Seasonal fluctuation and alternative host plants of vegetable crop-infesting tephritids in non-vegetable growing areas in South Sudanese zone of Burkina Faso.

This study was carried out in 3 types of biotopes where vegetable crops are not grown to highlight their contribution to the dynamics of vegetable-infesting flies. To this end, a trapping system based on a sexual attractant, the Cuelure associated with an insecticide was set up in 18 biotopes (6 natural areas, 6 mango orchards, and 6 agroforestry parks) in the regions of Hauts Bassins and Cascades in the South-West of Burkina Faso. During the trapping monitoring, which was done every 2 wk to collect insects captured, fruits present in 3 types of biotopes were sampled and incubated for insect emergence. Ten Dacus (Fabricius) [Diptera: Tephritidae] species and Zeugodacus cucurbitae (Coquillett) [Diptera: Tephritidae] were trapped in the study area. The predominant species captured was Z. cucurbitae (52.93%) followed by Dacus punctatifrons (Karsch) [Diptera: Tephritidae] (29.89%) and Dacus humeralis (Bezzi) (12.71%). Six tephritid species were emerged from 6 wild fruit species belonging to Cucurbitaceae, Apocynaceae, and Passifloraceae families. Fruit flies were more abundant from Jul to Nov with peaks observed in Aug or Oct depending on the species. Citrullus colocynthis L. (Cucurbitaceae), Lagenaria sp. (Cucurbitaceae), Passiflora foetida L. (Passifloraceae), and Passiflora sp. acted as reservoir host plants of Dacus ciliatus (Loew), Dacus bivittatus (Bigot), Dacus vertebratus (Bezzi) [Diptera: Tephritidae], D. punctatifrons, and Z. cucurbitae, the major vegetable insect pests in West Africa. The 3 types of biotopes acted as suitable refuge areas of vegetable crop-infesting fruit flies either for the favorable microclimate or for the alternative host plants.

Crop rotational diversity can mitigate climate-induced grain yield losses.

Diversified crop rotations have been suggested to reduce grain yield losses from the adverse climatic conditions increasingly common under climate change. Nevertheless, the potential for climate change adaptation of different crop rotational diversity (CRD) remains undetermined. We quantified how climatic conditions affect small grain and maize yields under different CRDs in 32 long-term (10-63 years) field experiments across Europe and North America. Species-diverse and functionally rich rotations more than compensated yield losses from anomalous warm conditions, long and warm dry spells, as well as from anomalous wet (for small grains) or dry (for maize) conditions. Adding a single functional group or crop species to monocultures counteracted yield losses from substantial changes in climatic conditions. The benefits of a further increase in CRD are comparable with those of improved climatic conditions. For instance, the maize yield benefits of adding three crop species to monocultures under detrimental climatic conditions exceeded the average yield of monocultures by up to 553 kg/ha under non-detrimental climatic conditions. Increased crop functional richness improved yields under high temperature, irrespective of precipitation. Conversely, yield benefits peaked at between two and four crop species in the rotation, depending on climatic conditions and crop, and declined at higher species diversity. Thus, crop species diversity could be adjusted to maximize yield benefits. Diversifying rotations with functionally distinct crops is an adaptation of cropping systems to global warming and changes in precipitation.

Use of modelling tools to assess climate change impacts on smallholder oil seed yields in South Africa.

