Spatial Variation in Agricultural BMPs and Relationships with Nutrient Yields Across New York State Watersheds.

Agricultural nutrients nitrogen and phosphorus can subsequently be transported to waterways and are often managed through the adoption of best management practices (BMPs). However, we have a poor understanding of how the use of BMPs varies spatially and how BMP adoption might be related to nutrient yields in surface waters. To address this, we performed a survey of agricultural landowners across New York State and compared this with estimates of annual incremental nitrogen and phosphorus yields of agricultural origin from the Spatially Referenced Regressions On Watershed attributes (SPARROW) model. Using these socio-behavioral data and SPARROW predictions, we perform colocation analysis to identify areas where watersheds with high nutrient yield from agriculture are collocated with non-use of agricultural BMPs. This colocation analysis offers a novel methodology for identifying areas where monitoring of waterways and promotion of best management practices could be targeted to achieve the greatest benefits.

Corrigendum: Paradise by the far-red light: Far-red and red:blue ratios independently affect yield, pigments, and carbohydrate production in lettuce, Lactuca sativa.

[This corrects the article DOI: 10.3389/fpls.2024.1383100.].

Examining the Relationship Between Stress, Barriers to Healthcare, and Alcohol Use in the US Agricultural Community.

OBJECTIVE: Farming is a high-risk, physically challenging occupation. Considering farmers report high stress and barriers to seeking healthcare, it is important to understand factors influencing alcohol use to tailor interventions and healthcare resources for alcohol use in rural areas. METHODS: An online survey was distributed to the agricultural community in the United States (n = 1045). Data was collected through QualtricsXM, and SPSS 28.0 was used for data analysis. RESULTS: Both formal healthcare challenges (ß = 0.112, p = .004) and stigma (ß = 0.328, p < .001) were identified as predictors of increased perceived stress, while resilience (ß = -0.137, p < .001) was identified as a protective factor against perceived stress. Higher perceived stress was identified as a predictor of binge drinking behavior (ß = 0.151, p < .001), and formal healthcare challenges were associated with higher drinking volume (ß = 0.174, p < .001), and engaging in more frequent alcohol consumption (ß = 0.123, p = .004) over the last three months. Resilience was identified as a protective factor against increased alcohol consumption (ß = -0.084, p = .032). Stigmatization of help-seeking for mental health challenges was associated with fewer instances of alcohol consumption over the last three months (ß = -0.169, p < .001). CONCLUSION: Interventions to address stress and alcohol consumption should focus on promoting resilience, reducing stigma, and encouraging peer support to address cultural norms around mental health and alcohol use. Rural practitioners should develop cultural competence to better serve agricultural communities to prevent alcohol use disorders. To discuss ways to reduce stigma and encourage peer support to address alcohol and mental health disorders in rural farming populations.

Sustainable soil management under drought stress through biochar application: Immobilizing arsenic, ameliorating soil quality, and augmenting plant growth.

Rise in climate change-induced drought occurrences have amplified pollution of metal(loid)s, deteriorated soil quality, and deterred growth of crops. Rice straw-derived biochars (RSB) and cow manure-enriched biochars (CEB) were used in the investigation (at doses of 0%, 2.5%, 5%, and 7.5%) to ameliorate the negative impacts of drought, improve soil fertility, minimize arsenic pollution, replace agro-chemical application, and maximize crop yields. Even in soils exposed to severe droughts, 3 months of RSB and CEB amendment (at 7.5% dose) revealed decreased bulk density (13.7% and 8.9%), and increased cation exchange capacity (6.0% and 6.3%), anion exchange capacity (56.3% and 28.0%), porosity (12.3% and 7.9%), water holding capacity (37.5% and 12.5%), soil respiration (17.8% and 21.8%), and nutrient contents (especially N and P). Additionally, RSB and CEB decreased mobile (30.3% and 35.7%), bio-available (54.7% and 45.3%), and leachable (55.0% and 56.5%) fractions of arsenic. Further, pot experiments with Bengal gram and coriander plants showed enhanced growth (62-188% biomass and 90-277% length) and reduced arsenic accumulation (49-54%) in above ground parts of the plants. Therefore, biochar application was found to improve physico-chemical properties of soil, minimize arsenic contamination, and augment crop growth even in drought-stressed soils. The investigation suggests utilisation of cow manure for eco-friendly fabrication of nutrient-rich CEB, which could eventually promote sustainable agriculture and circular economy. With the increasing need for sustainable agricultural practices, the use of biochar could provide a long-term solution to enhance soil quality, mitigate the effects of climate change, and ensure food security for future generations. Future research should focus on optimizing biochar application across various soil types and climatic conditions, as well as assessing its long-term effectiveness.

EfficientMaize: A Lightweight Dataset for Maize Classification on Resource-Constrained Devices.

Hyperspectral imaging, combined with deep learning techniques, has been employed to classify maize. However, the implementation of these automated methods often requires substantial processing and computing resources, presenting a significant challenge for deployment on embedded devices due to high GPU power consumption. Access to Ghanaian local maize data for such classification tasks is also extremely difficult in Ghana. To address these challenges, this research aims to create a simple dataset comprising three distinct types of local maize seeds in Ghana. The goal is to facilitate the development of an efficient maize classification tool that minimizes computational costs and reduces human involvement in the process of grading seeds for marketing and production. The dataset is presented in two parts: raw images, consisting of 4,846 images, are categorized into bad and good. Specifically, 2,211 images belong to the bad class, while 2,635 belong to the good class. Augmented images consist of 28,910 images, with 13,250 representing bad data and 15,660 representing good data. All images have been validated by experts from Heritage Seeds Ghana and are freely available for use within the research community.

