Independent Field Experiments Research Articles

The importance of model structure and soil data detail on the simulations of crop growth and water use: A case study for sugarcane

Process-based crop models have faced rapid development over the last years, and many modelling platforms are now available and can be used in a wide range of conditions. Whilst the selection of a model should be suited to the purpose of its application, very few studies focused on the impact of choosing different model structures and data details on the simulation outputs. One important aspect is the soil water dynamics, which can be simulated at different levels of details in terms of data and approaches. In this study, we investigated the impact of model structure and data detail on simulations of sugarcane growth and irrigation scheduling. Three different soil water routines (Standalone, Tipping-Bucket, SWAP) were coupled with the SAMUCA model and calibrated with a comprehensive field experiment dataset. We also tested the influence of using simplified homogeneous (SL) and detailed (DL) soil profile information in model performance. The model framework was evaluated against independent field experiments across Brazil and used to simulate long-term sugarcane growth and irrigation scheduling. After calibration, the SWAP-DL showed the highest accuracy in soil moisture predictions, with a 6 % error (RRMSE), but the difference from TippingBucket-DL was small (8 %). While the performance of stalk dry mass, LAI and water-use efficiency simulations were within the range found in literature, comprehensive field experiments showing significant impacts of drought on sugarcane growth are still lacking for a more rigorous evaluation. Both SWAP and tipping-bucket approaches showed higher robustness to soil data detail as compared to the Standalone method, which should be avoided when soil water is critical for sugarcane growth. The use of tipping-bucket method may still be preferred when the research goal is focused on crop growth and soil parameters are limited. SWAP-SAMUCA may provide an extended ability to represent agrohydrological processes in sugarcane plantations and process understanding.

Optimizing Grain Zinc Biofortification in Bread Wheat: Innovative Fertilization Strategies for Field Conditions

Zinc deficiency in humans is of worldwide concern. The aim of this study is to enrich grains with Zn through soil application at different doses and foliar application from various sources. For this purpose, two independent field experiments have been conducted. In Experiment I, Zn (ZnSO4.7H2O) was applied through soil as basal and top dressing. The treatments were Zn0: control, Zn1: 5 kg Zn ha−1 as basal, Zn2: 2.5 kg Zn ha−1 as basal and 2.5 kg Zn ha−1 as top dressing and Zn3: 5 kg Zn ha−1 as top dressing. In Experiment II, Zn was applied as foliar from different sources (ZnSO4.7H2O, Zn-Methionine, Zn-Polyol and Zn-EDTA) at different growth stages with or without urea. In both experiments, Zn concentration in the grain and leaves of wheat and grain yield increased while phytic acid and PA/Zn molar ratio decreased due to soil or foliar Zn application. It was determined that the application of ZnSO4.7H2O in the soil at the top dressing period in Experiment I and the application of ZnSO4.7H2O and Zn-Methionine forms together with urea in Experiment II were effective methods in increasing grain yield and grain Zn concentration. The application of ZnSO4.7H2O from both soil and foliar sources, especially in combination with urea, has proven to be highly effective in the Zn biofortification of wheat grains. It is possible to assert that the use of ZnSO4.7H2O, which is cost-effective compared to other sources, could contribute significantly to enhancing zinc nutrition in humans.

Nitrogen fertilizer source, rate, placement, and application timing effect on sorghum (grain and forage) and corn grain yields