Oil seed crops are the second most important field crops after cereals in the agricultural economy globally. The use and demand for oilseed crops such as groundnut, soybean and sunflower have grown significantly, but climate change is expected to alter the agroecological conditions required for oilseed crop production. This study aims to present an approach that utilizes decision-making tools to assess the potential climate change impacts on groundnut, soybean and sunflower yields and the greenhouse gas emissions from the management of the crops. The Decision Support Tool for Agrotechnology Transfer (DSSAT v4.7), a dynamic crop model and the Cool Farm Tool, a GHG calculator, was used to simulate yields and estimate GHG emissions from these crops, respectively. Four representative concentration pathways (RCPs 2.6, 4.5, 6.0, and 8.5), three nitrogen (0, 75, and 150 kg/ha) and phosphorous (0, 30 and 60 P kg/ha) fertilizer rates at three sites in Limpopo, South Africa (Ofcolaco, Syferkuil and Punda Maria) were used in field trials for calibrating the models. The highest yield was achieved by sunflower across all crops, years and sites. Soybean yield is projected to decrease across all sites and scenarios by 2030 and 2050, except at Ofcolaco, where yield increases of at least 15.6% is projected under the RCP 4.5 scenario. Positive climate change impacts are predicted for groundnut at Ofcolaco and Syferkuil by 2030 and 2050, while negative impacts with losses of up to 50% are projected under RCP8.5 by 2050 at Punda Maria. Sunflower yield is projected to decrease across all sites and scenarios by 2030 and 2050. A comparison of the climate change impacts across sites shows that groundnut yield is projected to increase under climate change while notable yield losses are projected for sunflower and soybean. GHG emissions from the management of each crop showed that sunflower and groundnut production had the highest and lowest emissions across all sites respectively. With positive climate change impacts, a reduction of GHG emissions per ton per hectare was projected for groundnuts at Ofcolaco and Syferkuil and for sunflower in Ofcolaco in the future. However, the carbon footprint from groundnut is expected to increase by 40 to 107% in Punda Maria for the period up to 2030 and between 70-250% for 2050, with sunflower following a similar trend. We conclude that climate change will potentially reduce yield for oilseed crops while management will increase emissions. Therefore, in designing adaptation measures, there is a need to consider emission effects to gain a holistic understanding of how both climate change impacts on crops and mitigation efforts could be targeted.

Assessment of induced allelopathy in crop-weed co-culture with rye-pigweed model.

This study evaluates induced allelopathy in a rye-pigweed model driven by rye's (Secale cereale L.) allelopathic potential as a cover crop and pigweed's (Amaranthus retroflexus L.) notoriety as a weed. The response of rye towards pigweed's presence in terms of benzoxazinoids (BXs) provides valuable insight into induced allelopathy for crop improvement. In the 2 week plant stage, pigweed experiences a significant reduction in growth in rye's presence, implying allelopathic effects. Rye exhibits increased seedling length and BXs upsurge in response to pigweed presence. These trends persist in the 4 week plant stage, emphasizing robust allelopathic effects and the importance of different co-culture arrangements. Germination experiments show rye's ability to germinate in the presence of pigweed, while pigweed exhibits reduced germination with rye. High-performance liquid chromatography with diode-array detection (HPLC-DAD) analysis identifies allelopathic compounds (BXs), 2,4-dihydroxy-1,4-benzoxazin-3-one (DIBOA) and 2,4-dihydroxy-7-methoxy-1,4-benzoxazin-3-one (DIMBOA) in rye. Rye significantly increases BX production in response to pigweed, age-dependently. Furthermore, pigweed plants are screened for possible BX uptake from the rhizosphere. Results suggest that allelopathy in rye-pigweed co-cultures is influenced by seed timing, and age-dependent dynamics of plants' allelopathic compounds, providing a foundation for further investigations into chemical and ecological processes in crop-weed interactions.

Cover crops support the climate change mitigation potential of agroecosystems.

Cover crops have the potential to mitigate climate change by reducing negative impacts of agriculture on ecosystems. This study is first to quantify the net climate change mitigation impact of cover crops including land-use effects. A systematic literature and data review was conducted to identify major drivers for climate benefits and costs of cover crops in maize (Zea maize L.) production systems. The results indicate that cover crops lead to a net climate change mitigation impact (NCCMI) of 3.30 Mg CO2e ha-1 a-1. We created four scenarios with different impact weights of the drivers and all of them showing a positive NCCMI. Carbon land benefit, the carbon opportunity costs based on maize yield gains following cover crops, is the major contributor to the NCCMI (34.5% of all benefits). Carbon sequestration is the second largest contributor (33.8%). The climate costs of cover crops are mainly dominated by emissions from their seed production and foregone benefits due to land use for cover crops seeds. However, these two costs account for only 15.8% of the benefits. Extrapolating these results, planting cover crops before all maize acreage in the EU results in a climate change mitigation of 49.80 million Mg CO2e a-1, which is equivalent to 13.0% of the EU's agricultural emissions. This study highlights the importance of incorporating cover crops into sustainable cropping systems to minimize the agricultural impact to climate change.

