A review to frame the utilization of Eastern black walnut (Juglans nigra L.) cultivars in alley cropping systems

Agroforestry adoptition is gaining considerable traction in the temperate US with growing popularity and government incentives (e.g., the Partnerships for Climate-Smart Commodities Project) for systems with greenhouse gas mitigation potential. The identification of complementary species combinations will accelerate the expansion of temperate agroforestry. Since the mid-19th century, European timber plantations have taken advantage of the late-leafing habit of walnut (Juglans spp.) to grow a spring grain crop between the tree rows. Such alley cropping systems increase land-use efficiency and provide extensive environmental benefits. A parallel but underutilized opportunity in North American involves incorporating eastern black walnut (Juglans nigra L.) cultivars into alley cropping systems (ACS). Eastern black walnut, henceforth referred to as black walnut, is native to North America and exhibits architectural and phenological characters for reduced competition with winter cereal crops grown in alleys. Black walnut also produces nutritious nuts, and cultivars with improved kernel percentage and mass offer potential to cultivate the species as a domesticated orchard crop, as opposed to just the high-quality timber for which it is well-known. However, field observations suggest significant variation in tree architecture and phenology amongst cultivars, which is likely to influence complementarity with winter grains. Comprehensive characterization of trait genetic diversity is needed to best leverage germplasm into productive systems. Here, we review literature related to implementing ACS with consideration of cultivar-dependent traits that may reduce interspecific competition. While the focus is directed toward black walnut, broad characterization of other underutilized fruit/nut species will allow for robust diversification of ACS.


Large-scale assessment of date palm plantations based on UAV remote sensing and multiscale vision transformer

Timely and efficient mapping of date palm plantations through unmanned aerial vehicle (UAV) remote sensing is critical for continuous observation, health and risk evaluation, pest management, resource optimization, and ensuring the long-term sustainability of the dates industry. This study presents an efficient and cost-effective transformer-based approach to identify, countify, monitor, and evaluate the overall well-being of palm trees using extensive UAV imagery. The suggested approach integrates an improved multiscale vision transformer, feature pyramid network, Mask R–CNN, and improved slicing-aided hyper inference for practical large-scale assessments. This combination enabled the extraction of multiscale features, capturing long-range dependencies in the data and boosting the model's generalizability. The proposed architecture outperformed several CNN-based architectures (including Mask R–CNN, Cascade Mask R–CNN, Point-based Rendering, and You Only Look At CoefficientTs), achieving F-scores of 94.33% and 94.2% for date palm tree detection and segmentation, respectively. The transformer-based architecture was optimized using transfer learning to differentiate between healthy and unhealthy date palm trees, particularly those with severe infestations. The potential generic condition of date palm trees was predicted with an F-score of 88.4%. Further advancements in this field could pave the way for a proactive strategy, enabling timely detection, which would aid in pest management and support the sustainable growth of the dates sector.


Alternative fertilization practices lead to improvements in yield-scaled global warming potential in almond orchards

This study investigates the impact of alternative fertilization practices on the yield-scaled global warming potential (YS-GWP) in almond orchards. Almond production is a contributor to greenhouse gas emissions, primarily due to nitrogen-based mineral fertilizers. This research aims to identify strategies that reduce the environmental footprint of almond cultivation while maintaining yield. Field experiments were conducted in an almond orchard using three alternative fertigation practices: Advance Grower Practice (AGP), Pump and Fertilize (P&F), and High Frequency Low Concentration (HFLC). AGP is the current practice used by producers to meet annual N demand for almond tree growth; P&F is a reduction in applied N rate in response to measured N concentrations in the groundwater so that the added N and groundwater N reach the same total N applied; HFLC is a practice of applying smaller N rates per individual event. HFLC uses a greater number of fertigation events to reach similar total annual N load as other treatments. Cumulative N2O and CH4 emissions were used to determine GWP by converting the emissions to carbon dioxide equivalents (CO2eq) within a 100-year horizon. Nitrous oxide emissions were multiplied by a radiative forcing potential CO2eq of 298 and CH4 by 25 (UNFCCC, 2007). The results revealed that both P&F and HFLC reduced the YS-GWP compared to AGP. HFLC demonstrated 52–78% decrease in GWP per unit of almond yield compared to AGP, while P&F showed 48–58% decrease over AGP. These reductions were attributed to the reduced nitrous oxide emissions associated with P&F and HFLC. Further, P&F and HFLC tended to have higher N use efficiency than AGP. We demonstrate that adopting alternative fertilization practices can effectively mitigate the environmental footprint of almond orchards while maintaining crop yields. These practices offer viable options for almond growers to reduce greenhouse gas emissions, enhance sustainability, and contribute to climate change mitigation.