AbstractIdentifying the limiting nutrient, fertilizer source, rate, placement, additives, and timing of application are critical components of fertilizer management. The objective of this study was to quantify the impact of nitrogen (N) fertilizer source, rate, placement method, additives, application timing, and environment on yields of grain sorghum, forage sorghum [Sorghum bicolor (L.) Moench], and corn (for grain, Zea mays L.). Independent field experiments were conducted at 13 different environments in Kansas from 2008 through 2013 on grain sorghum, forage sorghum, and corn. Treatments were an incomplete factorial combination of four fertilizer placement methods, three fertilizer types, five fertilizer additives, three fertilizer application times, and six fertilizer rates that varied by location and across years. Results showed grain and forage sorghum yields responded to N fertilizer in environments that were not extremely dry (<136 mm) or wet (>651 mm). Corn responded to N fertilizer application only in high‐precipitation environments. For grain sorghum, where rate × placement × source × additive interaction was significant, broadcast application of urea (source) at high rates (67–134 kg N ha−1), with summer application timing, or with additive in winter (with environmentally smart nitrogen [ESN]) resulted in up to 43% greater yield compared with application of urea‐ammonium nitrate (UAN; source) and surface band (placement) at 67 kg ha−1 without additives. In the one site‐year where forage sorghum responded to fertilizer application, forage yields with preplant application of UAN at 56–140 kg ha−1 were 164% greater than the control. For corn, application of either urea or UAN fertilizer, UAN in coulter or surface band, with ESN blend, applied at planting, and at highest rates (160 kg ha−1) resulted in best yields compared with the alternatives and 110% greater yield compared with the unfertilized control. We concluded that fertilizer rate is an important management component as it consistently affected yield regardless of crop considered. Fertilizer placement and timing have crop‐specific importance as they were significant for only corn, but the main effect of additives (N stabilizers) was not significant for any of the crops. Environment and crop type influenced crop response to N fertilizer rate, timing, placement, and additives.

A global dataset of biochar application effects on crop yield, soil properties, and greenhouse gas emissions

Biochar application is widely studied to mitigate the threats of soil degradation to food security and climate change. However, there are big variations in the effects of biochar application on crops, soils, and the atmosphere during crop production. This study provides a global dataset of biochar application effects on crop yield, soil properties, and greenhouse emissions. The dataset is extracted and integrated from 367 peer-reviewed studies with 891 independent field, laboratory, and incubation experiments across 37 countries. This dataset includes 21 variables before and after biochar application (including soil properties, crop yield, greenhouse gas emissions, etc.) of 2438 items, focusing on two main biochar application types: biochar application alone and combined with fertilizers. Background information on climate conditions, initial soil properties, management practices, and characteristics of biochar sources and production is also contained in the dataset. This dataset facilitates a comprehensive understanding of the impact of biochar application, supports the utilization of agricultural wastes for biochar production, and assists researchers in refining experimental protocols for further studies.

Erwinia amylovora Type III Secretion System Inhibitors Reduce Fire Blight Infection Under Field Conditions.

Fire blight, caused by Erwinia amylovora, is an economically important disease in apples and pears worldwide. This pathogen relies on the type III secretion system (T3SS) to cause disease. Compounds that inhibit the function of the T3SS (T3SS inhibitors) have emerged as alternative strategies for bacterial plant disease management, as they block bacterial virulence without affecting growth, unlike traditional antibiotics. In this study, we investigated the mode of action of a T3SS inhibitor named TS108, a plant phenolic acid derivative, in E. amylovora. We showed that adding TS108 to an in vitro culture of E. amylovora repressed the expression of several T3SS regulon genes, including the master regulator gene hrpL. Further studies demonstrated that TS108 negatively regulates CsrB, a global regulatory small RNA, at the posttranscriptional level, resulting in a repression of hrpS, which encodes a key activator of hrpL. Additionally, TS108 has no impact on the expression of T3SS in Dickeya dadantii or Pseudomonas aeruginosa, suggesting that its inhibition of the E. amylovora T3SS is likely species specific. To better evaluate the performance of T3SS inhibitors in fire blight management, we conducted five independent field experiments in four states (Michigan, New York, Oregon, and Connecticut) from 2015 to 2022 and observed reductions in blossom blight incidence as high as 96.7% compared with untreated trees. In summary, the T3SS inhibitors exhibited good efficacy against fire blight.