Extracting the winter wheat using the decision tree based on time series dual-polarization SAR feature and NDVI.

Winter wheat is one of the most important crops in the world. It is great significance to obtain the planting area of winter wheat timely and accurately for formulating agricultural policies. Due to the limited resolution of single SAR data and the susceptibility of single optical data to weather conditions, it is difficult to accurately obtain the planting area of winter wheat using only SAR or optical data. To solve the problem of low accuracy of winter wheat extraction only using optical or SAR images, a decision tree classification method combining time series SAR backscattering feature and NDVI (Normalized Difference Vegetation Index) was constructed in this paper. By synergy using of SAR and optical data can compensate for their respective shortcomings. First, winter wheat was distinguished from other vegetation by NDVI at the maturity stage, and then it was extracted by SAR backscattering feature. This approach facilitates the semi-automated extraction of winter wheat. Taking Yucheng City of Shandong Province as study area, 9 Sentinel-1 images and one Sentinel-2 image were taken as the data sources, and the spatial distribution of winter wheat in 2022 was obtained. The results indicate that the overall accuracy (OA) and kappa coefficient (Kappa) of the proposed method are 96.10% and 0.94, respectively. Compared with the supervised classification of multi-temporal composite pseudocolor image and single Sentinel-2 image using Support Vector Machine (SVM) classifier, the OA are improved by 10.69% and 5.66%, respectively. Compared with using only SAR feature for decision tree classification, the producer accuracy (PA) and user accuracy (UA) for extracting the winter wheat are improved by 3.08% and 8.25%, respectively. The method proposed in this paper is rapid and accurate, and provide a new technical method for extracting winter wheat.

Effects of experimental drought and plant diversity on multifunctionality of a model system for crop rotation.

In low-diversity productive grasslands, modest changes to plant diversity (richness, composition and relative abundance) may affect multiple ecosystem functions (multifunctionality), including yield. Despite the economic importance of productive grasslands, effects of plant diversity and environmental disturbance on multifunctionality are very rarely quantified. We systematically varied species richness, composition, and relative abundance of grassland ley communities and manipulated water supply (rainfed and drought) to quantify effects of diversity and environmental disturbance on multifunctionality. We then replaced the grassland leys with a monoculture crop to investigate 'follow-on' effects. We measured six agronomy-related ecosystem functions across one or both phases: yield, yield consistency, digestibility and weed suppression (grassland ley phase), legacy effect (effect on follow-on crop yield), and nitrogen fertiliser efficiency (full rotation). Drought reduced most ecosystem functions, although effects were species- and function-specific. Increased plant diversity affected mean performance, and reduced variation, across the six functions (contributing to multifunctional stability). Multifunctionality index values across a wide range of mixture diversity were higher than the best monoculture under both rainfed and drought conditions (transgressive over-performance). Higher-diversity, lower-nitrogen (150N) mixtures had higher multifunctionality than a low-diversity, higher-nitrogen (300N) grass monoculture. Plant diversity in productive grasslands is a practical farm-scale management action to mitigate drought impacts and enhance multifunctionality of grassland-crop rotation systems.

Harnessing Phytohormones: Advancing Plant Growth and Defence Strategies for Sustainable Agriculture.

