Roberta Masin

WeedTurf: a predictive model to aid control of annual summer weeds in turf

Abstract Predicting weed emergence is useful for planning weed management programs. Unfortunately, our ability to anticipate initial emergence and subsequent levels of emergence from simple field observations or weather reports is often inadequate to achieve optimal control. Weed emergence models may provide predictive tools that help managers anticipate best management options and times and, thereby, improve weed control. In this study, the germination characteristics of four annual grass weeds (large crabgrass, goosegrass, green foxtail, and yellow foxtail) were investigated under different temperatures and water stresses to calculate base temperatures and base water potentials. These parameters were used to develop a mathematical model describing seedling emergence processes in terms of hydrothermal time. Hydrothermal time describes seed germination in a single equation by considering the interaction of soil water potential and soil temperature. The model, called WeedTurf, predicted emergence with some accuracy, especially for large crabgrass (lowest efficiency index [EF] value 0.95) and green foxtail (lowest EF value 0.91). These results suggest the possibility of developing interactive computer software to determine the critical timing of weed removal and provide improved recommendations for herbicide application timing. Nomenclature: Goosegrass, Eleusine indica (L.) Gaertn. ELEIN; green foxtail, Setaria viridis (L.) Beauv. SETVI; large crabgrass, Digitaria sanguinalis (L.) Scop. DIGSA; yellow foxtail, Setaria glauca (L.) Beauv. SETLU.

Temperature and Water Potential as Parameters for Modeling Weed Emergence in Central-Northern Italy

Abstract Predicting weed emergence dynamics can help farmers to plan more effective weed control. The hydrothermal time concept has been used to model emergence as a function of temperature and water potential. Application of this concept is possible if the specific biological thresholds are known. This article provides a data set of base temperature and water potential of eight maize weeds (velvetleaf, redroot pigweed, common lambsquarters, large crabgrass, barnyardgrass, yellow foxtail, green foxtail, and johnsongrass). For five of these species, two ecotypes from two extreme regions of the predominant maize-growing area in Italy (Veneto and Tuscany), were collected and compared to check possible differences that may arise from using the same thresholds for different populations. Seedling emergence of velvetleaf and johnsongrass were modeled using three different approaches: (1) thermal time calculated assuming 5 C as base temperature for both species; (2) thermal time using the specific estimated base temperatures; and (3) hydrothermal time using the specific, estimated base temperatures and water potentials. All the species had base temperatures greater than 10 C, with the exception of velvetleaf (3.9 to 4.4 C) and common lambsquarters (2.0 to 2.6 C). All species showed a calculated base-water potential equal or up to −1.00 MPa. The thresholds of the two ecotypes were similar for all the studied species, with the exception of redroot pigweed, for which the Veneto ecotype showed a water potential lower than −0.41 MPa, whereas it was −0.62 MPa for the Tuscany ecotype. Similar thresholds have been found to be useful in hydrothermal time models covering two climatic regions where maize is grown in Italy. Furthermore, a comparison between the use of specific, estimated, and common thresholds for modeling weed emergence showed that, for a better determination of weed control timing, it is often necessary to estimate the specific thresholds. Nomenclature: Barnyardgrass, Echinochloa crus-galli (L.) Beauv. ECHCG; common lambsquarters, Chenopodium album L. CHEAL; green foxtail, Setaria viridis (L.) Beauv. SETVI; johnsongrass, Sorghum halepense (L.) Pers. SORHA; large crabgrass, Digitaria sanguinalis (L.) Scop. DIGSA; redroot pigweed, Amaranthus retroflexus L. AMARE; velvetleaf, Abutilon theophrasti Medik. ABUTH; yellow foxtail, Setaria pumila (Poir.) Roemer & J. A. Schultes SETLU.

Weed–Corn Competition Parameters in Late-Winter Sowing in Northern Italy

Abstract In recent years, interest has increased in late-winter sowing of corn in northern Italy because of many agronomic advantages. However, cold and rainy weather slows initial crop growth, which can favor weed infestation. There is, therefore, a need for appropriate timing of weed control tactics based on an understanding of the competitive relationship and dynamics between crop and weeds. Five experiments were conducted over 4 yr, with a series of treatments increasing either duration of interference or length of weed-free period. Yield data were fitted with sigmoidal equations to find the critical point (CP) and critical period of weed control (CPWC). Although the CP is determined only by the competition between weed and crop, the CPWC is also market dependent. To quantify the effect of weed flora on the CP, a multiple regression model was tested, taking into account weed density, inflection point, and slope parameter of the Gompertz model of the cumulated infestation. The results confirmed that the late-winter sowing date increases the importance of late winter– and early spring–emerging weeds. In general, the precompetitive period was longer in the late winter–sown corn than in traditional midspring-sown corn. The delayed start of the CPWC makes control more difficult with a preemergence herbicide, which raises questions on the utility of this agronomic technique. Multiple regression analysis showed that the position of CP can be estimated with the density, earliness, and competitiveness of the infestation. Furthermore, the slope/inflection point ratio of the Gompertz model appears to be independent of sowing date. Results suggest that the weed–crop competition mechanism can be represented with simply the weed flora dynamic parameters and that a combination of crop–weed competition studies and emergence prediction models can predict the position of CP and give useful information about the CPWC and weed management. Nomenclature: Corn, Zea mays L. cv. ‘PR33 J24’