A hydrothermal model to predict Russian thistle (Salsola tragus) seedling emergence in the dryland of the Pacific Northwest (USA)

AbstractRussian thistle (Salsola tragus L.) is among the most troublesome weeds in cropland and ruderal semiarid areas of the Pacific Northwest (PNW). Predicting S. tragus emergence timing plays a critical role in scheduling weed management measures. The objective of this research was to develop and validate a predictive model of the seedling emergence pattern of S. tragus under field conditions in the PNW to increase the efficacy of control measures targeting this species. The relationship between cumulative seedling emergence and cumulative hydrothermal time under field conditions was modeled using the Weibull function. This model is the first to use hydrothermal time units (HTT) to predict S. tragus emergence and showed a very good fit to the experimental data. According to this model, seedling emergence starts at 5 HTT, and 50% and 90% emergence is completed at 56 HTT and 177 HTT, respectively. For model validation, independent field experiments were carried out. Cumulative seedling emergence was accurately predicted by the model, supporting the idea that this model is robust enough to be used as a predictive tool for S. tragus seedling emergence. Our model can serve as the basis for the development of decision support systems, helping farmers make the best decisions to control S. tragus populations in no-till fallow and spring wheat systems.

A machine learning modeling framework for Triticum turgidum subsp. durum Desf. yield forecasting in Italy

AbstractThe forecasting of crop yield is one of the most critical research areas in crop science, which allows for the development of decision support systems, optimization of nitrogen fertilization, and food safety. Many tested modeling approaches can be differentiated according to the models and data used. The models used are traditional crop models that require data that are often difficult to measure. New modeling approaches based on artificial intelligence algorithms have proven to be of high performance, flexible, and can be tested based on available data. In this study, four independent field experiments conducted on Triticum turgidum subsp. durum Desf. in central–southern Italy were used to train a set of machine learning (ML) algorithms to predict the yield using 16 variables: fertilization, nitrogen management, pedoclimatic, and remote sensing data. Four ML algorithms were calibrated and validated over two independent sites, and a linear regression model was used as a control. The calibrated models can predict the grain yield in the two regions by using ancillary data, topsoil physical and chemical properties, multispectral drone imagery, climatic data, and nitrogen fertilizer applied at the site. Among the four ML algorithms, stochastic gradient boosting (root‐mean‐square error = 0.58 t ha−1) outperformed others during calibration and transferability. Nitrogen application rate, seasonal precipitation, and temperature are the most important features for predicting wheat yield.

Soil organic carbon regulates CH4 production through methanogenic evenness and available phosphorus under different straw managements

Methane (CH4) is the main greenhouse gas emitted from rice paddy fields driven by methanogens, for which methanogenic abundance on CH4 production has been intensively investigated. However, information is limited about the relationship between methanogenic diversity (e.g., richness and evenness) and CH4 production. Three independent field experiments with different straw managements including returning method, burial depth, and burial amount were used to identify the effects of methanogenic diversity on CH4 production, and its regulating factors from soil properties in a rice–wheat cropping system. The results showed that methanogenic evenness (dominance) can explain 23% of variations in CH4 production potential. CH4 production potential was positively related to methanogenic evenness (R2 = 0.310, p < 0.001), which is driven by soil organic carbon (SOC), available phosphorus (AP), and nitrate (NO3−) through structure equation model (SEM). These findings indicate that methanogenic evenness has a critical role in evaluating the responses of CH4 production to agricultural practices following changes in soil properties. The SEM also revealed that SOC concentration influenced CH4 production potential indirectly via complementarity of methanogenic evenness (dominance) and available phosphorus (AP). Increasing SOC accumulation improved AP release and stimulated CH4 production when SOC was at a low level, whereas decreased evenness and suppressed CH4 production when SOC was at a high level. A nonlinear relationship was detected between SOC and CH4 production potential, and CH4 production potential decreased when SOC was ≥14.16 g kg−1. Our results indicated that the higher SOC sequestration can not only mitigate CO2 emissions directly but CH4 emissions indirectly, highlighting the importance to enhance SOC sequestration using optimum agricultural practices in a rice–wheat cropping system.

