Distribution of residence time in rotary-drum composting and implications for hygienization.

Rotary drums enable rapid composting compared to static systems. Residence times (RT) of 3-5 days are commonly applied to fulfill sanitary requirements and ensure the initial stabilization of organic matter. Practically, RT distribution (RTD) implies that a portion of the feed is discharged earlier than the mean RT, which may not guarantee safe application of the end product. This study assessed RTD and other physical-chemical and biological parameters of cattle manure and green waste composted in an EcodrumTM rotary drum (∼10 m3). Two types of tracers were used: pieces of plastic tubing and lumps of raw material in which plant seeds were buried, which were packed in nylon socks. A transient-state during which less than 50 % of the drum volume was occupied was distinguished from a steady-state stage, during which the drum operated with its optimal loading of about two-thirds of its volume. Starting temperatures inside the drum were close to ambient when the drum was mostly empty and then increased up to 60-65 °C as the occupied volume approached 50 %. The two types of tracers seemed to provide complementary measurements; under steady-state conditions, actual RTs were 60 % of the mean RT for 10 % of the feed material. The viability of plant seeds which were included in tracers was somewhat dependent on the specific RT. Under transient-state conditions, even shorter RTs (relative to the mean RT) are expected, coupled with non-thermophilic conditions, reducing the likelihood of adequate destruction of pathogens.

Comparative study of bacterial community dynamics in different soils following application of the herbicide atrazine.

Microbial communities in cultivated soils control the fate of pollutants associated with agricultural practice. The present study was designed to explore the response of bacterial communities to the application of the widely-used herbicide atrazine in three different crop fields that differ significantly in their physicochemical structure and nutritional content: the nutrient-rich (with relatively high carbon and nitrogen content) Newe Yaar (NY) and Ha-Ogen (HO) soils and the nutrient-poor, sandy Sde-Eliyahu (SE) soil. The 16 S rRNA gene amplicon sequencing revealed the nutrient poor HO soil differs in its response to atrazine in comparison to the two nutrient-rich soils both in the shortest persistence of atrazine and its effect on community structure and composition. Potential reported bacterial degraders of atrazine such as Pseudomonas, Clostridium and Bacillus were more abundant in contaminated sandy/poor soils (HO) whereas bacteria known for nitrogen cycling such as Azospirillum, Sinorhizobium, Nitrospira and Azohydromonas were significantly more abundant in the nutrient rich contaminated SE soils. No significant increase of potential indigenous degrader Arthrobacter was detected in SE and NY soils whereas a significant increase was recorded with HO soils. An overall shift in bacterial community composition following atrazine application was observed only in the nutrient poor soil. Understanding atrazine persistence and microbiome response to its application of in dependence with soil types serve the design of precision application strategies.

Modeling-Guided Amendments Lead to Enhanced Biodegradation in Soil.

Extensive use of agrochemicals is emerging as a serious environmental issue coming at the cost of the pollution of soil and water resources. Bioremediation techniques such as biostimulation are promising strategies used to remove pollutants from agricultural soils by supporting the indigenous microbial degraders. Though considered cost-effective and eco-friendly, the success rate of these strategies typically varies, and consequently, they are rarely integrated into commercial agricultural practices. In the current study, we applied metabolic-based community-modeling approaches for promoting realistic in terra solutions by simulation-based prioritization of alternative supplements as potential biostimulants, considering a collection of indigenous bacteria. Efficacy of biostimulants as enhancers of the indigenous degrader Paenarthrobacter was ranked through simulation and validated in pot experiments. A two-dimensional simulation matrix predicting the effect of different biostimulants on additional potential indigenous degraders (Pseudomonas, Clostridium, and Geobacter) was crossed with experimental observations. The overall ability of the models to predict the compounds that act as taxa-selective stimulants indicates that computational algorithms can guide the manipulation of the soil microbiome in situ and provides an additional step toward the educated design of biostimulation strategies. IMPORTANCE Providing the food requirements of a growing population comes at the cost of intensive use of agrochemicals, including pesticides. Native microbial soil communities are considered key players in the degradation of such exogenous substances. Manipulating microbial activity toward an optimized outcome in efficient biodegradation processes conveys a promise of maintaining intensive yet sustainable agriculture. Efficient strategies for harnessing the native microbiome require the development of approaches for processing big genomic data. Here, we pursued metabolic modeling for promoting realistic in terra solutions by simulation-based prioritization of alternative supplements as potential biostimulants, considering a collection of indigenous bacteria. Our genomic-based predictions point at strategies for optimizing biodegradation by the native community. Developing a systematic, data-guided understanding of metabolite-driven targeted enhancement of selected microorganisms lays the foundation for the design of ecologically sound methods for optimizing microbiome functioning.

Power on! Low-energy electrophysical treatment is an effective new weed control approach.

BACKGROUND: Environmental concerns are driving the call for adoption of alternative nonchemical weeding approaches. This study aimed to develop and evaluate a novel, precise, low-energy electrophysical treatment weeding systems and to provide new insight into their control mechanism. Two electrophysical treatment systems, based on AC (2.2 kV) and DC (40 kV) energy sources, were developed and evaluated. The impacts of various operational and biological factors on the weed control effectiveness were evaluated. Additionally, thermal images were taken during the treatments to document plant temperature. RESULTS: Treatments via direct leaf contact caused greater damage to Amaranth plants than the stem contact treatments, with 75% and 20% biomass reduction compared to control, respectively. Treatment of early growth stages was favorable over later growth stages, with 100% and 75% biomass reduction for Trifolium pretense plants treated with 0.0125 W h 2 and 4 weeks after seeding, respectively, compared to control. Additionally, the applied energy affected treatment performance, with its impact varying across the growth stages and species; at the two-leaf growth stage, 0.0025 W h treatment was sufficient for plant death. A >40 °C increase in plant temperature was measured during the electrophysical treatment, with the temperature of some plant organs reaching ~70 °C. CONCLUSION: Results from this study demonstrate the potential use of electrophysical treatment as an effective weed control tool. The low energetic demands in the new systems provide suitable control results when applied at early stages. Temperature increase seemed to be one of the main control factors, yet efficacy was affected by various biological factors.

