Salt-tolerant plant growth-promoting bacteria as a versatile tool for combating salt stress in crop plants.

Soil salinization poses a great threat to global agricultural ecosystems, and finding ways to improve the soils affected by salt and maintain soil health and sustainable productivity has become a major challenge. Various physical, chemical and biological approaches are being evaluated to address this escalating environmental issue. Among them, fully utilizing salt-tolerant plant growth-promoting bacteria (PGPB) has been labeled as a potential strategy to alleviate salt stress, since they can not only adapt well to saline soil environments but also enhance soil fertility and plant development under saline conditions. In the last few years, an increasing number of salt-tolerant PGPB have been excavated from specific ecological niches, and various mechanisms mediated by such bacterial strains, including but not limited to siderophore production, nitrogen fixation, enhanced nutrient availability, and phytohormone modulation, have been intensively studied to develop microbial inoculants in agriculture. This review outlines the positive impacts and growth-promoting mechanisms of a variety of salt-tolerant PGPB and opens up new avenues to commercialize cultivable microbes and reduce the detrimental impacts of salt stress on plant growth. Furthermore, considering the practical limitations of salt-tolerant PGPB in the implementation and potential integration of advanced biological techniques in salt-tolerant PGPB to enhance their effectiveness in promoting sustainable agriculture under salt stress are also accentuated.

Exploring selection signatures in the divergence and evolution of lipid droplet (LD) associated genes in major oilseed crops.

BACKGROUND: Oil bodies or lipid droplets (LDs) in the cytosol are the subcellular storage compartments of seeds and the sites of lipid metabolism providing energy to the germinating seeds. Major LD-associated proteins are lipoxygenases, phospholipaseD, oleosins, TAG-lipases, steroleosins, caleosins and SEIPINs; involved in facilitating germination and enhancing peroxidation resulting in off-flavours. However, how natural selection is balancing contradictory processes in lipid-rich seeds remains evasive. The present study was aimed at the prediction of selection signatures among orthologous clades in major oilseeds and the correlation of selection effect with gene expression. RESULTS: The LD-associated genes from the major oil-bearing crops were analyzed to predict natural selection signatures in phylogenetically close-knit ortholog clusters to understand adaptive evolution. Positive selection was the major force driving the evolution and diversification of orthologs in a lineage-specific manner. Significant positive selection effects were found in 94 genes particularly in oleosin and TAG-lipases, purifying with excess of non-synonymous substitution in 44 genes while 35 genes were neutral to selection effects. No significant selection impact was noticed in Brassicaceae as against LOX genes of oil palm. A heavy load of deleterious mutations affecting selection signatures was detected in T-lineage oleosins and LOX genes of Arachis hypogaea. The T-lineage oleosin genes were involved in mainly anther, tapetum and anther wall morphogenesis. In Ricinus communis and Sesamum indicum > 85% of PLD genes were under selection whereas selection pressures were low in Brassica juncea and Helianthus annuus. Steroleosin, caleosin and SEIPINs with large roles in lipid droplet organization expressed mostly in seeds and were under considerable positive selection pressures. Expression divergence was evident among paralogs and homeologs with one gene attaining functional superiority compared to the other. The LOX gene Glyma.13g347500 associated with off-flavor was not expressed during germination, rather its paralog Glyma.13g347600 showed expression in Glycine max. PLD-α genes were expressed on all the tissues except the seed,δ genes in seed and meristem while ß and γ genes expressed in the leaf. CONCLUSIONS: The genes involved in seed germination and lipid metabolism were under strong positive selection, although species differences were discernable. The present study identifies suitable candidate genes enhancing seed oil content and germination wherein directional selection can become more fruitful.

Spectral enhancement of PlanetScope using Sentinal-2 images to estimate soybean yield and seed composition.