Phytohormones, pivotal regulators of plant growth and development, are increasingly recognized for their multifaceted roles in enhancing crop resilience against environmental stresses. In this review, we provide a comprehensive synthesis of current research on utilizing phytohormones to enhance crop productivity and fortify their defence mechanisms. Initially, we introduce the significance of phytohormones in orchestrating plant growth, followed by their potential utilization in bolstering crop defences against diverse environmental stressors. Our focus then shifts to an in-depth exploration of phytohormones and their pivotal roles in mediating plant defence responses against biotic stressors, particularly insect pests. Furthermore, we highlight the potential impact of phytohormones on agricultural production while underscoring the existing research gaps and limitations hindering their widespread implementation in agricultural practices. Despite the accumulating body of research in this field, the integration of phytohormones into agriculture remains limited. To address this discrepancy, we propose a comprehensive framework for investigating the intricate interplay between phytohormones and sustainable agriculture. This framework advocates for the adoption of novel technologies and methodologies to facilitate the effective deployment of phytohormones in agricultural settings and also emphasizes the need to address existing research limitations through rigorous field studies. By outlining a roadmap for advancing the utilization of phytohormones in agriculture, this review aims to catalyse transformative changes in agricultural practices, fostering sustainability and resilience in agricultural settings.

Ecological weed management and square planting influenced the weed management, and crop productivity in direct-seeded rice.

Herbicide use may pose a risk of environmental pollution or evolution of resistant weeds. As a result, an experiment was carried out to assess the influence of different non-chemical weed management tactics (one hoeing (HH) at 12 DAS followed by (fb) one hand weeding at 30 DAS, one HH at 12 DAS fb Sesbania co-culture and its mulching, one HH at 12 DAS fb rice straw mulching @ 4t ha-1, one HH at 12 DAS fb rice straw mulching @ 6 t ha-1) on weed control, crop growth and yield, and economic returns in direct-seeded rice (DSR). Experiment was conducted during kharif season in a split-plot design and replicated thrice. Zero-till seed drill-sown crop (PN) had the lowest weed density at 25 days after sowing (DAS), while square planting geometry (PS) had the lowest weed density at 60 DAS. PS also resulted in a lower weed management index (WMI), agronomic management index (AMI), and integrated weed management index (IWMI), as well as higher growth attributes, grain yield (4.19 t ha-1), and net return (620.98 US$ ha-1). The cultivar Arize 6444 significantly reduced weed density and recorded higher growth attributes, yield, and economic return. In the case of weed management treatments, one HH at 12 DAS fb Sesbania co-culture and its mulching had the lowest weed density, Shannon-weinner index and eveness at 25 DAS. However, one hoeing at 12 DAS fb one hand weeding at 30 DAS (HH + WH) achieved the highest grain yield (4.85 t ha-1) and net returns (851.03 US$ ha-1) as well as the lowest weed density at 60 DAS. PS × HH + WH treatment combination had the lowest weed persistent index (WPI), WMI, AMI, and IWMI, and the highest growth attributes, production efficiency, and economic return.

Finger millet: a hero in the making to combat food insecurity.

Climate change and population growth pose challenges to food security. Major crops such as maize, wheat, and rice are expected to face yield reductions due to warming in the coming years, highlighting the need for incorporating climate-resilient crops in agricultural production systems. Finger millet (Eleusine coracana (L.) Gaertn) is a nutritious cereal crop adapted to arid regions that could serve as an alternative crop for sustaining the food supply in low rainfall environments where other crops routinely fail. Despite finger millet's nutritional qualities and climate resilience, it is deemed an "orphan crop," neglected by researchers compared to major crops, which has hampered breeding efforts. However, in recent years, finger millet has entered the genomics era. Next-generation sequencing resources, including a chromosome-scale genome assembly, have been developed to support trait characterization. This review discusses the current genetic and genomic resources available for finger millet while addressing the gaps in knowledge and tools that are still needed to aid breeders in bringing finger millet to its full production potential.

Maize/soybean intercropping increases nutrient uptake, crop yield and modifies soil physio-chemical characteristics and enzymatic activities in the subtropical humid region based in Southwest China.

