Crop Yield Losses Research Articles

Ozone-induced oxidative stress alleviation by biogenic silver nanoparticles and ethylenediurea in mung bean (Vigna radiata L.) under high ambient ozone.

Ground-level ozone (O3) is the most phytotoxic secondary air pollutant in the atmosphere, severely affecting crop yields worldwide. The role of nanoparticles (NP) in the alleviation of ozone-induced yield losses in crops is not known. Therefore, in the present study, we investigated the effects of biogenicB-AgNPs on the mitigation of ozone-induced phytotoxicity in mung bean and compared its results with ethylenediurea (EDU) for the first time. Two mung bean cultivars (Vigna radiata L., Cv. SML-668 and PDM-139) were foliar sprayed with weekly applications of B-AgNPs (0 = control, 10 and 25ppm) and EDU (0 = control, 200 and 300ppm) until maturation phase. Morphological, physiological, enzymatic, and non-enzymatic antioxidant data were collected 30 and 60days after germination (DAG). The mean O3 and AOT40 values (8hday-1) during the cultivation period were approximately 52ppb and 4.4ppm.h, respectively. More biomass was accumulated at the vegetative phase due to the impact of B-AgNPs and EDU, and more photosynthates were transported to the reproductive phase, increasing yield. We observed that the 10ppm B-AgNPs treatment had a more noticeable impact on yield parameters and lower Ag accumulation in seeds for both cultivars. Specifically, SML-668 cultivar treated with 10ppm B-AgNPs (SN1) showed greater increases in seed weight plant-1 (124.97%), hundred seed weight (33.45%), and harvest index (37.53%) in comparison to control. Our findings suggest that B-AgNPs can enhance growth, biomass, yield, and seed quality, and can improve mung bean ozone tolerance. Therefore, B-AgNPs may be a promising protectant for mung bean.

Phytohormone-Based Biostimulants as an Alternative Mitigating Strategy for Horticultural Plants Grown Under Adverse Multi-Stress Conditions: Common South African Stress Factors

Worldwide, it has been recorded extensively that plants are subjected to severe abiotic and biotic stressors. The scientific research community has widely reported that multi-abiotic stressors cause horticultural crop losses, accounting for at least 50 to 70% of the crop yield and quality losses. Therefore, this review focused on the detrimental effects caused by abiotic stress factors occurring in single-, combined- and multi-cell stresses on horticultural plants worldwide, along with the best production systems practices for mitigation during and post-single and combined abiotic or multi-stress damages. A conclusion and recommendation could be reached using the pool of research material, which constituted research articles, reviews, book chapters, thesis, research short communications and industrial short communications from at least twenty-five years ago. Findings showed that some of the leading abiotic stresses are single- and combined abiotic stressors like water deficit, salinity, soil pH, phosphate deficiency, wounding, soil density and pot size. Established commercial and smallholder farmers are globally adapting to plant growth regulators and biostimulants as part of their production systems. However, as much as the effectiveness of biostimulants containing humic acids, algal extracts, plant growth-promoting microorganisms and phytohormones has been reported to promote plant development under multi-stress, only a few studies are focusing on organic phytohormone-based biostimulants on horticultural crops grown under adverse multi stress factoring. In conclusion, the review recommends alternative solutions for emerging South African farmers and growers who cannot afford agricultural insurance options and energy alternatives on the common single- and combined abiotic- or multi-stress-factors.

Phylogenetic position of Pratylenchus sp. (Nematoda: Pratylenchidae) associated with grasslands using 28S rDNA from South Africa

Plant-parasitic nematodes are the main nematodes that live in the soil, causing yield loss in various crops. As endoparasites, Pratylenchus species can reduce the yield of grass and other plants by feeding on their roots. Because of its parasitic nature on plants, this species requires careful identification; in South Africa's Limpopo Province, grasslands are among the most vital agricultural resources. Therefore, this molecular study was conducted in 2023 at Limpopo University to identify the nematode from South Africa's soils using 28S rDNA marker. The recovered nematode was extracted using the tray method, and then its DNA was extracted using the chelex method. The nematode was identified as Pratylenchus. Afterward, 28S rDNA was amplified using specific primers to identify the nematode at the molecular level. The Nblast analysis based on the large subunit ribosomal DNA showed South African Pratylenchus had 99% similarity (OQ343703) with the South African population. Phylogenetic analysis using maximum likelihood placed this species with those molecularly identified as Pratylenchus in the same clade with highly supported (100) bootstrap values. In conclusion, this species was identified using 28S rDNA; however, other rDNA markers, such as ITS rDNA and mtDNA is recommended for a better understanding of Pratylenchus phylogeny.