Soybean is an essential crop to fight global food insecurity and is of great economic importance around the world. Along with genetic improvements aimed at boosting yield, soybean seed composition also changed. Since conditions during crop growth and development influences nutrient accumulation in soybean seeds, remote sensing offers a unique opportunity to estimate seed traits from the standing crops. Capturing phenological developments that influence seed composition requires frequent satellite observations at higher spatial and spectral resolutions. This study introduces a novel spectral fusion technique called multiheaded kernel-based spectral fusion (MKSF) that combines the higher spatial resolution of PlanetScope (PS) and spectral bands from Sentinel 2 (S2) satellites. The study also focuses on using the additional spectral bands and different statistical machine learning models to estimate seed traits, e.g., protein, oil, sucrose, starch, ash, fiber, and yield. The MKSF was trained using PS and S2 image pairs from different growth stages and predicted the potential VNIR1 (705 nm), VNIR2 (740 nm), VNIR3 (783 nm), SWIR1 (1610 nm), and SWIR2 (2190 nm) bands from the PS images. Our results indicate that VNIR3 prediction performance was the highest followed by VNIR2, VNIR1, SWIR1, and SWIR2. Among the seed traits, sucrose yielded the highest predictive performance with RFR model. Finally, the feature importance analysis revealed the importance of MKSF-generated vegetation indices from fused images.

Protein research in millets: current status and way forward.

MAIN CONCLUSION: Millets' protein studies are lagging behind those of major cereals. Current status and future insights into the investigation of millet proteins are discussed. Millets are important small-seeded cereals majorly grown and consumed by people in Asia and Africa and are considered crops of future food security. Although millets possess excellent climate resilience and nutrient supplementation properties, their research advancements have been lagging behind major cereals. Although considerable genomic resources have been developed in recent years, research on millet proteins and proteomes is currently limited, highlighting a need for further investigation in this area. This review provides the current status of protein research in millets and provides insights to understand protein responses for climate resilience and nutrient supplementation in millets. The reference proteome data is available for sorghum, foxtail millet, and proso millet to date; other millets, such as pearl millet, finger millet, barnyard millet, kodo millet, tef, and browntop millet, do not have any reference proteome data. Many studies were reported on stress-responsive protein identification in foxtail millet, with most studies on the identification of proteins under drought-stress conditions. Pearl millet has a few reports on protein identification under drought and saline stress. Finger millet is the only other millet to have a report on stress-responsive (drought) protein identification in the leaf. For protein localization studies, foxtail millet has a few reports. Sorghum has the highest number of 40 experimentally proven crystal structures, and other millets have fewer or no experimentally proven structures. Further proteomics studies will help dissect the specific proteins involved in climate resilience and nutrient supplementation and aid in breeding better crops to conserve food security.

Redesigning and validation of fertilizer use in maize for variable plant densities in central rift valley and Jimma in Ethiopia.

Due to low adoption and sub-optimal fertilizer use and planting density recommendation in maize, redesigning and testing these technologies are required. The study was conducted to evaluate redesigned fertilizer use of maize in two pant densities (32,443 and 53,333 plants ha-1 in Central Rift Valley (CRV); 27724 and 62,000 plants ha-1 in Jimma) on farmers' fields in contrasting agro-ecologies of Ethiopia. The on-farm study was conducted in the 2017 and 2018 cropping seasons with 3 × 2 fertilizer and plant density, factors in both regions of Ethiopia. In redesigned fertilizer use, nutrients were estimated based on the target yield. In this study, 40.8, 0.0, and 12.2 kg ha-1 N, P, and K were estimated for the redesigned fertilizer use in CRV (50% of water-limited potential yield (Yw) = 3.1 t ha-1) whereas in Jimma (50% of Yw = 7.5 t ha-1) 149.8, 9, 130.6 kg ha-1 N, P and K were estimated to produce the 50% of Yw. Linear mixed modeling was used to assess the effect of fertilizer-plant density treatments on maize yield and nutrient use efficiency. The result revealed that the average estimated maize yield for WOF, FFU, and RDFU fertilizer treatments were 2.6, 3.6, and 4.5 t ha-1 under current plant density (32,443 plants ha-1) in CRV whereas the average yields of these treatments were 3.2, 4.5 and 4.5 t ha-1 respectively when maize was grown with redesigned plant density (53,333 plants ha-1) in the same location. The average maize yield with WOF, FFU, and RDFU were 3.0, 4.6, and 4.6 t ha-1 with 27,774 plants ha-1 plant density in Jimma whereas the average maize yields over the two seasons with the same treatments were 4.3, 6.0 and 8.0 t ha-1 respectively when the crop is planted with 62,000 plants ha-1 plant density. The RDFU and redesigned plant density resulted in significantly higher yield compared to their respective control CRV but RDFU significantly increased maize yield when it was planted at redesigned (62,000 plant ha-1) in Jimma. FFU and RDFU were economically viable and redesigned plant density was also a cheaper means of improving maize productivity, especially in the Jimma region. Soil organic carbon and N were closely related to the grain yield response of maize compared to other soil factors. In conclusion, this investigation gives an insight into the importance of redesigned fertilizer use and redesigned plant density for improving maize productivity and thereby narrowing the yield gaps of the crop in high maize potential regions in Ethiopia like Jimma.