An exotic plant successfully invaded as a passenger driven by light availability.

Invasive exotic plant species (IEPs) are widely distributed across the globe, but whether IEPs are drivers or passengers of habitat change in the invaded spaces remains unclear. Here, we carried out a vegetation and soil survey in 2018 and two independent field experiments (Pedicularis kansuensis removal in 2014 and 2015, and fertilization experiment since 2012) and found that the invasive annual P. kansuensis was at a disadvantage in light competition compared with perennial native grasses, but the successful invasion of P. kansuensis was due to the sufficient light resources provided by the reduced coverage of the native species. Conversely, nitrogen enrichment can effectively inhibit P. kansuensis invasion by increasing the photocompetitive advantage of the native species. sP. kansuensis invasion did not reduce species richness, but did increase plant community coverage, productivity and soil nutrients. Furthermore, the removal of P. kansuensis had little effect on the plant community structure and soil properties. Our results suggest that the passenger model perfectly explains the benign invasive mechanism of P. kansuensis. The invasion "ticket" of P. kansuensis is a spare ecological niche for light resources released by overgrazing.

Effects of age and pasture type on the concentration and prevalence of tetracycline and macrolide resistant Enterococcus species in beef cow-calf production system

Enterococci are a normal flora of the gastrointestinal tracts of humans and animals. Enterococci can also cause life-threatening nosocomial infections. Antimicrobial-resistant Enterococcus species have been reported in the feedlot and dairy cattle productions and in meat and milk products, suggesting their foodborne importance. Cow-calf operations represent a significant segment in the beef production system by producing weaned calves. Weaned calves are brought into the feedlot to be finished for meat, and culled cows are also slaughtered for beef, primarily for ground beef products. Infection dynamics in the cow-calf operation can contribute to meat contamination. This study evaluated the effects of age and wheat grazing on the concentration and prevalence of a macrolide antibiotic erythromycin (ERYr) and tetracycline (TETr) resistant enterococci, associated resistance genes and species distribution in a cow-calf production system. In 2017 and 2018, 32 Angus breed cow-calf pairs were randomly assigned to feed on tall fescue or wheat pasture in two independent field experiments. During the grazing experiments of 2-3 weeks, fecal samples were collected weekly and cultured to enumerate, isolate and identify ERYr, TETr, and generic enterococci, using media supplemented with erythromycin, tetracycline or non-supplemented media, respectively. The two main species frequently associated with human illnesses, Enterococcus faecium and E. faecalis, were widely distributed in the cow-calf groups. Generic and TETr- enterococci were prevalent (96-100% prevalence) and abundant (3.2-4.9 log10 CFU/g) in the cow-calf population; however, ERYr enterococci were enumerable by direct plating only from a single cow despite being detected in at least 40% of the fecal samples after enrichment, showing their low abundance. TET- and ERY-resistance were mainly conferred by tet(M) and erm(B), respectively. Wheat grazing reduced the concentration of TETr enterococci and modified enterococcal species and resistance gene distributions. Hence, it is necessary to further investigate wheat grazing in cow-calf production as a potential strategy to mitigate antimicrobial resistance.

Fire blight resistance, irrigation and conducive wet weather improve Erwinia amylovora winter survival in cankers.