Deep Learning in Robotics to Remove Ward of Weeds

Weeds are the problematic unwanted plants in the fields that causes, 33.16% yield loss in food crops, 41.26% in cereals, 31.88% in pulses, 40.82% in oilseeds, 34.23% in fiber crops, and 40.28% in rice crops. The Proposed System helps to optimization the work to yield in rice crop by removing weed that grows along crop, focusing on these issue is important as to yield the crops only with rice crop. This study focus on the issue in rice crop plant which grows along with weed (unwanted plant).New methodology introduced to remove the weed plant that grows with crop by the means of robotics. The image will be captured through drone in the field and the same frame co-ordinate forwarded to robotic designed with agriculture drone sensor which is coded using python to predict the accurate weed plant for statistical prediction. The robot locate the plant after comparing with the captured co-ordinates of drone with its own captured image and decide to pluck the weed plant grown along with crop

Recent advancements in the role of histone acetylation dynamics to improve stress responses in plants.

In eukaryotes, transcriptional regulation is determined by the DNA sequence and is facilitated through sophisticated and complex chromatin alterations and histone remodelling. Recent research has shown that the histone acetylation dynamic, an intermittent and reversible substitution, constitutes a prerequisite for chromatin modification. These changes in chromatin structure modulate genome-wide and specific changes in response to external and internal cues like cell differentiation, development, growth, light temperature, and biotic stresses. Histone acetylation dynamics also control the cell cycle. HATs and HDACs play a critical role in gene expression modulation during plant growth and response to environmental circumstances. It has been well established that HATs and HDACs interact with various distinct transcription factors and chromatin-remodelling proteins (CRPs) involved in the transcriptional regulation of several developmental processes. This review explores recent research on histone acyltransferases and histone deacetylases, mainly focusing on their involvement in plant biotic stress responses. Moreover, we also emphasized the research gaps that must be filled to fully understand the complete function of histone acetylation dynamics during biotic stress responses in plants. A thorough understanding of histone acetylation will make it possible to enhance tolerance against various kinds of stress and decrease yield losses in many crops.

Sulfonate derivatives bearing an amide unit: design, synthesis and biological activity studies

Pest disasters which occurs on crops is a serious problem that not only cause crop yield loss or even crop failure but can also spread a number of plant diseases.Sulfonate derivatives have been widely used in insecticide and fungicide research in recent years. On this basis, a series of sulfonate derivatives bearing an amide unit are synthesized and the biological activities are evaluated. The bioassay results showed that compounds A8, A13, A16, B1, B3, B4, B5, B10, B12 − 20, C3, C5, C9, C10, C14, C15, C17 and C19 showed 100% activity at a concentration of 500 µg/mL against the Plutella xylostella (P. xylostella). Among them, B15 which contains a thiadiazole sulfonate structure still shows 100% activity at 50 µg/mL concentration against P. xylostella and had the lowest median lethal concentration (LC50) (7.61 µg/mL) among the target compounds. Further mechanism studies are conducted on compounds with better insecticidal activity. Molecular docking results shows that B15 formed hydrophobic interactions π-π and hydrogen bonds with the indole ring of Trp532 and the carboxyl group of Asp384, respectively, with similar interaction distances or bond lengths as those of diflubenzuron. Moreover, chitinase inhibition assays are performed to further demonstrate its mode of action. In addition, the anti-bacterial activity of the series of compounds is also tested and the results showed that the series of compounds has moderate biological activity against Xanthomonas oryzae pv. oryzae (Xoo) and Xanthomonas oryzae pv. oryzicola (Xoc), with inhibition rates of 91%, 92% and 92%, 88% at the concentration of 100 µg/mL, respectively. Our study indicates that B15 can be used as a novel insecticide for crop protection.Graphical

Formation of the photoassimilation apparatus of pea (Pisum sativum L.) crops under biostimulants in arid conditions of the Southern Steppe of Ukraine