Carrier-based delivery system of phytohormones in plants: stepping outside of the ordinary.

Climate change is increasing the stresses on crops, resulting in reduced productivity and further augmenting global food security issues. The dynamic climatic conditions are a severe threat to the sustainability of the ecosystems. The role of technology in enhancing agricultural produce with the minimum environmental impact is hence crucial. Active molecule/Plant growth regulators (PGRs) are molecules helping plants' growth, development, and tolerance to abiotic and biotic stresses. However, their degradation, leaching in surrounding soil and ground water, as well as the assessment of the correct dose of application etc., are some of the technical disadvantages faced. They can be resolved by encapsulation/loading of PGRs on polymer matrices. Micro/nanoencapsulation is a revolutionary tool to deliver bioactive compounds in an economically affordable and environmentally friendly way. Carrier-based smart delivery systems could be a better alternative to PGRs application in the agriculture field than conventional methods (e.g., spraying). The physiochemical properties and release kinetics of PGRs from the encapsulating system are being explored. Therefore, the present review emphasizes the current status of PGRs encapsulation approach and their potential benefits to plants. This review also addressed the mechanistic action of carrier-based delivery systems for release, which may aid in developing smart delivery systems with specific tailored properties in future research.

The Role of Satellites in the Evolution of Begomoviruses.

Begomoviruses have emerged as destructive pathogens of crops, particularly in the tropics and subtropics, causing enormous economic losses and threatening food security. Epidemics caused by begomoviruses have even spread in regions and crops that were previously free from these viruses. The most seriously affected crops include cassava; cotton; grain legumes; and cucurbitaceous, malvaceous, and solanaceous vegetables. Alphasatellites, betasatellites, and deltasatellites are associated with the diseases caused by begomoviruses, but begomovirus-betasatellite complexes have played significant roles in the evolution of begomoviruses, causing widespread epidemics in many economically important crops throughout the world. This article provides an overview of the evolution, distribution, and approaches used by betasatellites in the suppression of host plant defense responses and increasing disease severity.

Livestock predation, crop raiding, and community attitudes towards sustainable wildlife conservation in and around Mankira Forest, Southwest Ethiopia.