Erwinia amylovora causes fire blight, a disease responsible for enormous economic losses in the pome fruit-producing areas where it is present. Despite the abundant research on fire blight, information about E. amylovora population dynamics and survival in fire blight cankers and the plant defense responses to this pathogen in the infected bark are limited. In our study, we obtained fire blight cankers in apple, pear, and Asian pear cultivars showing differing resistance to the disease by shoot inoculation with E. amylovora. We collected cankers from irrigated and non-irrigated trees every 3 months in two independent field experiments and analyzed samples by viability digital PCR. We also assessed the expression of pathogenicity-related (PR) genes in the bark of selected apple and Asian pear cultivars. A logistic regression analysis revealed the impact of environmental and host factors on E. amylovora detection rates in cankers. The chances of detecting live E. amylovora cells in cankers increased significantly in those collected from irrigated trees, in July, and/or during an experiment performed in a year with an expected average rainfall when compared to samples from non-irrigated trees, collected in January, and/or during an experiment performed under environmental conditions dominated by drought. We found a positive correlation between the pathogen detection rates in cankers and the host resistance to fire blight that might be explained by lower E. amylovora survival rates in more damaged tissues of susceptible hosts. The genes PR-1, PR-2, PR-5, and PR-8 were induced in the bark surrounding apple and Asian pear fire blight cankers. Our study, involving the analysis of more than 800 canker samples, provides new knowledge about the fire blight disease cycle and lays the foundation for improved fire blight management and eradication strategies in pome fruit orchards.

Seed Treatment with Diamide and Neonicotinoid Mixtures for Controlling Fall Armyworm on Corn: Toxicity Evaluation, Effects on Plant Growth and Residuality.

The diamides, chlorantraniliprole (CHL) and cyantraniliprole (CYA), have been used as seed treatment agents against the fall armyworm (FAW), Spodoptera frugiperda in China. However, large-scale application of these two insecticides is prohibited because of their high cost. The neonicotinoid insecticides, clothianidin (CLO) and thiamethoxam (THI), are cheaper and widely used. In this study, we tested the efficacy of CHL + CLO and CYA + THI as seed treatment agents against FAW larvae both in laboratory and field conditions. Laboratory experiments showed that the two binary mixtures (both 240 g.a.i.100 kg−1 corn seeds) caused FAW mortality exceeded 84.00% at 14 days after seedling emergence (DAE). The mortality of the binary mixtures were similar to either CHL (300 g.a.i.100 kg−1corn seeds) or CYA (144 g a.i.100 kg−1corn seeds), but higher than CLO (120 g.a.i.100 Kg−1corn seeds) or THI (180 g a.i.100 kg−1corn seeds). Two independent field experiments showed that both binary mixtures resulted in above 68.00% control efficacy at 14 DAE, suggesting that these insecticidal combinations could effectively control FAW over a relative long period. In addition, both binary mixtures showed no negative effects on the growth and development of corn seedlings. The residues of binary mixtures in corn leave were also lower at 28 DAE as compared to residues in CHL or CYA alone. Most importantly, the costs of CHL + CLO were reduced up to 50% and CYA + THI up to 20% when compared to singly used chemical. Totally, our results indicated that CHL + CLO and CYA + THI had the same control efficacy as CHL or CYA alone, but with much lower cost.

Evaluation of LiDAR-Derived Snow Depth Estimates From the iPhone 12 Pro

Snow is a critical contributor to the global water-energy budget with impacts on springtime flooding and water resource management practices. Laser altimetry [light detection and ranging (LiDAR)] is a remote-sensing technique that has demonstrated skill in monitoring snow depth, but the expense of purchasing and transporting traditional LiDAR equipment limits their operational use. In this work, we demonstrate that the LiDAR sensor installed on the Apple iPhone 12 Pro consumer smartphone is a real-time, handheld measurement instrument for accurately observing changes in snow depth. Two independent field experiments in Southern Ontario, Canada, found that the iPhone LiDAR was able to accurately capture daily changes in snow depth when compared to <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> snow ruler measurements. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">In situ</i> and LiDAR comparisons of xs <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$n=75$ </tex-math></inline-formula> days at measurement site A exhibit a correlation of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$r &gt; 0.99$ </tex-math></inline-formula> , mean absolute bias less than 1 mm, and a root mean squared error (RMSE) of approximately 6 mm. A similar positive agreement was also noted at the second field study site for <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$n=16$ </tex-math></inline-formula> measurements over the same period. The high accuracy of the LiDAR sensor suggests that a mobile application could be developed which allows users to quickly scan a snow-covered area before and after a snowfall event and consequently use this data to aid in filling current observational gaps through a citizen-science-based approach to measuring changes in snow depth.

