Adjuvants are agrochemicals or natural substances, commonly mixed with pesticides to increase their efficacy or reduce off-target movement by modifying the physical properties of the spray solution, such as surface tension, droplet size, and spreadability, which ultimately improve pesticide adhesion and coverage on target surfaces. Adjuvant use across Europe remains less widespread compared to regions like the USA, where adjuvants are often recommended or required with certain herbicide applications. This paper highlights the potential benefits of incorporating adjuvants with herbicides in weed control, particularly as a strategy to reduce overall herbicide use. Findings from dose-response research on available adjuvants suggest they may enable the application of lower herbicide rates than typically recommended, without sacrificing effectiveness, thereby contributing to the goal of reducing herbicide use by 50% by 2030 in Europe. Furthermore, literature findings indicate that adjuvants significantly improve weed control by enhancing the performance of active ingredients, with efficacy increases of up to 50% compared to using herbicides alone. The integration of adjuvants into herbicide tank mixtures offers considerable promise, especially for managing herbicide-resistant weeds and achieving effective weed control.

Modeling the intricate interactions between fruit trees, their environments, soils, and economic factors continues to be a significant challenge in agricultural research globally, requiring a multidisciplinary approach. Despite advances in agricultural technology and algorithms, significant knowledge gaps persist in understanding and modeling these interactions. This review explores basic concepts related to modeling for tropical fruit production. It explains modeling development from sensor technologies, image analysis, databases, and algorithms for decision support systems while considering climate changes or edaphoclimatic limitations. We report the current fruit modeling tendencies showing a significant increase in publications on these topics starting in 2021, driven by the need for sustainable solutions and access to large agricultural databases. This study emphasizes inherent challenges in tropical fruit modeling, such as fruit tree cycles, costly and time-consuming experimentation, and the lack of standardized data. These limitations are evident in tropical fruit, where few models have been reported or validated for cocoa, avocado, durian, dragonfruit, banana, mango, or passion fruit. This study analyzes the classification of the algorithms related to tropical fruit into three main categories: supervised, unsupervised, and reinforcement learning, each with specific applications in agricultural management optimization. Crop classification and yield prediction use supervised models like neural networks and decision trees. Unsupervised models, like K-Means clustering, allow pattern identification without prior labels, which is useful for area segmentation and pest detection. Automation of irrigation and fertilization systems employs reinforcement learning algorithms to maximize efficiency. This multidisciplinary review discusses recent approaches to 1) Modeling Soil health and plant-soil interaction, 2) Yield prediction in tropical fruit orchards, 3) Integrating meteorological models for enhanced tropical fruit production, and 4) Economics of tropical fruit business through modeling. Furthermore, this review illustrates the complexity and multidisciplinary research on models for tropical fruit and platforms using agricultural models. Further opportunities to advance fruit modeling frameworks are indicated, requiring technical knowledge about the fruit crop requirements with user-friendly platforms to collect and access fruit tree data and site-specific agroecological conditions.

Unmanned aerial vehicles (UAVs) represent a cutting-edge technology that holds the promise of revolutionizing the conventional tasks carried out in the realm of agriculture. On a global scale, UAVs are gaining prominence for pesticide applications, particularly with a focus on utilizing low spray volumes. Nevertheless, there remains a notable gap in research concerning the impacts of employing low spray volumes on herbicide efficacy. Hence, multi-location field studies were conducted at Agricultural Research Station, Bhavanisagar and Wetland Station, Coimbatore, Tamil Nadu, India in 2022 to evaluate the impact of different spray volumes using UAV and Knapsack Manual Sprayer (KMS) on droplet deposition, droplet density, and weed control efficacy. The treatments included UAV sprays at 30 and 45 L ha-1, as well as KMS at 500 L ha-1, with a weedy check as a control. Bispyribac-sodium 10% SC was applied at a rate of 35 g a.i ha-1 during the 2-to 3-leaf stage of the crops. The results revealed that droplet deposition, area coverage, and volume median diameter were affected by sprayer type (UAV and KMS). However, the two spray volumes tested using the UAV method provided similar droplet parameters. The KMS system at 500 L ha-1 exhibited the highest droplet deposition, while the UAV system achieved better droplet distribution at a spray volume of 30 L ha-1. Remarkably, the UAV system at 30 L ha-1 demonstrated effective weed control, which was statistically comparable to the KMS system at 500 L ha-1. These findings emphasize that the UAV spraying system with a spray volume of 30 L ha-1, delivering effective weed control while utilizing less carrier volume compared to the manual knapsack spraying method. Thus, the UAV spray system has great potential as a viable alternative to manual knapsack spraying for herbicide application in direct-seeded rice.