Modeling Weed Emergence in Italian Maize Fields

Abstract A hydrothermal time model was developed to simulate field emergence for three weed species in maize (common lambsquarters, johnsongrass, and velvetleaf). Models predicting weed emergence facilitate well-timed and efficient POST weed control strategies (e.g., chemical and mechanical control methods). The model, called AlertInf, was created by monitoring seedling emergence from 2002 to 2008 in field experiments at three sites located in the Veneto region in northeastern Italy. Hydrothermal time was calculated using threshold parameters of temperature and water potential for germination estimated in previous laboratory studies with seeds of populations collected in Veneto. AlertInf was validated with datasets from independent field experiments conducted in Veneto and in Tuscany (west central Italy). Model validation resulted in both sites in efficiency index values ranging from 0.96 to 0.99. AlertInf, based on parameters estimated in a single region, was able to predict the timing of emergence in several sites located at the two extremes of the Italian maize growing area. Nomenclature: common lambsquarters, Chenopodium album L.,CHEAL; johnsongrass, Sorghum halepense L. Pers, SORHA; velvetleaf, Abutilon theophrasti Medik., ABUTH.

Vegetated Ditches for the Mitigation of Pesticides Runoff in the Po Valley.

In intensive agricultural systems runoff is one of the major potential diffuse pollution pathways for pesticides and poses a risk to surface water. Ditches are common in the Po Valley and can potentially provide runoff mitigation for the protection of watercourses. The effectiveness depends on ditch characteristics, so there is an urgent need for site-specific field trials. The use of a fugacity model (multimedia model) can allows recognition of the mitigation main processes. A field experiment was conducted in order to evaluate the mitigation capacity of a typical vegetated ditch, and results were compared with predictions by a fugacity model. To evaluate herbicide mitigation after an extreme runoff, the ditch was flooded with water containing mesotrione, S-metolachlor and terbuthylazine. Two other subsequent floods with uncontaminated water were applied 27 and 82 days later to evaluate herbicides release. Results show that the ditch can immediately reduce runoff concentration of herbicides by at least 50% even in extreme flooding conditions. The half-distances were about 250 m. As a general rule, a runoff of 1 mm from 5 ha is mitigated by 99% in 100 m of vegetated ditch. Herbicides retention in the vegetated ditch was reversible, and the second flood mobilized 0.03-0.2% of the previous one, with a concentration below the drinking water limit of 0.1 μg L-1. No herbicide was detected in the third flood, because the residual amount in the ditch was too low. Fugacity model results show that specific physical-chemical parameters may be used and a specific soil-sediment-plant compartment included for modelling herbicides behaviour in a vegetated ditch, and confirm that accumulation is low or negligible for herbicides with a half-life of 40 days or less. Shallow vegetated ditches can thus be included in a general agri-environment scheme for the mitigation of pesticides runoff together with wetlands and linear buffer strips. These structures are present in the landscape, and their environmental role can be exploited by proper management.

A Single-Time Survey Method to Predict the Daily Weed Density for Weed Control Decision-Making

Decision-making processes must indicate if, how, and when weed control should be practiced. So far, Decision Support Systems (DSSs) for weed control to prevent crop yield losses can guide decisions on “if” and “how.” Experience shows that farmers need a DSS that can also guide when to treat, but this can only be done if the actual weed density observed in the field is known during the crop cycle. Emergence models allow the prediction of daily density, but precision depends on the survey date. This study focuses on the estimation of the date of the survey for the best prediction of the daily density throughout the crop cycle. The predicted daily density of each species can be used by DSSs without any further survey, saving time and money and improving the use of the DSSs. Results showed that the best date is when the actual density of each weed reaches or exceeds 50% emergence, and this is earlier than the critical point date, supporting the validity of the date estimation method. The possibility to provide specific advice for farmers considering a proper mortality rate of weed seedlings is then discussed. The ability to optimize the date of sampling can improve the reliability of decision-making tools for integrated weed management, in agreement with the European Union goal of sustainable use of pesticides and more environmentally sustainable cropping systems through the use of integrated pest management.