Crop raiding and livestock predation negatively impact the views of the local community towards wildlife conservation. Farmers across the African continent, especially those in rural regions, incur financial losses as a result of crop raiding and livestock depredation. The sustainability of the forest relies heavily on comprehending the essential connection between a harmonious park-people relationship and the coexistence of humans and wildlife. The primary aim of this study is to evaluate the predation of livestock, the raiding of crops, and the attitudes of the community towards wildlife in the Mankira Forest located in southwest Ethiopia. This particular area has been lacking in scientific research, making it crucial to conduct this assessment. The data were collected between November 2021 and September 2022 via a structured questionnaire. This study used a sample of 241 randomly selected respondents from the four villages, and responses were compared using chi-square tests. Pearson correlation was also used to test the relationship between the distance of farmland and the extent of crop raiding. The majority of the respondents (95%) reported the presence of crop raiding and livestock predation in the area. These losses were caused by the Papio anubis (39%), the Chlorocebus aethiops (24.1%), the Hystrix cristata (15.3%), the Canis aures (58.3%), and the Crocutacrocuta (29.5%). Maize stood out as the crop type most susceptible to crop raiders. Most of the respondents (56.7%) had a negative attitude towards wildlife conservation. There was a significant difference among age groups of respondents related to their attitude towards wildlife conservation (p < 0.05). The study highlights the need to address several gaps in understanding and managing human-wildlife conflict through research on predation, raiding, and community attitudes. Therefore, to fulfill the dual goals of community support and conservation of wildlife, rigorous management and planning are needed.

Genetic and Biotechnological Approaches to Improve Fruit Bioactive Content: A Focus on Eggplant and Tomato Anthocyanins.

Anthocyanins are a large group of water-soluble flavonoid pigments. These specialized metabolites are ubiquitous in the plant kingdom and play an essential role not only in plant reproduction and dispersal but also in responses to biotic and abiotic stresses. Anthocyanins are recognized as important health-promoting and chronic-disease-preventing components in the human diet. Therefore, interest in developing food crops with improved levels and compositions of these important nutraceuticals is growing. This review focuses on work conducted to elucidate the genetic control of the anthocyanin pathway and modulate anthocyanin content in eggplant (Solanum melongena L.) and tomato (Solanum lycopersicum L.), two solanaceous fruit vegetables of worldwide relevance. While anthocyanin levels in eggplant fruit have always been an important quality trait, anthocyanin-based, purple-fruited tomato cultivars are currently a novelty. As detailed in this review, this difference in the anthocyanin content of the cultivated germplasm has largely influenced genetic studies as well as breeding and transgenic approaches to improve the anthocyanin content/profile of these two important solanaceous crops. The information provided should be of help to researchers and breeders in devising strategies to address the increasing consumer demand for nutraceutical foods.

Landscape features support natural pest control and farm income when pesticide application is reduced.

Future trajectories of agricultural productivity need to incorporate environmental targets, including the reduction of pesticides use. Landscape features supporting natural pest control (LF-NPC) offer a nature-based solution that can serve as a partial substitute for synthetic pesticides, thereby supporting future productivity levels. Here, we introduce a novel approach to quantify the contribution of LF-NPC to agricultural yields and its associated economic value to crop production in a broad-scale context. Using the European Union as case study, we combine granular farm-level data, a spatially explicit map of LF-NPC potential, and a regional agro-economic supply and market model. The results reveal that farms located in areas characterized by higher LF-NPC potential experience lower productivity losses in a context of reduced synthetic pesticides use. Our analysis suggests that LF-NPC reduces yield gaps on average by four percentage points, and increases income by a similar magnitude. These results highlight the significance of LF-NPC for agricultural production and income, and provide a valuable reference point for farmers and policymakers aiming to successfully invest in landscape features to achieve pesticides reduction targets.

Belowground plant allocation regulates rice methane emissions from degraded peat soils.