Mathematical model of agricultural crop yield

Theoretical basis for presenting research results in agricultural science is mathematical statistics and probability theory using empirical forms of generalization of experimental data. To improve the methods of planning field experiment and processing its data using digital technologies, we proposed to use mathematical modeling based on physical principle of balance of cause-and-effect interactions in a closed physical system as a priority option. When analyzing impact of environmental factors on crop yields, the initial provisions, the mathematical modeling of the crop yield is based, on are not associated with characteristics of crops and natural conditions, therefore, the model options are universal in application and are valid for any agricultural crop, regardless of the region of cultivation. To ensure statistically correct digital information, based on the established forms of mathematical model, the field experiment layout aimed at establishing the dependence of the crop yield on yield-forming factors should include at least 4 options for nutritional levels (NPK) with a research duration of at least 4 years. To check the accuracy of the developed crop yield model, the data of independent field experiments of Professor N.N. Semenenko with barley and winter triticale has been used. It has been determined that, in Belarus, yield-forming factors, as a result of their impact on the grain yield, are arranged in the following decreasing sequence: total dose of applied NPK º the amount of precipitation during the active phases of growing season → air temperature for the same period. Calculations have shown that decrease in the number of yield-forming factors taken into account in the mathematical model from three (food, moisture and heat) to two (food and moisture) reduces the accuracy of calculating the grain crop yield insignificantly.

Vertical Trapping of the Coffee Berry Borer, Hypothenemus hampei (Coleoptera: Scolytinae), in Coffee.

Simple SummaryGlobally, the Coffee Berry Borer, Hypothenemus hampei (Ferrari) (Coleoptera: Curculionidae: Scolytinae), severely affects the quality and production of coffee. To understand how to control this pest, we studied their capture patterns at different trapping heights over time. Baited column traps captured more coffee berry borers at 0.5m height than at higher heights irrespective of temperature changes, rainfall, and relative humidity. Understanding the height position for the most efficient insect capture is useful for developing future cost-effective management strategies to control this coffee pest.The coffee industry loses millions of dollars annually worldwide due to the Coffee Berry Borer (CBB); these losses imply a decrease in quality and production. Traps are used to monitor their flight and for pest control. The main objective of this study was to determine the capture pattern and trap capture percentages of the CBB population over time using column traps (CTs) in two independent field experiments. CTs were composed of four traps installed at four different heights 0.5, 1.5, 2.5, and 3.5 m above ground. Our results demonstrated a significant difference in CBB capture by traps placed at different heights above the ground. The CT capture maintained a pattern throughout this study’s lag: the lower the height, the greater the percentage of CBBs captured. The study was conducted in two independent experiments (A and B). In Experiment A and B, the traps placed at 0.5 m caught 67% and 85% of the CBBs captured, respectively. Furthermore, the trap set at 1.5 m above the ground in the multi-level CT showed a higher capture percentage than the single placed trap (ST, also at 1.5 m about ground). The pattern of the capture and proportion of the CBB in the CTs was maintained throughout the study despite the season, changes in temperature, and relative air humidity. We suggest that CTs could be explored as a useful tool for capturing the CBB, considering its monitoring and management.