The Southern Steppe of Ukraine is characterised by a range of unfavourable agro-climatic conditions, which leads to inhibition of growth processes, disruption of physiological processes and loss of crop yields. The use of environmentally safe bioregulators stimulates growth processes, optimises nitrogen nutrition, increases the adaptability of legumes to adverse conditions and increases yields. The purpose of this study was to find out the specific features of the influence of biostimulants on the formation of the photoassimilation apparatus of pea of the Oplot variety in the Southern Steppe of Ukraine. A 3-year small-plot study was conducted to determine the leaf area index, total chlorophyll content, and net photosynthetic productivity in pea crops. The biostimulants were used for pre-sowing and foliar treatment of pea crops in the budding phase at concentrations described in the methodology. It was found that Stimpo (25 ml/t + 20 ml/ha) increased the leaf surface index in different stages of vegetation of pea variety Oplot by 1.12-1.54 times and Regoplant (250 ml/t + 50 ml/ha) increased the leaf surface index by 1.18-1.38 times compared to the control. A significant increase in the chlorophyll content in pea stipules was recorded after foliar treatment of crops with biostimulants and exceeded the value of control plants by 9.0-10.4% in the BBCH stages 61(65) – 75(79). Based on 3-year results, the positive impact of biostimulants on net photosynthetic productivity was proven. Thus, Stimpo and Regoplant increased the net photosynthetic productivity of pea crops by 35% and 22%, respectively, in the budding (BBCH 51-61) and flowering (BBCH 55-65) phases. The obtained scientific results contribute to the widespread use of the studied biostimulants in the technology of pea cultivation in the Southern Steppe zone of Ukraine to increase crop productivity and obtain a high-quality crop

Pumpkin Injury and Yield Response to Low Rates of 2,4-D Choline and Dicamba

The recent release of 2,4-D- and dicamba-tolerant soybean traits has increased the risk of off-target herbicide injury and yield loss for specialty crop growers in the midwestern United States. Most dicotyledonous plants, including many specialty crops like pumpkin (Cucurbita pepo), are susceptible to synthetic auxin herbicides; however, the relationship between off-target herbicide rate, visible crop injury, and eventual yield loss is not well documented. The objective of this 2-year field study in 2019 and 2020 was to determine the effect of sublethal herbicide rates of 2,4-D and dicamba on visible injury and crop yield loss in pumpkin when applied at the vegetative and flowering growth stages. Herbicides included 2,4-D choline salt (1066 g ae·ha−1 labeled rate) and dicamba diglycolamine salt (560 g ae·ha−1 labeled rate) ranging from 1/500 to 1/4 of the labeled rate. Visible injury ratings were recorded every 7 d after application and pumpkins were harvested and weighed when ripe. Injury and yield data were fit to a four-parameter log-logistic regression model to estimate effective doses (ED) required for 5% to 50% visible injury or yield loss. Pumpkin treated with the 1/10 and 1/4 rates of 2,4-D at both growth stages had visible injury (± 1 SE) ranging from 8% (± 3%) to 55% (± 3%), but injury did not always result in yield loss. Maximum yield loss from 2,4-D was 32% (± 2%), observed following the 1/4 rate at the vegetative growth stage in 2020 (estimated ED for 20% yield loss was ∼1/50). Pumpkin treated at the vegetative growth stage with the 1/10 and 1/4 rates of dicamba resulted in 65% (± 6%) to 82% (± 1%) visible injury and 33% (± 2%) to 86% (± 14%) yield loss (estimated ED for 20% yield loss was ∼1/10 in 2019 and ∼1/15 in 2020). At the flowering stage, dicamba rates of 1/10 and 1/4 caused visible injury of 31% (± 2%) to 74% (± 5%) and yield loss of 26% (± 10%) to 60% (± 14%) (estimated ED for 20% yield loss was ∼1/20 in 2019 and ∼1/5 in 2020). Susceptibility of pumpkin to 2,4-D and dicamba suggests herbicide applicators and pumpkin growers should consider strategies that mitigate off-target movement, including using nozzles that increase droplet size, shielded sprayers, thorough tank cleanout, buffer zones, and programs that facilitate communication between applicators and growers.