Intercropping, a widely adopted agricultural practice worldwide, aims to increase crop yield, enhance plant nutrient uptake, and optimize the utilization of natural resources, contributing to sustainable farming practices on a global scale. However, the underlying changes in soil physio-chemical characteristics and enzymatic activities, which contribute to crop yield and nutrient uptake in the intercropping systems are largely unknown. Consequently, a two-year (2021-2022) field experiment was conducted on the maize/soybean intercropping practices with/without nitrogen (N) fertilization (i.e., N0; 0 N kg ha-1 and N1; 225 N kg ha-1 for maize and 100 N kg ha-1 for soybean ) to know whether such cropping system can improve the nutrients uptake and crop yields, soil physio-chemical characteristics, and soil enzymes, which ultimately results in enhanced crop yield. The results revealed that maize intercropping treatments (i.e., N0MI and N1MI) had higher crop yield, biomass dry matter, and 1000-grain weight of maize than mono-cropping treatments (i.e., N0MM, and N1MM). Nonetheless, these parameters were optimized in N1MI treatments in both years. For instance, N1MI produced the maximum grain yield (10,105 and 11,705 kg ha-1), biomass dry matter (13,893 and 14,093 kg ha-1), and 1000-grain weight (420 and 449 g) of maize in the year 2021 and 2022, respectively. Conversely, soybean intercropping treatments (i.e., N0SI and N1SI) reduced such yield parameters for soybean. Also, the land equivalent ratio (LER) and land equivalent ratio for N fertilization (LERN) values were always greater than 1, showing the intercropping system's benefits in terms of yield and improved resource usage. Moreover, maize intercropping treatments (i.e., N0MI and N1MI) and soybean intercropping treatments (i.e., N0SI and N1SI) significantly (p < 0.05) enhanced the nutrient uptake (i.e., N, P, K, Ca, Fe, and Zn) of maize and soybean, however, these nutrients uptakes were more prominent in N1MI and N1SI treatments of maize and soybean, respectively in both years (2021 and 2022) compared with their mono-cropping treatments. Similarly, maize-soybean intercropping treatments (i.e., N0MSI and N1MSI) significantly (p < 0.05) improved the soil-based N, P, K, NH4, NO3, and soil organic matter, but, reduced the soil pH. Such maize-soybean intercropping treatments also improved the soil enzymatic activities such as protease (PT), sucrose (SC), acid phosphatase (AP), urease (UE), and catalase (CT) activities. This indicates that maize-soybean intercropping could potentially contribute to higher and better crop yield, enhanced plant nutrient uptake, improved soil nutrient pool, physio-chemical characteristics, and related soil enzymatic activities. Thus, preferring intercropping to mono-cropping could be a preferable choice for ecologically viable agricultural development.

Modeling maize growth and nitrogen dynamics using CERES-Maize (DSSAT) under diverse nitrogen management options in a conservation agriculture-based maize-wheat system.

Agricultural field experiments are costly and time-consuming, and often struggling to capture spatial and temporal variability. Mechanistic crop growth models offer a solution to understand intricate crop-soil-weather system, aiding farm-level management decisions throughout the growing season. The objective of this study was to calibrate and the Crop Environment Resource Synthesis CERES-Maize (DSSAT v 4.8) model to simulate crop growth, yield, and nitrogen dynamics in a long-term conservation agriculture (CA) based maize system. The model was also used to investigate the relationship between, temperature, nitrate and ammoniacal concentration in soil, and nitrogen uptake by the crop. Additionally, the study explored the impact of contrasting tillage practices and fertilizer nitrogen management options on maize yields. Using field data from 2019 and 2020, the DSSAT-CERES-Maize model was calibrated for plant growth stages, leaf area index-LAI, biomass, and yield. Data from 2021 were used to evaluate the model's performance. The treatments consisted of four nitrogen management options, viz., N0 (without nitrogen), N150 (150 kg N/ha through urea), GS (Green seeker-based urea application) and USG (urea super granules @150kg N/ha) in two contrasting tillage systems, i.e., CA-based zero tillage-ZT and conventional tillage-CT. The model accurately simulated maize cultivar's anthesis and physiological maturity, with observed value falling within 5% of the model's predictions range. LAI predictions by the model aligned well with measured values (RMSE 0.57 and nRMSE 10.33%), with a 14.6% prediction error at 60 days. The simulated grain yields generally matched with measured values (with prediction error ranging from 0 to 3%), except for plots without nitrogen application, where the model overestimated yields by 9-16%. The study also demonstrated the model's ability to accurately capture soil nitrate-N levels (RMSE 12.63 kg/ha and nRMSE 12.84%). The study concludes that the DSSAT-CERES-Maize model accurately assessed the impacts of tillage and nitrogen management practices on maize crop's growth, yield, and soil nitrogen dynamics. By providing reliable simulations during the growing season, this modelling approach can facilitate better planning and more efficient resource management. Future research should focus on expanding the model's capabilities and improving its predictions further.