Pickering emulsions stabilized by cellulose nanocrystals extracted from hazelnut shells: Production and stability under different harsh conditions

Cellulose nanocrystals (CNCs) are biodegradable particles that have emerged as promising stabilizers for Pickering emulsions. This study investigated the effectiveness of CNCs in forming the Pickering emulsion from hazelnut shells (HS), an agricultural waste. Following the alkaline and bleaching treatments applied to HS, CNCs were obtained from treated hazelnut shell with acid hydrolysis. The physicochemical characteristics of CNCs were investigated using dynamic light scattering, XRD, FTIR, SEM, and TEM. A high crystalline (69.6 %) CNCs with a spherical shape were obtained. Contact angle and interfacial tension tests were conducted and showed that CNCs had amphiphilic nature. Pickering emulsions were investigated for their size, zeta potential, and stability under varying CNC concentrations. The results showed that when CNCs concentration increased from 0.5 to 2.0 wt%, droplet diameter decreased approximately 1.8 times and zeta potential increased. Creaming was not observed during 28 days of storage in a concentration of 2.0 wt% CNCs. The CNC stabilized emulsions exhibited high stability within a range of pH, temperatures, and salt concentrations. This study demonstrated that CNCs extracted from HS as environmentally friendly and cost-effective materials, could serve as a new stabilizer for Pickering emulsions especially for high temperature and low pH sensitive products such as mayonnaise.

Nut bush pesticide limits: urgent need for a comprehensive strategy to address current and emerging insect pests and insecticide options in the Australian macadamia industry

In Australia, macadamia orchards are attacked by four main insect pest groups. Management and control of three of these key pests currently relies on broad-spectrum insecticides whose long-term future is questionable. Of the 23 insecticides registered for use in macadamia in Australia, 19 face issues affecting their availability and 12 are presently not approved in the EU, the USA or Canada. These international markets may refuse produce that does not adhere to their own insecticide use standards, hence Australian produce may be excluded from market access. Many of the potential replacement integrated pest management methods of pest control are generally considered less effective by the industry and have not been adopted. There are 17 insect pest groups identified by the industry, any of which have potential to become major problems if broad-spectrum insecticide options become unavailable. Thirteen pest groups need urgent attention as they are at risk of losing current effective control methods, and no replacement solutions have yet been developed. The lag period for research and development to identify new chemical and biological control solutions means there is now an urgent need for the macadamia industry to craft a strategy for sustainable pest management for each pest. Critically, this industry strategy needs to address the vulnerabilities identified in this paper, identify potential solutions for any cases of market failure and consider funding mechanisms to address these gaps. On economic and sustainability grounds, potential biological control options should be explored, especially in cases where insecticide control options are vulnerable.

Fe2O3/carbon derived from peanut shell hybrid as an advanced anode for high performance lithium ion batteries

Carbon materials derived from biomass behave sustainability, easy availability, low cost and environmentally benign. And Fe2O3 are considered as promising anodes for high-performance Li-ion batteries (LIBs) because of their rich electrochemical properties, higher theoretical capacity (1007 mAh g−1), non-toxicity, high corrosion resistance and safety. However, the high irreversible capacity loss and poor cycling stability of Fe2O3 hinders its commercial applications in LIBs. In this work, we have developed a Fe2O3@C derived from peanut shell composite by two-step hydrothermal method and low-temperature calcination with the assistance of Fe(NO3)3. As an anode for LIBs, the Fe2O3@C composite an excellent electrochemical performance in term of the specific capacity of 1000.8 mAh g−1 at 200 mA g−1 after 100 cycles, and high rate capability of 573.5 mAh g−1 even at 1 A g−1 after 200 cycles. This enhancement could be attributed to the porous carbon matrix combined with Fe2O3 nanoparticles which could increase contact area between electrolyte and active materials, improve conductivity, and accommodate the volume variations via additional void space during cycling. This work may be provide a new approach to improve anode materials using carbon derived-from biomass with larger reversible capacity and long cycle life in LIBs.


Effect of drought stress and subsequent re-watering on the physiology and nutrition of Pistacia vera and Pistacia atlantica

Arid and semi-arid regions are characterised by extreme conditions including drought stress and salinity. These factors profoundly affect the agricultural sector. The objective of this work is to study the effect of drought and re-watering on leaf gas exchange, chlorophyll fluorescence and mineral nutrition in Pistacia vera and Pistacia atlantica. Water stress was applied to individuals of P. vera and P. atlantica for 23days, followed by rehydration for 7days. The results showed a clear reduction in water relations, leaf gas exchange and chlorophyll content in P. vera. Compared to P. vera, P. atlantica maintained less affected water status, total chlorophyll content, leaf gas exchange and chlorophyll fluorescence, stable Zn and Fe proportion, and even elevated K and Cu. The changes in the chlorophyll fluorescence parameter were manifested particularly at the maximal fluorescence (Fm). In contrast, no change was recorded at the minimal fluorescence (F0). After re-hydration, although water status was fully recovered in both species, stomatal conductance (gs), net photosynthesis (A) and transpiration rate (E) remain with lower values than the well-watered seedlings. P. atlantica was better adapted to drought stress than P. vera.