Genetic improvement of wheat early vigor promote weed-competitiveness under Mediterranean climate.

Chemical weed-control is the most effective practice for wheat, however, rapid evolution of herbicide-resistant weeds threat food-security and calls for integration of non-chemical practices. We hypothesis that integration of alternative GA-responsive dwarfing genes into elite wheat cultivars can promote early vigor and weed-competitiveness under Mediterranean climate. We develop near-isogenic lines of bread wheat cultivars with GAR dwarfing genes and evaluate them for early vigor and weed-competitiveness under various environmental and management conditions to identify promising NIL for weed-competitiveness and grain yield. While all seven NILs responded to external gibberellic acid application, they exhibited differences in early vigor. Greenhouse and field evaluations highlighted NIL OC1 (Rht8andRht12) as a promising line, with significant advantage in canopy early vigor over its parental. To facilitate accurate and continuous early vigor data collection, we applied non-destructive image-based phenotyping approaches which offers non-expensive and end-user friendly solution for selection. NIL OC1 was tested under different weed density level, infestation waves, and temperatures and highlight the complex genotypic × environmental × management interactions. Our findings demonstrate the potential of genetic modification of dwarfing genes as promising approach to improve weed-competitiveness, and serve as basis for future breeding efforts to support sustainable wheat production under semi-arid Mediterranean climate.

3-D Image-Driven Morphological Crop Analysis: A Novel Method for Detection of Sunflower Broomrape Initial Subsoil Parasitism.

Effective control of the parasitic weed sunflower broomrape (Orobanche cumana Wallr.) can be achieved by herbicides application in early parasitism stages. However, the growing environmental concerns associated with herbicide treatments have motivated the adoption of precise chemical control approaches that detect and treat infested areas exclusively. The main challenge in developing such control practices for O. cumana lies in the fact that most of its life-cycle occurs in the soil sub-surface and by the time shoots emerge and become observable, the damage to the crop is irreversible. This paper approaches early O. cumana detection by hypothesizing that its parasitism already impacts the host plant morphology at the sub-soil surface developmental stage. To validate this hypothesis, O. cumana- infested sunflower and non-infested control plants were grown in pots and imaged weekly over 45-day period. Three-dimensional plant models were reconstructed using image-based multi-view stereo followed by derivation of their morphological parameters, down to the organ-level. Among the parameters estimated, height and first internode length were the earliest definitive indicators of infection. Furthermore, the detection timing of both parameters was early enough for herbicide post-emergence application. Considering the fact that 3-D morphological modeling is nondestructive, is based on commercially available RGB sensors and can be used under natural illumination; this approach holds potential contribution for site specific pre-emergence managements of parasitic weeds and as a phenotyping tool in O. cumana resistant sunflower breeding projects.

Use of a visible reporter marker- myb-related gene in crop plants to minimize herbicide usage against weeds.

Weeds, a main threat to agricultural productivity worldwide, are mostly controlled by herbicides. To minimize herbicide usage by targeting only weedy areas, we developed a new methodology for robust weed detection that relies on manipulating the crop plant's leaf hue, without affecting crop fitness. We generated transgenic tobacco (Nicotiana tabacum Xanthi) lines overexpressing the anthocyanin pigment as a traceable marker that differentiates transgenes from the surrounding weeds at an early stage. Transformation with the anthocyanin VlmybA1-2 gene produced purple-colored leaves. Subsequent gene silencing with vector pTRV2:VlmybA1-2 significantly reduced anthocyanin pigments in tobacco leaves 40 days after agroinfiltration, with a concomitant reduction in VlmybA1-2 transcript levels. Purple hue faded gradually, and there were no fitness costs in terms of plant height or leaf number in the silenced vs. non-silenced tobacco transgenes. These results could lead to a new sustainable weed-control method that will alleviate weed-related ecological, agricultural and economic issues.

Using genetically modified tomato crop plants with purple leaves for absolute weed/crop classification.

BACKGROUND: Weed/crop classification is considered the main problem in developing precise weed-management methodologies, because both crops and weeds share similar hues. Great effort has been invested in the development of classification models, most based on expensive sensors and complicated algorithms. However, satisfactory results are not consistently obtained due to imaging conditions in the field. RESULTS: We report on an innovative approach that combines advances in genetic engineering and robust image-processing methods to detect weeds and distinguish them from crop plants by manipulating the crop's leaf color. We demonstrate this on genetically modified tomato (germplasm AN-113) which expresses a purple leaf color. An autonomous weed/crop classification is performed using an invariant-hue transformation that is applied to images acquired by a standard consumer camera (visible wavelength) and handles variations in illumination intensities. CONCLUSION: The integration of these methodologies is simple and effective, and classification results were accurate and stable under a wide range of imaging conditions. Using this approach, we simplify the most complicated stage in image-based weed/crop classification models.