Prospects for crowdsourced information on the geomorphic ‘engineering’ by the invasive Coypu (Myocastor coypus)

ABSTRACT: Among the most invasive species, the Coypu (Myocastor coypus) best exemplifies the widespread effect of alien species on ecosystems. Among the impacts, the induced erosion in riverbanks has an increasing economic and social importance. Despite its significance, this type of erosion is rarely quantified, and the available information is limited to local knowledge, grey literature, and maintenance reports. This research shows the potential of freely and instantly available Structure‐from‐Motion (SfM) photogrammetry to obtain crowdsourced information based on smartphone images. The results highlight how it is possible to provide a rough estimate of the damages with relatively low or null cost of application, and limited expert knowledge and expenditure of time, depending on the scale of analysis. The proposed technique provides a fresh approach to a known long‐standing issue, offering a new source of information for farmers, researchers, wildlife managers, as well as for land managers and planners. The potential applications of such a technique and its unprecedented ease of use and very low cost offer effective tools for management plans and scientific research, providing a basis to relate eroded volumes to the functioning of the drainage system and the connected agroecosystem. The method would also enable the opportunity of participatory and opportunistic crowdsourced sensing. Further scientific research on the crowd‐based data on erosion should encourage standardisation of data gathering and accessibility, together with a public involvement in information exchange, to generate a better understanding and awareness of erosion problems also for other fields of research. Copyright

Evaluation of Weed Emergence Model AlertInf for Maize in Soybean

Abstract AlertInf is a recently developed model to predict the daily emergence of three important weed species in maize cropped in northern Italy (common lambsquarters, johnsongrass, and velvetleaf). Its use can improve the effectiveness and sustainability of weed control, and there has been growing interest from farmers and advisors. However, there are two important limits to its use: the low number of weed species included and its applicability only to maize. Consequently, the aim of this study was to expand the AlertInf weed list and extend its use to soybean. The first objective was to add another two important weed species for spring-summer crops in Italy, barnyardgrass and large crabgrass. Given that maize and soybean have different canopy architectures that can influence the interrow microclimate, the second objective was to compare weed emergence in maize and soybean sown on the same date. The third objective was to evaluate if AlertInf was transferable to soybean without recalibration, thus saving time and money. Results showed that predictions made by AlertInf for all five species simulated in soybean were satisfactory, as shown by the high efficiency index (EF) values, and acceptable from a practical point of view. The fact that the algorithm used for estimating weed emergence in maize was also efficient for soybean, at least for crops grown in northeastern Italy with standard cultural practices, encourages further development of AlertInf and the spread of its use. Nomenclature: Common lambsquarters, Chenopodium album L., CHEAL; barnyardgrass, Echinochloa crus-galli (L.) Beauv., ECHCG; johnsongrass, Sorghum halepense (L.) Pers, SORHA; large crabgrass, Digitaria sanguinalis (L.) Scop., DIGSA; velvetleaf, Abutilon theophrasti Medik., ABUTH; maize, Zea mays L.; soybean, Glycine max (L.) Merr.

Estimation and Comparison of Base Temperatures for Germination of European Populations of Velvetleaf (Abutilon theophrasti) and Jimsonweed (Datura stramonium)

Abstract Weed emergence models require biological parameters such as base temperature for germination, determination of which is costly and time-consuming. Transferability of these parameters across different populations may therefore represent one of the main constraints for the development and practical use of emergence models at a large scale. A collaborative project was undertaken to assess the interpopulation variability of base temperature for germination in different European populations of velvetleaf and jimsonweed and evaluate possible applicative consequences in terms of weed control. Seeds were collected in Italy, Portugal, and Spain, and each population was then sown in every country, obtaining nine seed batches named as experimental lots. Base temperature for germination was estimated for each experimental lot to calculate lot-specific accumulation of growing degree days (GDD) under three dissimilar climatic scenarios. Threshold date (TD50) was calculated as the date when GDD accumulation of a given experimental lot surpassed the values corresponding to 50% of cumulative field emergence of seedlings. GDD accumulation and TD50 were then used as indicators to identify differences among experimental lots within each climatic scenario. No significant differences were detected among base temperatures estimated for velvetleaf experimental lots or among their patterns of accumulation of GDD and TD50 values within climatic scenarios. Each value of base temperature determined for a single experimental lot could therefore be adopted to model germination for all the lots regardless of the population of origin or cultivation site. In contrast, the population of origin affected the base temperature for jimsonweed, with significantly higher values for experimental lots of the Portuguese population. From an applicative perspective, differences among patterns of accumulation of GDD and TD50 of several experimental lots within each climatic scenario suggest the need to use population-specific values as base temperature for germination and emergence modeling of jimsonweed. Nomenclature: Jimsonweed, Datura stramonium L. DATST; velvetleaf, Abutilon theophrasti Medik. ABUTH.

Inhibiting effect of shallow seed burial on grass weed emergence

Loddo D., Vasileiadis V.P., Masin R., Zuin M.C., Zanin G. (2016): Inhibiting effect of shallow seed burial on grass weed emergence. Plant Protect. Sci., 52: 64–69. The efficacy of superficial tillage as a sustainable tool to reduce the emergence of Digitaria sanguinalis , setaria viridis, and sorghum halepense was evaluated with field experiments. Seeds were buried at 1, 2, 5, and 10 cm of depth to simulate seed vertical distribution caused by autumn superficial tillage. Seedling emergence was monitored weekly for two years after sowing. The highest emergence was obtained in the first year after sowing and from 1 and 2 cm. sorghum halepense was only slightly affected by seed burial, with 15% of emergence from 10 cm of depth, while D. sanguinalis was strongly affected, with 4% of emergence from 5 cm. The efficacy of superficial tillage as control tool could vary according to local weed flora.