The mechanisms behind the contrasting responses to waterlogging in black-grass (Alopecurus myosuroides) and wheat (Triticum aestivum).

Black-grass (Alopecurus myosuroides ) is one of the most problematic agricultural weeds of Western Europe, causing significant yield losses in winter wheat (Triticum aestivum ) and other crops through competition for space and resources. Previous studies link black-grass patches to water-retaining soils, yet its specific adaptations to these conditions remain unclear. We designed pot-based waterlogging experiments to compare 13 biotypes of black-grass and six cultivars of wheat. These showed that wheat roots induced aerenchyma when waterlogged whereas aerenchyma-like structures were constitutively present in black-grass. Aerial biomass of waterlogged wheat was smaller, whereas waterlogged black-grass was similar or larger. Variability in waterlogging responses within and between these species was correlated with transcriptomic and metabolomic changes in leaves of control or waterlogged plants. In wheat, transcripts associated with regulation and utilisation of phosphate compounds were upregulated and sugars and amino acids concentrations were increased. Black-grass biotypes showed limited molecular responses to waterlogging. Some black-grass amino acids were decreased and one transcript commonly upregulated was previously identified in screens for genes underpinning metabolism-based resistance to herbicides. Our findings provide insights into the different waterlogging tolerances of these species and may help to explain the previously observed patchiness of this weed's distribution in wheat fields.

Exploring the Potential of Remote Sensing to Facilitate Integrated Weed Management in Smallholder Farms: A Scoping Review

In light of a growing population and climate change compounding existing pressures on the agri-food system, there is a growing need to diversify agri-food systems and optimize the productivity and diversity of smallholder farming systems to enhance food and nutrition security under climate change. In this context, improving weed management takes on added significance, since weeds are among the primary factors contributing to crop yield losses for smallholder farmers. Adopting remote-sensing-based approaches to facilitate precision agricultural applications such as integrated weed management (IWM) has emerged as a potentially more effective alternative to conventional weed control approaches. However, given their unique socio-economic circumstances, there remains limited knowledge and understanding of how these technological advancements can be best utilized within smallholder farm settings. As such, this study used a systematic scoping review and attribute analysis to analyze 53 peer-reviewed articles from Scopus to gain further insight into remote-sensing-based IWM approaches and identify which are potentially best suited for smallholder farm applications. The findings of this review revealed that unmanned aerial vehicles (UAVs) are the most frequently utilized remote sensing platform for IWM applications and are also well suited for mapping and monitoring weeds within spatially heterogeneous areas such as smallholder farms. Despite the potential of these technologies for IWM, several obstacles to their operationalization within smallholder farm settings must be overcome, and careful consideration must be given on how best to maximize their potential before investing in these technologies.

Co-designed agro-climate indicators identify different future climate effects for grape and olive across Europe

Co-design processes involving the scientific community, practitioners, end users and stakeholders can efficiently characterize harmful weather events during the growing season that potentially result in losses of crop yield and quality. This study builds on the experience of the EU Horizon 2020 project MED-GOLD for grape and olive. The identified agro-climate indicators are extended from the MED-GOLD regions to the entire ones where grape and olive are currently grown in Europe and Turkey, and used to assess climate change impacts with intrinsic adaptation relevance stemming from the co-design process. Before 2000, only a low fraction of the European grape and olive growing areas was exposed to extreme weather events as revealed by the agro-climate indicators, but this has changed rapidly afterward. Projections show increasingly widespread extreme high temperature events from 2020 to 2080. Approximately one-third of grapevine regions and over half of olive cultivation areas are expected to experience extreme drought conditions. Additionally, the frequency of compound extreme events will increase in the future, especially in the Mediterranean region and under the high-end emission scenario RCP8.5. This outcome calls for a new decision-making mindset that embeds expected levels of climate variability and extremes as the “new normal” for grape and olive in Europe. This will facilitate deployment of the required biophysical, economic and policy adaptation tools.

