresolved. Here, we present observational evidence from crop yield and insurance data that excessive rainfall can reduce maize yield up to −34% (−17 ± 3% on average) in the United States relative to the expected yield from the long‐term trend, comparable to the up to −37% loss by extreme drought (−32 ± 2% on average) from 1981 to 2016. Drought consistently decreases maize yield due to water deficiency and concurrent heat, with greater yield loss for rainfed maize in wetter areas. Excessive rainfall can have either negative or positive impact on crop yield, and its sign varies regionally. Excessive rainfall decreases maize yield significantly in cooler areas in conjunction with poorly drained soils, and such yield loss gets exacerbated under the condition of high preseason soil water storage. Current process‐based crop models cannot capture the yield loss from excessive rainfall and overestimate yield under wet conditions. Our results highlight the need for improved understanding and modeling of the excessive rainfall impact on crop yield.

Inheritance of Striga hermonthica adaptive traits in an early‐maturing white maize inbred line containing resistance genes from Zea diploperennis

AbstractStriga hermonthica can cause as high as 100% yield loss in maize depending on soil fertility level, type of genotype, severity of infestation and climatic conditions. Understanding the mode of inheritance of Striga resistance in maize is crucial for introgression of resistance genes into tropical germplasm and deployment of resistant varieties. This study examined the mode of inheritance of resistance to Striga in early‐maturing inbred line, TZdEI 352 containing resistance genes from Zea diploperennis. Six generations, P1, P2, F1, F2, BC1P1 and BC1P2 derived from a cross between resistant line, TZdEI 352 and susceptible line, TZdEI 425 were screened under artificial Striga infestation at Mokwa and Abuja, Nigeria, 2015. Additive‐dominance model was adequate in describing observed variations in the number of emerged Striga plants among the population; hence, digenic epistatic model was adopted for Striga damage. Dominance effects were higher than the additive effects for the number of emerged Striga plants at both locations signifying that non‐additive gene action conditioned inheritance of Striga resistance. Inbred TZdEI 352 could serve as invaluable parent for hybrid development in Striga endemic agro‐ecologies of sub‐Saharan Africa.