Crop residues colonized saprophytically by necrotrophic plant pathogens are an important primary inoculum source for epidemics of foliar diseases. Residues of crops, weeds, and litter were systematically sampled in a complex crop rotation experiment. Concentrations of DNA of major pathogens of the grown crops, Alternaria solani in potato and Cercospora beticola, Ramularia beticola, and Stemphylium beticola in sugar beet, were quantified in the residues using newly developed qPCR assays. Repeated field trials gave additional insights into the dynamics of A. solani in potato foliage residues for 2 years. The overall results demonstrate that the A. solani and C. beticola colonized crop residues of their host crops initially after harvest at high densities whereas R. beticola and S. beticola were almost absent in the field. Within several months, amounts of available host residues decreased substantially and concentrations of pathogens in the remaining host residues decreased steeply. Alternative substrates, residues of non-host crops including cover crops and weeds, were colonized saprophytically by the necrotrophic pathogens A. solani and C. beticola. It can be concluded that residues of non-hosts can potentially serve as an important bridge for pathogen populations during host-free cropping seasons in crop rotation systems. These findings contribute to the development of rational crop residue management strategies aiming at disease prevention by lowering the inoculum potential in crop rotation systems.

The soil microbiome plays a pivotal role in the functioning and resilience of agricultural ecosystems, contributing to critical processes such as organic matter decomposition, nutrient cycling, and plant growth promotion. However, the soil microbiome is constantly challenged by various environmental stresses, including drought, heavy metal contamination, salinity, and climate change, which can significantly disrupt the delicate balance of the soil ecosystem. In this context, the application of silicon (Si) has emerged as a promising strategy to mitigate the adverse effects of these environmental stresses on the soil microbiome. This review paper synthesizes the current understanding of the impacts of environmental stresses on the soil microbiome and explores the potential of Si as a mitigating agent in enhancing the resilience of the soil microbial community. Silicon can enhance the resilience of the soil microbiome through several mechanisms, such as increasing soil pH, improving nutrient and water availability and uptake, altering root exudation patterns and plant physiology, and directly stimulating the abundance, diversity, and functional potential of key microbial groups. By enhancing the resilience of the soil microbiome, Si application can help maintain the critical ecosystem services provided by soil microorganisms, ultimately contributing to the sustainability and productivity of agricultural systems. The review also highlights future research aspects, including elucidating the precise mechanisms of Si-microbiome interactions, evaluating the long-term effects of Si on soil microbiome resilience, optimizing Si application strategies for specific crop-soil systems, integrating Si management with other sustainable soil practices, and assessing the impacts of Si on soil microbiome-mediated ecosystem services.