Quantification of Lactobacillus delbrueckii subsp. Bulgaricus and its applicability as a tracer for studying contamination spread on environmental surfaces

Infectious disease-causing pathogens can be transmitted via contact with contaminated environmental surfaces (i.e., fomite transmission). However, the physical mechanism of fomite transmission remains unclear because of a lack of suitable surrogate tracers. In this study, the non-toxic, non-human-origin and gram-positive bacterium Lactobacillus delbrueckii subsp. Bulgaricus was selected as a tracer, and its applicability for studying bacterial contamination spread on environmental surfaces was investigated in an office setting. After bacterial introduction by a designated carrier, surface contamination levels indicated by the L. bulgaricus proline iminopeptidase (pepIP) gene copy numbers were quantified using an optimized qPCR assay. This qPCR assay exhibited a high sensitivity (55 copies per reaction mixture and 1585 copies per surface sample), a wide dynamic range (7 orders of magnitude) and a high specificity for pepIP gene in environmental surface samples. Three independent, natural and unsupervised field experiments involving human participants confirmed the applicability of L. bulgaricus as a tracer in field studies and the pepIP gene as a unique marker of externally introduced contamination. Experimentally, contamination was distributed nearly equally over public surfaces, the carrier's seat location and the other seat locations in the office setting. An analysis by seat location revealed that the contamination level was attenuated as the physical distance from the carrier's seat location increased. Volunteers' faces were ubiquitously contaminated, suggesting a potentially high risk of fomite exposure via mucous membranes. In conclusion, L. bulgaricus can feasibly be used as a tracer organism in future large-scale field studies of bacterial contamination spread on environmental surfaces.

Effects of mowing regimes on forage yield and crude protein of Leymus chinensis (Trin.) Tzvel in Songnen grassland

AbstractForage dry matter (DM) yield and its nutrient content are important in livestock nutrition; however, they have distinct, even opposite responses to mowing regimes. To optimize forage resources, two independent field experiments were conducted to determine effects of initial mowing time (15‐day intervals from May 15 to September 1) and mowing frequency (one to five times per year) on DM yield and nutritive value of Leymus chinensis (Trin.) Tzvel. The greatest cumulative DM yield (cDMY), pre‐mowing crude protein yield (pCPY) and cumulative crude protein yield (cCPY) were attained when initial mowing occurred from July 15 to August 15. The crude protein (CP) concentration of pDMY was higher, whereas fiber concentrations were lower, when initial mowing was from May 15 to June 15, with opposite results when the initial mowing was delayed (July 1 to September 30). When mowing three times annually, cDMY and cCPY of L. chinensis were higher (p &lt; .05) than with less frequent mowing. With more than three mowings, accumulated CP yield of L. chinensis was not significantly affected. With four or five yearly mowings, accumulated DM yield of L. chinensis decreased significantly compared to mowing one to three times. In conclusion, based on DM yield and nutritive value, the optimal initial mowing date ranged from July 15 to August 15, whereas optimal mowing frequency was three times yearly.

Surprising spatiotemporal stability of a multi-peak fitness landscape revealed by independent field experiments measuring hybrid fitness.

The effect of the environment on fitness in natural populations is a fundamental question in evolutionary biology. However, experimental manipulations of both environment and phenotype at the same time are rare. Thus, the relative importance of the competitive environment versus intrinsic organismal performance in shaping the location, height, and fluidity of fitness peaks and valleys remains largely unknown. Here, we experimentally tested the effect of competitor frequency on the complex fitness landscape driving adaptive radiation of a generalist and two trophic specialist pupfishes, a scale‐eater and molluscivore, endemic to hypersaline lakes on San Salvador Island (SSI), Bahamas. We manipulated phenotypes, by generating 3407 F4/F5 lab‐reared hybrids, and competitive environment, by altering the frequency of rare transgressive hybrids between field enclosures in two independent lake populations. We then tracked hybrid survival and growth rates across these four field enclosures for 3–11 months. In contrast to competitive speciation theory, we found no evidence that the frequency of hybrid phenotypes affected their survival. Instead, we observed a strikingly similar fitness landscape to a previous independent field experiment, each supporting multiple fitness peaks for generalist and molluscivore phenotypes and a large fitness valley isolating the divergent scale‐eater phenotype. These features of the fitness landscape were stable across manipulated competitive environments, multivariate trait axes, and spatiotemporal heterogeneity. We suggest that absolute performance constraints and divergent gene regulatory networks shape macroevolutionary (interspecific) fitness landscapes in addition to microevolutionary (intraspecific) competitive dynamics. This interplay between organism and environment underlies static and dynamic features of the adaptive landscape.