Emerging concern of nano-pollution in agro-ecosystem: Flip side of nanotechnology.

Nanomaterials (NMs) have proven to be a game-changer in agriculture, showcasing their potential to boost plant growth and safeguarding crops. The agricultural sector has widely adopted NMs, benefiting from their small size, high surface area, and optical properties to augment crop productivity and provide protection against various stressors. This is attributed to their unique characteristics, contributing to their widespread use in agriculture. Human exposure from various components of agro-environmental sectors (soil, crops) NMs residues are likely to upsurge with exposure paths may stimulates bioaccumulation in food chain. With the aim to achieve sustainability, nanotechnology (NTs) do exhibit its potentials in various domains of agriculture also have its flip side too. In this review article we have opted a fusion approach using bibliometric based analysis of global research trend followed by a holistic assessment of pros and cons i.e. toxicological aspect too. Moreover, we have also tried to analyse the current scenario of policy associated with the application of NMs in agro-environment.

Biostimulants: A sufficiently effective tool for sustainable agriculture in the era of climate change?

Climate change is currently considered as one of the main concerns of the agriculture sector, as it limits crop production and quality. Furthermore, the current context of global crisis with international political instability and war conflicts over the world is pushing the agriculture sector even more to urgently boost productivity and yield and doing so in a sustainable way in the current frame of climate change. Biostimulants can be an effective tool in alleviating the negative effects of environmental stresses to which plants are exposed, such as drought, salinity, heavy metals and extreme temperatures etc. Biostimulants act through multiple mechanisms, modifying gene expression, metabolism and phytohormone production, promoting the accumulation of compatible solutes and antioxidants and mitigating oxidative stress. However, it is important to keep in mind that the use and effect of biostimulants has limitations and must be accompanied by other techniques to ensure crop yield and quality in the current frame of climate change, such as proper crop management and the use of other sustainable resources. Here, we will not only highlight the potential use of biostimulants to face future agricultural challenges, but also take a critical look at their limitations, underlining the importance of a broad vision of sustainable agriculture in the context of climate change.

PAU Smart Seeder: a novel way forward for rice residue management in North-west India.

In winter, the paddy residues become wet during morning and late evening due to dew, which restricts the operation of sowing machines (Happy Seeder and Super Seeder) into paddy residues, as wet residues do not slide on furrow openers/tines. A PAU Smart Seeder (PSS) was developed and evaluated for a four-wheel tractor that can sow wheat with optimum crop establishment in combined harvested rice fields. The PSS were evaluated for its performance under varying straw load, forward speed, and rotor speed in terms of fuel consumption, field capacity, seed emergence, and grain yield. The crop establishment and wheat yield of PSS was also compared with the existing straw management machines Happy Seeder (HS) and Super Seeder (SS) under heavy paddy residue conditions. The effect of the straw load was more pronounced on dependent variables than the effect of the speed index. PSS performance was best at a forward speed of 2.6 km h-1, rotor speed of 127.5 rpm, and a straw load of 6 t ha-1. Average fuel consumption using PSS was lower than SS but higher than HS. Wheat emergence was higher by 15.6 and 25.7% on the PSS plots compared to HS and SS, respectively. Average wheat grain yield in PSS plots was significantly higher by 12.7 and 18.9% than SS and HS, respectively in one experiment, while the grain yield was similar for both PSS and HS in other experiments. PSS has a novel mechanism to manage paddy straw and simultaneously sow wheat into a heavy straw load (> 8 t ha-1) mixture of anchored and loose straw. In conclusion, PSS showed promise for in-situ management of rice straw as it eliminates most of the operational problems encountered by the existing seeders (HS and SS).

Recent advances in genome editing strategies for balancing growth and defence in sugarcane (Saccharum officinarum).