IntroductionCover crop services depend on biomass production and species composition of the cover crop stand. In this study, we investigated the interactions in shoot biomass of dual cover crop mixtures and their competitiveness to suppress weeds before winter under different growing conditions.MethodsA field experiment was performed on sandy loam soil in Triesdorf, Germany, for two consecutive years. The cover crop species white mustard (Sinapis alba L.), oil radish (Raphanus sativus var. oleiformis L.), phacelia (Phacelia tanacetifolia J.), Egyptian clover (Trifolium alexandrinum L.), common vetch (Vicia sativa L.), field pea (Pisum sativum L.), and field bean (Vicia faba L.) were grown in pure stands or dual mixtures. Cover crops were sown in August, and shoot biomass was harvested at the end of the vegetation period. Cover crop shoot biomass was dried, and the share of each species and the sown test weed (Brassica napus L.) were determined.ResultsThe share of shoot biomass of a cover crop species in dual-species mixtures was closely related to its shoot biomass in its pure stand. In both years, mustard and phacelia showed similar interactions in shoot biomass production when growing with a second species. Regarding competitiveness against weeds, cruciferous species outperformed other cover crop species and could suppress weeds even if they were mixed with a less competitive partner. Weed suppression of mixtures with phacelia depended on the second component in the mixture and was more effective in a dry season. Legume species, especially Egyptian clover and common vetch could not suppress weeds in a pure stand.DiscussionOur results show that species with high weed suppression potential as single stands retain this ability in dual cover crop mixtures, regardless of the suppression potential of the second species that completes the mixture.

IntroductionImproving photosynthetic use efficiency in dryland agroecosystems to sustain high agricultural yields is a key responsibility for ensuring food security.MethodsThis study was conducted in the regions on the semiarid Loess Plateau of China during 2018–2020. Dryland maize of Xianyu 335 comprised four modes: basic yield input (CK, plastic film mulching, 37500 plant.ha-1 of plant density and unfertilized), farmer input (FP, plastic film mulching, 45000 plant.ha-1 of plant density and inorganic nitrogen(N) and phosphate(P) fertilizer were 150kg.ha-1 and 90kg.ha-1), high yield and high-efficiency input (HH, full plastic-film mulching on double furrow, 67500 plant.ha-1 of plant density and N, P and organic manure(M) fertilizer were 230kg.ha-1, 140kg.ha-1 and 1500kg.ha-1), and super high yield input (SH, full plastic-film mulching on double furrow, 9000 plant.ha-1 of plant density and N, P and organic M fertilizer were 300kg.ha-1, 180kg.ha-1 and 7500kg.ha-1). The effects of different cultivation modes on yield, WUE, net photosynthetic rate(Pn), leaf area index(LAI), chlorophyll index(SPAD value) and root index were studied.ResultsThe results showed that the value average of yield and WUE for CK were 7790kg and 17480kg.ha-1 in three years. SH, HH and FP cultivation modes of yield and WUE was significant higher compared with CK cultivation mode (P<0.05). SH, HH and FP cultivation modes of yield and WUE increased by 34.01%, 48.68%, 56.39% and 34.34%, 47.99%, 57.99%, compared than CK cultivation mode. These differences were observed during the seedling stage, jointing stage, silking stage and filling stage. Year to year variation in performance of applied treatment, this improved in CK cultivation mode significantly enhanced SPAD value, Pn, LAI and the root index than SH, HH and FP cultivation modes. The yield exhibited a positive correlation with the WUE, SPAD value, Pn, LAI. The SH cultivation mode was the highest yields.DiscussionThe results indicated that maize yield and WUE could be increased through integrating and optimizing cultivation techniques in maize production on the semiarid western Loess Plateau of China. The SH cultivation mode was the highest yields. The primary factor contributing to the increase in yield and WUE of maize due to increased density, increased fertilizer and covering measures is the augmentation of Pn, LAI, SPAD value, and root index.

To meet the grand challenges of agricultural production including climate change impacts on crop production, a tight integration of social science, technology and agriculture experts including farmers are needed. Rapid advances in information and communication technology, precision agriculture and data analytics, are creating a perfect opportunity for the creation of smart connected farms (SCFs) and networked farmers. A network and coordinated farmer network provides unique advantages to farmers to enhance farm production and profitability, while tackling adverse climate events. The aim of this article is to provide a comprehensive overview of the state of the art in SCF including the advances in engineering, computer sciences, data sciences, social sciences and economics including data privacy, sharing and technology adoption. More specifically, we provide a comprehensive review of key components of SCFs and crucial elements necessary for its success. It includes, high-speed connections, sensors for data collection, and edge, fog and cloud computing along with innovative wireless technologies to enable cyber agricultural system. We also cover the topic of adoption of these technologies that involves important considerations around data analysis, privacy, and the sharing of data on platforms. From a social science and economics perspective, we examine the net-benefits and potential barriers to data-sharing within agricultural communities, and the behavioral factors influencing the adoption of SCF technologies. The focus of this review is to cover the state-of-the-art in smart connected farms with sufficient technological infrastructure; however, the information included herein can be utilized in geographies and farming systems that are witnessing digital technologies and want to develop SCF. Overall, taking a holistic view that spans technical, social and economic dimensions is key to understanding the impacts and future trajectory of Smart and Connected Farms.