Carbon-rich peat soils have been drained and used extensively for agriculture throughout human history, leading to significant losses of their soil carbon. One solution for rewetting degraded peat is wet crop cultivation. Crops such as rice, which can grow in water-saturated conditions, could enable agricultural production to be maintained whilst reducing CO2 and N2O emissions from peat. However, wet rice cultivation can release considerable methane (CH4). Water table and soil management strategies may enhance rice yield and minimize CH4 emissions, but they also influence plant biomass allocation strategies. It remains unclear how water and soil management influences rice allocation strategies and how changing plant allocation and associated traits, particularly belowground, influence CH4-related processes. We examined belowground biomass (BGB), aboveground biomass (AGB), belowground:aboveground ratio (BGB:ABG), and a range of root traits (root length, root diameter, root volume, root area, and specific root length) under different soil and water treatments; and evaluated plant trait linkages to CH4. Rice (Oryza sativa L.) was grown for six months in field mesocosms under high (saturated) or low water table treatments, and in either degraded peat soil or degraded peat covered with mineral soil. We found that BGB and BGB:AGB were lowest in water saturated conditions where mineral soil had been added to the peat, and highest in low-water table peat soils. Furthermore, CH4 and BGB were positively related, with BGB explaining 60% of the variation in CH4 but only under low water table conditions. Our results suggest that a mix of low water table and mineral soil addition could minimize belowground plant allocation in rice, which could further lower CH4 likely because root-derived carbon is a key substrate for methanogenesis. Minimizing root allocation, in conjunction with water and soil management, could be explored as a strategy for lowering CH4 emissions from wet rice cultivation in degraded peatlands.

Novel Bacillus and Prestia isolates from Dwarf century plant enhance crop yield and salinity tolerance.

Soil salinity is a major environmental stressor impacting global food production. Staple crops like wheat experience significant yield losses in saline environments. Bioprospecting for beneficial microbes associated with stress-resistant plants offers a promising strategy for sustainable agriculture. We isolated two novel endophytic bacteria, Bacillus cereus (ADJ1) and Priestia aryabhattai (ADJ6), from Agave desmettiana Jacobi. Both strains displayed potent plant growth-promoting (PGP) traits, such as producing high amounts of indole-3-acetic acid (9.46, 10.00 µgml-1), ammonia (64.67, 108.97 µmol ml-1), zinc solubilization (Index of 3.33, 4.22, respectively), ACC deaminase production and biofilm formation. ADJ6 additionally showed inorganic phosphate solubilization (PSI of 2.77), atmospheric nitrogen fixation, and hydrogen cyanide production. Wheat seeds primed with these endophytes exhibited enhanced germination, improved growth profiles, and significantly increased yields in field trials. Notably, both ADJ1 and ADJ6 tolerated high salinity (up to 1.03 M) and significantly improved wheat germination and seedling growth under saline stress, acting both independently and synergistically. This study reveals promising stress-tolerance traits within endophytic bacteria from A. desmettiana. Exploiting such under-explored plant microbiomes offers a sustainable approach to developing salt-tolerant crops, mitigating the impact of climate change-induced salinization on global food security.

Multi-trait index: selection and recommendation of superior black bean genotypes as new improved varieties.

Common bean provides diet rich in vitamins, fiber, minerals, and protein, which could contribute into food security of needy populations in many countries. Developing genotypes that associate favorable agronomic and grain quality traits in the common bean crop could increase the chances of adopting new cultivars black bean. In this context, the present study aimed at selection of superior black bean lines using multi-variate indexes, Smith-Hazel-index, and genotype by yield*trait biplot analysis. These trials were conducted in Campos dos Goytacazes - RJ, in 2020 and 2021. The experimental design used was randomized blocks, with 28 treatments and three replications. The experimental unit consisted of four rows 4.0 m long, spaced at 0.50 m apart, with a sowing density of 15 seeds per meter. The two central rows were used for the evaluations. The selection of superior genotypes was conducted using the multiple trait stability index (MTSI), multi-trait genotype-ideotype distance index (MGIDI), multi-trait index based on factor analysis and genotype-ideotype distance (FAI-BLUP), Smith-Hazel index, and Genotype by Yield*Trait Biplot (GYT). The multivariate indexes efficiently selected the best black bean genotypes, presenting desirable selection gains for most traits. The use of multivariate indexes and GYT enable the selection of early genotypes with higher grain yields. These lines G9, G13, G17, G23, and G27 were selected based on their performance for multiple traits closest to the ideotype and could be recommended as new varieties.

Adoption of CRISPR-Cas for crop production: present status and future prospects.