Sugarcane (Saccharum officinarum ) has gained more attention worldwide in recent decades because of its importance as a bioenergy resource and in producing table sugar. However, the production capabilities of conventional varieties are being challenged by the changing climates, which struggle to meet the escalating demands of the growing global population. Genome editing has emerged as a pivotal field that offers groundbreaking solutions in agriculture and beyond. It includes inserting, removing or replacing DNA in an organism's genome. Various approaches are employed to enhance crop yields and resilience in harsh climates. These techniques include zinc finger nuclease (ZFN), transcription activator-like effector nuclease (TALEN) and clustered regularly interspaced short palindromic repeats/associated protein (CRISPR/Cas). Among these, CRISPR/Cas is one of the most promising and rapidly advancing fields. With the help of these techniques, several crops like rice (Oryza sativa ), tomato (Solanum lycopersicum ), maize (Zea mays ), barley (Hordeum vulgare ) and sugarcane have been improved to be resistant to viral diseases. This review describes recent advances in genome editing with a particular focus on sugarcane and focuses on the advantages and limitations of these approaches while also considering the regulatory and ethical implications across different countries. It also offers insights into future prospects and the application of these approaches in agriculture.

Functions of Basic Helix-Loop-Helix (bHLH) Proteins in the Regulation of Plant Responses to Cold, Drought, Salt, and Iron Deficiency: A Comprehensive Review.

Abiotic stresses including cold, drought, salt, and iron deficiency severely impair plant development, crop productivity, and geographic distribution. Several bodies of research have shed light on the pleiotropic functions of BASIC HELIX-LOOP-HELIX (bHLH) proteins in plant responses to these abiotic stresses. In this review, we mention the regulatory roles of bHLH TFs in response to stresses such as cold, drought, salt resistance, and iron deficiency, as well as in enhancing grain yield in plants, especially crops. The bHLH proteins bind to E/G-box motifs in the target promoter and interact with various other factors to form a complex regulatory network. Through this network, they cooperatively activate or repress the transcription of downstream genes, thereby regulating various stress responses. Finally, we present some perspectives for future research focusing on the molecular mechanisms that integrate and coordinate these abiotic stresses. Understanding these molecular mechanisms is crucial for the development of stress-tolerant crops.

Digital Twins in Agriculture: Orchestration and Applications.

Digital Twins have emerged as an outstanding opportunity for precision farming, digitally replicating in real-time the functionalities of objects and plants. A virtual replica of the crop, including key agronomic development aspects such as irrigation, optimal fertilization strategies, and pest management, can support decision-making and a step change in farm management, increasing overall sustainability and direct water, fertilizer, and pesticide savings. In this review, Digital Twin technology is critically reviewed and framed in the context of recent advances in precision agriculture and Agriculture 4.0. The review is organized for each step of agricultural lifecycle, edaphic, phytotechnologic, postharvest, and farm infrastructure, with supporting case studies demonstrating direct benefits for agriculture production and supply chain considering both benefits and limitations of such an approach. Challenges and limitations are disclosed regarding the complexity of managing such an amount of data and a multitude of (often) simultaneous operations and supports.

Agricultural production and air pollution: An investigation on crop straw fires.

In numerous developing nations, the pervasive practice of crop residue incineration is a principal contributor to atmospheric contamination in agricultural operations. This study examines the repercussions of such biomass combustion on air quality during the autumnal harvest season, utilizing data acquired from satellite-based remote sensing of fire events and air pollution measurements. Employing wind direction information alongside difference-in-difference and fixed-effects methodologies, this investigation rectifies estimation inaccuracies stemming from the non-random distribution of combustion occurrences. The empirical findings reveal that agricultural residue burning precipitates an elevation in average PM2.5 and PM10 concentrations by approximately 27 and 22 µg/m3 during the autumnal incineration period, respectively. Furthermore, air pollution attributed to residue burning in prominent grain-producing regions exceeds the national average by approximately 40%. By integrating economic paradigms into agri-environmental inquiries, this study offers novel insights and substantiation of the environmental expenditures engendered by crop residue burning, juxtaposed with extant meteorological and ecological research findings.