IntroductionThere is a need to rebuild soil health by implementing regenerative agricultural practices across cropping systems dependent on agrochemicals, such as in United States corn production. One increasingly utilized regenerative practice is the application of biostimulants, or microbial inoculants that can rebuild soil health and productivity. In this study, we describe results from a multi-year corn trial conducted to quantify the impact of Re-Gen, a biostimulant invented to recycle plant biomass and increase nutrient bioavailability in the soil.MethodsRe-Gen was applied across four fields (VA01, BH01, VA04, and LA05) at a dairy cattle farm in Ferrisburgh, VT.ResultsOver the two consecutive years (2022-2023) of the trial, Re-Gen application on corn stover and cover crop residues increased ear corn yield by 24% and corn silage yield by 12.5-30%, depending on the field. Analysis of soil nutrients and plant tissues showed increased nutrients, particularly in field LA-05. Multi-year Re-Gen application increased yield and generated additional economic value, indicating that the effects of Re-Gen do not diminish with multiple applications. The increased corn silage yield correlated to increased potential milk yield from cows fed silage grown in Re-Gen-treated fields. Further investigation into the mechanism suggests that increased phosphatase production Re-Gen could contribute to increased phosphorus bioavailability in the soil and uptake in the tissue, potentially increasing yields.DiscussionThese results highlight the potential for Re-Gen to foster regenerative agriculture processes on cropland and livestock farms while also increasing corn and milk yield and, therefore, revenue for corn farmers in the United States and for similar cropping systems worldwide.

IntroductionSorghum is emerging as a viable crop option to increase food production under changing climate due to its resilience to drought and marginal soils. Appropriate planting date, crop cultivars, type of tillage and rotations, under contrasting climatic conditions, could make significant contribution on the effective management of sorghum under changing climatic conditions. A short-term study was carried out to investigate the effects of planting date, crop cultivar, tillage type and rotations on the growth and primary nutrient uptake of sorghum in contrasting climatic regions.MethodsThe study was conducted in Free State - (FS) and KwaZulu Natal (KZN) Provinces of South Africa over two seasons (2020/21 and 2021/22). The two cultivars (Pan8816 and Macia) were sown in December (PD1) and in January (PD2) under conventional tillage (CT) and no-till (NT) and with two rotations (Sorghum-Cowpea-Sorghum and Sorghum-Sorghum-Sorghum) resulting in 2×2×2×2 factorial experiment.Results and discussionIn KZN, in both the first (2020/21) and second (2021/22) seasons, the effects of all the factors, except cultivar in the second season, were not significant on yield, and uptake of nitrogen (N), phosphorus (P) and potassium (K). In the second season, Pan8816 (4.40 t/ha) produced 3.3 times higher yield than Macia (1.32 t/ha), and took up higher N, K and P. In FS, the early planted sorghum (1.15 t/ha for season one; 3.39 t/ha for season two) had significantly higher yield than late planted sorghum (0.434 and 0.91 t/ha for seasons one and two, respectively). Furthermore, the early-planted crops took up higher N, K and P than when planted late, while Pan8816 took up 1.74 times more P than Macia. Plants grown under CT (2.61 t/ha) produced significantly higher yield than under NT (1.70 t/ha), with plants under CT taking up significantly more K than those grown on NT. These findings suggest that in the drier FS, early planting under conventional tillage, while in the wetter KZN, selecting the appropriate cultivar (PAN8816), are essential for sorghum grain yield, at least in the short-term.