Effect of deficit irrigation on physiological, morphological and fruit quality traits of six walnut tree cultivars in the inland area of Central Asia

Persian walnut, a drought-sensitive tree, exhibits significant genetic variation in functional traits in response to drought—a domain that remains largely unexplored. This study examines the impact of two distinct irrigation regimes—conventional irrigation (CI) and deficit irrigation (DI)—on physiological, morphological, and fruit quality traits across six walnut tree cultivars in a scion orchard during the summer drought period. Our findings revealed significant effects of irrigation treatments on soil water content, with notable drought stress observed in Win 185, Xinjufeng, and Zha71 under DI. Win 185 and Xinfeng, subjected to DI, exhibited diminished photosynthetic rates (A) and stomatal conductance (gs), whereas Win 185, Xinjufeng, Xinxin 2, and Zha71 displayed heightened instantaneous water use efficiency (WUEi) under DI. The maximum photochemical efficiency of photosystem II (Fv/Fm) and chlorophyll index were also affected in Win 185, Xinfeng, Xinjufeng, Xinxin 2 and Zha71 subjected to the DI treatment. Identified as primary drought response strategies, stomatal regulation, osmotic adjustment, and morphological adaptations varied uniquely among cultivars, potentially mitigating the adverse effects of drought on fruit quality. Notably, DI induced minor changes in fruit quality for Win 185, Xinlu, and Zha71, resulting in varying reductions in fruit diameter and weight. This suggests the possibility of achieving reduced water consumption while preserving fruit quality in specific cultivars. Phenotypic plasticity was evident across all traits; however, its response to drought exhibited cultivar-specific variations. A nuanced understanding of phenotypic plasticity's role in fruit quality is essential for optimizing deficit irrigation practices across diverse walnut cultivars.




Yield prediction in a peanut breeding program using remote sensing data and machine learning algorithms

Peanut is a critical food crop worldwide, and the development of high-throughput phenotyping techniques is essential for enhancing the crop’s genetic gain rate. Given the obvious challenges of directly estimating peanut yields through remote sensing, an approach that utilizes above-ground phenotypes to estimate underground yield is necessary. To that end, this study leveraged unmanned aerial vehicles (UAVs) for high-throughput phenotyping of surface traits in peanut. Using a diverse set of peanut germplasm planted in 2021 and 2022, UAV flight missions were repeatedly conducted to capture image data that were used to construct high-resolution multitemporal sigmoidal growth curves based on apparent characteristics, such as canopy cover and canopy height. Latent phenotypes extracted from these growth curves and their first derivatives informed the development of advanced machine learning models, specifically random forest and eXtreme Gradient Boosting (XGBoost), to estimate yield in the peanut plots. The random forest model exhibited exceptional predictive accuracy (R2 = 0.93), while XGBoost was also reasonably effective (R2 = 0.88). When using confusion matrices to evaluate the classification abilities of each model, the two models proved valuable in a breeding pipeline, particularly for filtering out underperforming genotypes. In addition, the random forest model excelled in identifying top-performing material while minimizing Type I and Type II errors. Overall, these findings underscore the potential of machine learning models, especially random forests and XGBoost, in predicting peanut yield and improving the efficiency of peanut breeding programs.




Walnut By-Products and Elderberry Extracts – Sustainable Alternatives for Human and Plant Health

A current alternative for sustainable development through green chemistry is the replacement of synthetic compounds with natural ones through the superior capitalization of natural resources, with numerous applications in different fields. The benefits of walnuts (Juglans regia L.) and elderberries (Sambucus nigra L.) have been known since ancient times, due to the presence of phytochemicals such as flavonoids, polyphenols, carotenoids, alkaloids, nitrogen-containing compounds, tannins, steroids, anthocyanins, etc. These active compounds have multiple biological activities for human health, including benefits that are antibacterial, antioxidant, anti-inflammatory, antidiabetic, hepatoprotective, antihypertensive, neuroprotective, etc. Like other medicinal plants, the walnut and the elderberry possess important phytosanitary properties (antibacterial, antifungal, and insecticidal) and their extracts can also be used as environmentally safe biopesticides, with the result that they constitute a viable and cheap alternative to environmentally harmful synthetic products. During recent years, walnut by-products and elderberries have attracted the attention of researchers, and investigations have focused on the species' valuable constituents and active properties. Comparing the information from the literature regarding the phytochemical profile and biological activities, it is highlighted that, apart from the predominant specific compounds, the walnut and the elderberry have common bioactive compounds, which come from six classes (phenols and derivatives, flavonoids, hydroxycinnamic acids, tannins, triterpenoids, and phytosteroids), and act on the same microorganisms. From this perspective, the aim of this review is to provide an overview of the bioactive compounds present in the different constitutive parts of walnut by-products and elderberries, which present a specific or common activity related to human health and the protection of agricultural crops in the context of sustainable development.