Artificial Intelligence: A Promising Tool for Application in Phytopathology

Artificial intelligence (AI) is revolutionizing approaches in plant disease management and phytopathological research. This review analyzes current applications and future directions of AI in addressing evolving agricultural challenges. Plant diseases annually cause 10–16% yield losses in major crops, prompting urgent innovations. Artificial intelligence (AI) shows an aptitude for automated disease detection and diagnosis utilizing image recognition techniques, with reported accuracies exceeding 95% and surpassing human visual assessment. Forecasting models integrating weather, soil, and crop data enable preemptive interventions by predicting spatial-temporal outbreak risks weeks in advance at 81–95% precision, minimizing pesticide usage. Precision agriculture powered by AI optimizes data-driven, tailored crop protection strategies boosting resilience. Real-time monitoring leveraging AI discerns pre-symptomatic anomalies from plant and environmental data for early alerts. These applications highlight AI’s proficiency in illuminating opaque disease patterns within increasingly complex agricultural data. Machine learning techniques overcome human cognitive constraints by discovering multivariate correlations unnoticed before. AI is poised to transform in-field decision-making around disease prevention and precision management. Overall, AI constitutes a strategic innovation pathway to strengthen ecological plant health management amidst climate change, globalization, and agricultural intensification pressures. With prudent and ethical implementation, AI-enabled tools promise to enable next-generation phytopathology, enhancing crop resilience worldwide.

Enhancing Biocontrol Potential: Development and Efficacy Assessment of a Liquid Formulation of Trichoderma Asperellum MSU007 against Sclerotium Rrolfsii

Global agricultural systems face significant challenges due to the devastating impact of Sclerotium rolfsii, a plant pathogen responsible for substantial crop yield losses. Considering this problem, this study aims to enhance biocontrol potential against S. rolfsii by developing and evaluating a liquid formulation of Trichoderma asperellum MSU007. We prepared 4 distinct liquid formulations of T. asperellum MSU007, incorporating various protectants: 10 % molasses, 5 % molasses, 5 % lactose and 5 % trehalose. After 45 days at 28 ± 2 °C, T. asperellum MSU007 spore counts remained consistent at 107 spores/mL across all formulations. All formulations resulted in no growth and effectively suppressed S. rolfsii mycelium growth at concentration of 4, 5 and 6 mL/L. Transferring inhibited mycelium to fresh Potato Dextrose Agar (PDA) showed growth resembling T. asperellum MSU007 within 48 h. Terrachor Super-X fungicide fully suppressed growth. Notably, the 5 % trehalose formulation continued inhibiting sclerotia germination even after 45-day storage. This study highlights T. asperellum MSU007 formulations, particularly those based on trehalose as promising agents for disease control and prolonged storage stability. Future mechanistic investigations will be crucial to comprehensive understanding and application. HIGHLIGHTS Liquid formulations of Trichoderma asperellum MSU007 with different protectants were developed for enhanced biocontrol against Sclerotium rolfsii. All formulations effectively suppressed S. rolfsii mycelium growth at various application rates. The 5 % trehalose-based formulation displayed prolonged inhibition of sclerotia germination even after 45-day storage. These findings suggest the potential of T. asperellum MSU007 formulations, particularly trehalose-based, for disease control and extended storage stability, warranting further mechanistic investigation. GRAPHICAL ABSTRACT

Seed Dormancy Dynamics and Germination Characteristics of Malva parviflora L.

Little mallow (Malva parviflora L.) is a notorious weed that causes substantial yield losses in winter crops. For effective weed management and seed testing, a deeper understanding of seed dormancy, germination behavior, and dormancy-breaking methods is necessary. Experiments were conducted to determine the effect of seed treatments, i.e., mechanical scarification, acid scarification, hot water treatment, and different germinating temperatures, i.e., 15 °C, 20 °C, or alternating 15–20 °C (16/8 h), on the seed dormancy in M.parviflora. A large proportion of M. parviflora seeds were physically dormant, with just 10.90% germination. Seed treatments had a significant influence on seed germination, seedling dry weight, vigor index, and water absorption (p ≤ 0.01). Among the various treatments, mechanical scarification enhanced germination by 32%, the vigor index by 487% and water uptake by 34%, and decreased percent hard seeds by 34%. Among the various germination temperatures, alternating 15–20 °C temperatures (16/8 h) gave the most significant result for germination and the lowest percent hard seeds. The findings of this study will serve as a valuable reference for seed testing and the development of suitable weed control strategies for M. parviflora.