Acetic acid immersion – A reactive pest treatment for bivalve aquaculture

Unwanted biofouling and predatory pests are a universal problem threatening aquaculture productivity and profitability. Various control approaches have been trialled, but industry uptake has been elusive due to the typically fine balance between pest and bivalve physiological tolerances (i.e., ‘therapeutic window’) and operational challenges related to infrastructure, scalability, and quality control. This study aimed to address these factors for acetic acid (AcOH), arguably the best-studied and most broadly applicable reactive treatment for bivalve aquaculture. Using case studies of farmed New Zealand green-lipped mussels (Perna canaliculus Gmelin 1791) and Pacific oysters (Crassostrea gigas Thunberg 1793), AcOH tolerances of various size classes of these bivalves were determined in a series of laboratory experiments, and cross-referenced to corresponding data for biofouling and predatory pests. Resulting ‘therapeutic windows’ formed the basis of provisional treatment parameters, being 2% AcOH for 60 s or 4% AcOH for 30 s for P. canaliculus and C. gigas, respectively. Three independent field experiments on operational P. canaliculus and C. gigas farms subsequently served to refine and validate the treatment parameters and associated operational procedures. For P. canaliculus, AcOH treatment had overall positive impacts on commercially relevant measures of aquaculture production, with the best performing treatment regimens of 1% or 2% AcOH for 60 s resulting in almost three times as many individual P. canaliculus per section of growing rope. Incorporating a subsequent air-drying step was also shown to reduce required AcOH immersion times, providing opportunities to enhance operational efficiencies via more rapid treatments. The provisional treatment parameters for C. gigas of 4% AcOH for 30 s were also highly effective against biofouling pests in the field and resulted in no detectable mortality of the culture species. Overall, this study demonstrates the utility of carefully refined and validated AcOH treatments to control problematic pests in bivalve aquaculture. It is essential to accurately determine ‘therapeutic windows’ for any given bivalve culture species and developing understanding of crop-pest interactions would better inform treatment timing and frequency. Such approaches could feed into wider frameworks to optimally manage pests below economically damaging thresholds, with AcOH ideally being one option in an arsenal of management interventions.

Evaluation of pyraclostrobin as a management tool of Groundnut ringspot virus in peanut crop

Yield losses due to Groundnut ringspot virus – GRSV (genus Orthotospovirus) infection have been observed across major peanut (Arachis hypogaea L.) growing areas in Brazil. However, effective management systems capable of minimizing GRSV damage are not yet available. The aim of the present study was to verify the effectiveness of the pyraclostrobin (a strobilurin fungicide reported as a potential activator of natural, large–spectrum plant defense mechanisms) in the management of GRSV in peanuts. Two independent field experiments were carried out in commercial peanut areas with a natural occurrence of GRSV. A completely randomized block design was used with a 5 × 2 factorial scheme, including four replicates, five peanut cultivars (‘Runner IAC 886’, ‘IAC OL4’, ‘IAC 503’, ‘IAC 505’, and ‘Granoleico’) and two treatments (with and without pyraclostrobin application). At 80 and 100 days after sowing, visual disease severity scores and the number of infected plants were evaluated, followed by virus quantification in the leaf tissues and yield. The cultivars ‘Granoleico’ and ‘IAC 503’ displayed the highest levels of GRSV susceptibility. Pyraclostrobin was found to be effective in reducing the number of GRSV–infected plants, as well as in attenuating disease severity. In addition, pyraclostrobin was able to promote significant yield increase. Even though the mechanism(s) of pyraclostrobin action against GRSV remain elusive, this fungicide can be regarded as a potential component for viral disease management programs in peanuts.