Background: Global food systems in recent years have been impacted by some harsh environmental challenges and excessive anthropogenic activities. The increasing levels of both biotic and abiotic stressors have led to a decline in food production, safety, and quality. This has also contributed to a low crop production rate and difficulty in meeting the requirements of the ever-growing population. Several biotic stresses have developed above natural resistance in crops coupled with alarming contamination rates. In particular, the multiple antibiotic resistance in bacteria and some other plant pathogens has been a hot topic over recent years since the food system is often exposed to contamination at each of the farm-to-fork stages. Therefore, a system that prioritizes the safety, quality, and availability of foods is needed to meet the health and dietary preferences of everyone at every time. Methods: This review collected scattered information on food systems and proposes methods for plant disease management. Multiple databases were searched for relevant specialized literature in the field. Particular attention was placed on the genetic methods with special interest in the potentials of the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and Cas (CRISPR associated) proteins technology in food systems and security. Results: The review reveals the approaches that have been developed to salvage the problem of food insecurity in an attempt to achieve sustainable agriculture. On crop plants, some systems tend towards either enhancing the systemic resistance or engineering resistant varieties against known pathogens. The CRISPR-Cas technology has become a popular tool for engineering desired genes in living organisms. This review discusses its impact and why it should be considered in the sustainable management, availability, and quality of food systems. Some important roles of CRISPR-Cas have been established concerning conventional and earlier genome editing methods for simultaneous modification of different agronomic traits in crops. Conclusion: Despite the controversies over the safety of the CRISPR-Cas system, its importance has been evident in the engineering of disease- and drought-resistant crop varieties, the improvement of crop yield, and enhancement of food quality.

Force and power requirement for development of cumin harvester: a dynamic approach.

An experimental setup was developed for simulating the field conditions to determine the force and power required for cutting cumin crops in dynamic conditions. The effect of cutter bar speeds, forward speeds, and blade type on cutting force and power requirement for cutting cumin were also studied. Experiments were carried out at three levels: cutter bar speeds, forward speeds, and blade type. The results showed that all the factors significantly affected cutting force. The cutting force followed a decreasing trend with the increase in cutter bar speed. Whereas it followed an increasing trend with the increase in forward speed. The maximum cutting force for all three blades was observed at a cutter bar speed of 2.00 strokes.s-1 and forward speed of 0.46 m.s-1. The idle power and actual power required for cutting the cumin crop were also determined based on the cutting force. The results obtained were validated by the power drawn from the power source while operating the cutter bar blades. The R2 values for Blade-B1, Blade-B2, and Blade-B3 were 0.90, 0.82, and 0.88, respectively. The cutting force was primarily affected by the cutter bar speed, resulting in PCR values of 74.20%, 82.32%, and 81.75% for Blade-B1, Blade-B2, and Blade-B3, respectively, followed by the forward speed, which also had an impact on PCR values of 16.60%, 15.27%, and 18.25% for Blade-B1, Blade-B2, and Blade-B3, respectively. The cutting force for Blade-B1, Blade-B2, and Blade-B3 varied from 15.96 to 58.97 N, 21.08 to 76.64 N, and 30.22 to 85.31, respectively, for the selected range of cutter bar speed and forward speed. Blade-B1 had 18 and 30% less power consumption than Blade-B2 and Blade-B3, respectively.

Spatiotemporal evolution characteristics and influencing factors of the crop water use efficiency in watersheds based on the water footprint.