Chilli Leaf Curl Disease: An Emerging Threat to Chilli Cultivation in Maharashtra, India

Chilli leaf curl disease (ChiLCD) locally known as ‘Churda Murda’ is a most destructive disease of chilli (Capsicum annuum) in India. The ChiLCD is caused by whitefly (Bemisia tabaci)-transmitted Begomovirus, belonging to the family Geminiviridae. A study was conducted to investigate the current status of ChiLCD in Maharashtra. Survey was carried out in chilli growing districts of Maharashtra to study the disease incidence (DI) and percent diseases index (PDI) of ChiLCD. Artificial Intelligence (AI)-based application (App) ‘Plantix–your crop doctor’ was used to assess the diagnosis of ChiLCD. During the survey different symptoms of ChiLCD, leaf curling, leaf yellowing, crinkling, puckering, vein banding and stunting were observed in diseased chilli plants. In this study, ‘Plantix–your crop doctor’ App accurately diagnosed the ChiLCD and its pathogen Chilli leaf curl virus (ChiLCV). High ChiLCD incidence of 85-100% with PDI of 53.8-62.7% was observed at Kemwadi village in Osmanabad district and 80-90% with PDI of 42.3-45.7% at Ranmasle village in Solapur district of Maharashtra. The high incidence of ChiLCD in Maharashtra has been taken into consideration and this can be correlated with various factors such as weather conditions, insecticide resistance in whitefly populations, and the appearance of virulent strains of ChiLCV. Early detection of ChiLCV using the AI-based ‘Plantix–your crop doctor’ App and effective management of insect vector whitefly could prevent ChiLCV spread and minimize the crop yield losses.

Coherent spore dispersion via drop-leaf interaction.

The dispersion of plant pathogens, such as rust spores, is responsible for more than 20% of global crop yield loss annually. However, the release mechanism of pathogens from flexible plant surfaces into the canopy is not well understood. In this study, we investigated the interplay between leaf elasticity and rainfall, revealing how a flexible leaf structure can generate a lateral flow stream, with embedded coherent structures that enhance transport. We first modeled the linear coupling between drop momentum, leaf vibration, and the stream flux from leaf surfaces. With Lagrangian diagnostics, we further mapped out the nested coherent structures around the fluttering profile, providing a dynamical description for local spore delivery. We hope the mechanistic details extracted here can facilitate the construction of physically informed analytical models for local crop disease management.

A Warmer and Wetter World Would Aggravate GHG Emissions Intensity in China's Cropland

AbstractMany agricultural regions in China are likely to become appreciably wetter or drier as the global climate warming increases. However, the impact of these climate change patterns on the intensity of soil greenhouse gas (GHG) emissions (GHGI, GHG emissions per unit of crop yield) has not yet been rigorously assessed. By integrating an improved agricultural ecosystem model and a meta‐analysis of multiple field studies, we found that climate change is expected to cause a 20.0% crop yield loss, while stimulating soil GHG emissions by 12.2% between 2061 and 2090 in China's agricultural regions. A wetter‐warmer (WW) climate would adversely impact crop yield on an equal basis and lead to a 1.8‐fold‐ increase in GHG emissions relative to those in a drier‐warmer (DW) climate. Without water limitation/excess, extreme heat (an increase of more than 1.5°C in average temperature) during the growing season would amplify 15.7% more yield while simultaneously elevating GHG emissions by 42.5% compared to an increase of below 1.5°C. However, when coupled with extreme drought, it would aggravate crop yield loss by 61.8% without reducing the corresponding GHG emissions. Furthermore, the emission intensity in an extreme WW climate would increase by 22.6% compared to an extreme DW climate. Under this intense WW climate, the use of nitrogen fertilizer would lead to a 37.9% increase in soil GHG emissions without necessarily gaining a corresponding yield advantage compared to a DW climate. These findings suggest that the threat of a wetter‐warmer world to efforts to reduce GHG emissions intensity may be as great as or even greater than that of a drier‐warmer world.