Climate change has exacerbated the contradiction between water scarcity and sustainable agricultural development. Assessing the crop water use efficiency and its influencing factors could provide a decision-making reference to realize Sustainable Development Goal 2. By analyzing the temporal and spatial evolution characteristics of the crop water footprint, the blue water footprint, green water footprint, and grey water footprint were introduced into the super efficiency slack-based measure model to evaluate the crop water use efficiency in basins. The influence of the driving factors was examined by using the geographic detector model. The situation in the provinces along the Yellow River Basin from 2005 to 2020 was used as a verification case. The results indicated that (1) during the study period, crop water use in the basin was mainly based on the blue water footprint, accounting for approximately 55% of the total water footprint, the grey water footprint, accounting for approximately 30% of the total water footprint, and the green water footprint, accounting for the lowest proportion, at approximately 15%. (2) The crop water use efficiency exhibited a spatial distribution pattern of high values in the east and low values in the west, with obvious upstream provinces disposable income of rural residents (0.71) > population urbanization rate (0.65) > degree of agricultural mechanization (0.63) > agricultural disaster rate (0.61). Furthermore, the interaction effects between the driving factors were greater than the effects of the single factors. The study provides an important reference for understanding the changes, driving mechanisms, and impacts of crop water use efficiency in basin areas. It promotes green agricultural transformation and development to address climate change and alleviate the pressure on water resources.

How plant composition in margins influences the assemblage of pests and predators and its effect on biocontrol in melon fields.

Many agricultural landscapes offer few resources for maintaining natural enemy populations and floral plantings have frequently been adopted to enhance biological pest control in crops. However, restored margins may harbour both pests and natural enemies. The aim was to compare the abundance of pests and natural enemies in three types of margins (unmanaged, sown herbaceous floral strips and shrubby hedgerows) as well as in adjacent melon fields. Besides, yield was compared among melon fields as way of testing the effect of the type of margin on biocontrol. The research was carried out during 2 years in twelve melon fields from four different locations in southern Spain. Arthropods were sampled periodically in margins and melon fields by visual inspections and Berlese extraction. Hedgerow and floral strips hosted higher numbers of both pests and predators than unmanaged margins. Besides, hedgerows had a similar or higher number of natural enemies than floral strips but lower number of pests. In just a few occasions, the type of margin had a significant effect on the abundance of pests and natural enemies in melon fields, but rarely there was consistency between the two growing seasons. No differences were found in yield. We hypothesised that the lack of association in the abundances of pests and natural enemies between margins and melon fields could be attributed to the overriding effects of the landscape and/or the internal population dynamics of arthropods in melon fields. Overall, shrubby hedgerows are more recommended than herbaceous floral strips.

Unravelling the impact of environmental factors in shaping plant microbiomes.

This article emphasizes the significant role of environmental factors in shaping the plant microbiome, highlighting how bacterial and fungal communities influence plant responses to water stress, and how environmental factors shape fungal communities in crops. Furthermore, recent studies describe how different genotypes and levels of water stress affect the composition of bacterial communities associated with quinoa plants, as well as the relationship between environmental factors and the structure of fungal communities in apple fruit. These findings underscore the importance of understanding plant microbiome dynamics in developing effective crop protection strategies and improving agricultural sustainability with the objective of advance towards a microbiome-based strategy which allows us to improve crop tolerance to abiotic stresses.

Novel artificial intelligence assisted Landsat-8 imagery analysis for mango orchard detection and area mapping.

The mango fruit plays a crucial role in providing essential nutrients to the human body and Pakistani mangoes are highly coveted worldwide. The escalating demand for agricultural products necessitates enhanced methods for monitoring and managing agricultural resources. Traditional field surveys are labour-intensive and time-consuming whereas remote sensing offers a comprehensive and efficient alternative. The field of remote sensing has witnessed substantial growth over time with satellite technology proving instrumental in monitoring crops on a large scale throughout their growth stages. In this study, we utilize novel data collected from a mango farm employing Landsat-8 satellite imagery and machine learning to detect mango orchards. We collected a total of 2,150 mango tree samples from a farm over six months in the province of Punjab, Pakistan. Then, we analyzed each sample using seven multispectral bands. The Landsat-8 framework provides high-resolution land surface imagery for detecting mango orchards. This research relies on independent data, offering an advantage for training more advanced machine learning models and yielding reliable findings with high accuracy. Our proposed optimized CART approach outperformed existing methods, achieving a remarkable 99% accuracy score while the k-Fold validation score also reached 99%. This research paves the way for advancements in agricultural remote sensing, offering potential benefits for crop management yield estimation and the broader field of precision agriculture.