Quantifying potential trade-offs and win-wins between arthropod diversity and yield on cropland under agri-environment schemes–A meta-analysis

In Europe, agri-environment schemes (AES) are a key instrument to combat the ongoing decline of farmland biodiversity. AES aim is to support biodiversity and maintain ecosystem services, such as pollination or pest control. To what extent AES affect crop yield is still poorly understood. We performed a systematic review, including hierarchical meta-analyses, to investigate potential trade-offs and win-wins between the effectiveness of AES for arthropod diversity and agricultural yield on European croplands. Altogether, we found 26 studies with a total of 125 data points that fulfilled our study inclusion criteria. From each study, we extracted data on biodiversity (arthropod species richness and abundance) and yield for fields with AES management and control fields without AES. The majority of the studies reported significantly higher species richness and abundance of arthropods (especially wild pollinators) in fields with AES (31 % increase), but yields were at the same time significantly lower on fields with AES compared to control fields (21 % decrease). Aside from the opportunity costs, AES that promote out-of-production elements (e.g. wildflower strips), supported biodiversity (29–32 % increase) without significantly compromising yield (2–5 % increase). Farmers can get an even higher yield in these situations than in current conventional agricultural production systems without AES. Thus, our study is useful to identify AES demonstrating benefits for arthropod biodiversity with negligible or relatively low costs regarding yield losses. Further optimization of the design and management of AES is needed to improve their effectiveness in promoting both biodiversity and minimizing crop yield losses.

Using wavelet transform and hybrid CNN – LSTM models on VOC & ultrasound IoT sensor data for non-visual maize disease detection

Early detection of plant diseases is crucial for safeguarding crop yield, especially in regions vulnerable to food insecurity, such as Sub-Saharan Africa. One of the significant contributors to maize crop yield loss is the Northern Leaf Blight (NLB), which traditionally takes 14–21 days to visually manifest on maize. This study introduces a novel approach for detecting NLB as early as 4–5 days using Internet of Things (IoT) sensors, which can identify the disease before any visual symptoms appear. Utilizing Convolutional Neural Networks (CNN) and Long Short Term Memory (LSTM) models, nonvisual measurements of Total Volatile Organic Compounds (VOCs) and ultrasound emissions from maize plants were captured and analyzed. A controlled experiment was conducted on four maize varieties, and the data obtained were used to develop and validate a hybrid CNN-LSTM model for VOC classification and an LSTM model for ultrasound anomaly detection. The hybrid CNN-LSTM model, enhanced with wavelet data preprocessing, achieved an F1 score of 0.96 and an Area under the ROC Curve (AUC) of 1.00. In contrast, the LSTM model exhibited an impressive 99.98% accuracy in identifying anomalies in ultrasound emissions. Our findings underscore the potential of IoT sensors in early disease detection, paving the way for innovative disease prevention strategies in agriculture. Future work will focus on optimizing the models for IoT device deployment, incorporating chatbot technology, and more sensor data will be incorporated for improved accuracy and evaluation of the models in a field environment.

CRISPR/Cas9-mediated homology donor repair base editing system to confer herbicide resistance in maize (Zea mays L.)

Weed infestation is a significant concern to crop yield loss, globally. The potent broad-spectrum glyphosate (N-phosphomethyl-glycine) has a widely utilized herbicide, acting on the shikimic acid pathway within chloroplast by inhibiting 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS). This crucial enzyme plays a vital role in aromatic amino acid synthesis. Repurposing of CRISPR/Cas9-mediated gene-editing was the inflection point for generating novel crop germplasm with diverse genetic variations in essential agronomic traits, achieved through the introduction of nucleotide substitutions at target sites within the native genes, and subsequent induction of indels through error-prone non-homologous end-joining DNA repair mechanisms. Here, we describe the development of efficient herbicide-resistant maize lines by using CRISPR/Cas9 mediated site-specific native ZmEPSPS gene fragment replacement via knock-out of conserved region followed by knock-in of desired homologous donor repair (HDR-GATIPS-mZmEPSPS) with triple amino acid substitution. The novel triple substitution conferred high herbicide tolerance in edited maize plants. Transgene-free progeny harbouring the triple amino acid substitutions revealed agronomic performances similar to that of wild-type plants, suggesting that the GATIPS-mZmEPSPS allele substitutions are crucial for developing elite maize varieties with significantly enhanced glyphosate resistance. Furthermore, the aromatic amino acid contents in edited maize lines were significantly higher than in wild-type plants. The present study describing the introduction of site-specific CRISPR/Cas9- GATIPS mutations in the ZmEPSPS gene via genome editing has immense potential for higher tolerance to glyphosate with no yield penalty in maize.