Harvesting insect pests for animal feed: potential to capture an unexploited resource.

The demand for animal protein grows as the human population increases. Technological and genetic advances in traditional animal agriculture will not produce enough protein to meet future needs without significant innovations such as the use of insects as protein sources. Insect farming is growing insects, whereas insect harvesting is collecting insects from their natural habitats to produce high-quality protein for animal feed or human food. Intensive agricultural environments produce tremendous quantities of pestiferous insects and with the right harvest technologies these insects can be used as a protein supplement in traditional animal daily rations. An avenue to exploit these insects is to use traps such as the United States Department of Agriculture-Biomass Harvest Trap (USDA-BHT) to efficiently attract, harvest, and store insects from naturally abundant agricultural settings. The modular design allows for a low cost, easy to build and fix device that is user friendly and has customizable attractants to target various pest species. Although insect harvesting faces substantial challenges, including insect biomass quantity, seasonal abundance and preservation, food safety, and economic and nutritional evaluation, the potential for utilizing these pests for protein shows tremendous promise. In this forum, insect harvesting is discussed, including its potential, limitations, challenges, and research needs. In addition, the use of a mass trapping device is discussed as a tool to increase the biomass of insects collected from the environment.

Conceptualization, design, and construction of a novel insect mass trapping device: the USDA Biomass Harvest Trap (USDA-BHT).

The use of insects as animal feed has the potential to be a green revolution for animal agriculture as insects are a rich source of high-quality protein. Insect farming must overcome challenges such as product affordability and scalability before it can be widely incorporated as animal feed. An alternative is to harvest insect pests from the environment using mass trapping devices and use them as animal feed. For example, intensive agricultural environments generate large quantities of pestiferous insects and with the right harvest technologies, these insects can be used as a protein supplement in traditional animal daily rations. Most insect trapping devices are limited by the biomass they can collect. In that context, and with the goal of using wild collected insects as animal feed, the United States Department of Agriculture-Biomass Harvest Trap (USDA-BHT) was designed and built. The USDA-BHT is a valuable mass trapping device developed to efficiently attract, harvest, and store flying insects from naturally abundant agricultural settings. The trap offers a modular design with adjustable capabilities, and it is an inexpensive device that can easily be built with commonly available parts and tools. The USDA-BHT is also user-friendly and has customizable attractants to target various pest species.

A critical systematic review on spectral-based soil nutrient prediction using machine learning.

The United Nations (UN) emphasizes the pivotal role of sustainable agriculture in addressing persistent starvation and working towards zero hunger by 2030 through global development. Intensive agricultural practices have adversely impacted soil quality, necessitating soil nutrient analysis for enhancing farm productivity and environmental sustainability. Researchers increasingly turn to Artificial Intelligence (AI) techniques to improve crop yield estimation and optimize soil nutrition management. This study reviews 155 papers published from 2014 to 2024, assessing the use of machine learning (ML) and deep learning (DL) in predicting soil nutrients. It highlights the potential of hyperspectral and multispectral sensors, which enable precise nutrient identification through spectral analysis across multiple bands. The study underscores the importance of feature selection techniques to improve model performance by eliminating redundant spectral bands with weak correlations to targeted nutrients. Additionally, the use of spectral indices, derived from mathematical ratios of spectral bands based on absorption spectra, is examined for its effectiveness in accurately predicting soil nutrient levels. By evaluating various performance measures and datasets related to soil nutrient prediction, this paper offers comprehensive insights into the applicability of AI techniques in optimizing soil nutrition management. The insights gained from this review can inform future research and policy decisions to achieve global development goals and promote environmental sustainability.

Assessment of the USDA Biomass Harvest Trap (USDA-BHT) device as an insect harvest and mosquito surveillance tool.

Insects are a promising source of high-quality protein, and the insect farming industry will lead to higher sustainability when it overcomes scaling up, cost effectiveness, and automation. In contrast to insect farming (raising and breeding insects as livestock), wild insect harvesting (collecting agricultural insect pests), may constitute a simple sustainable animal protein supplementation strategy. For wild harvest to be successful sufficient insect biomass needs to be collected while simultaneously avoiding the collection of nontarget insects. We assessed the performance of the USDA Biomass Harvest Trap (USDA-BHT) device to collect flying insect biomass and as a mosquito surveillance tool. The USDA-BHT device was compared to other suction traps commonly used for mosquito surveillance (Centers for Disease Control and Prevention (CDC) light traps, Encephalitis virus surveillance traps, and Biogents Sentinel traps). The insect biomass harvested in the USDA-BHT was statistically higher than the one harvested in the other traps, however the mosquito collections between traps were not statistically significantly different. The USDA-BHT collected some beneficial insects, although it was observed that their collection was minimized at night. These findings coupled with the fact that sorting time to separate the mosquitoes from the other collected insects was significantly longer for the USDA-BHT, indicate that the use of this device for insect biomass collection conflicts with its use as an efficient mosquito surveillance tool. Nevertheless, the device efficiently collected insect biomass, and thus can be used to generate an alternative protein source for animal feed.

Impact of climate change on the yield of medicinal plants in recent years.

Climate change significantly impacts the yield and quality of medicinal plants due to alterations in temperature, precipitation patterns, and increased frequency of extreme weather events. These changes affect the growth, secondary metabolite production, and geographical distribution of medicinal plants, leading to reduced yields and compromised medicinal properties. Adaptive strategies such as developing climate-resilient plant varieties, sustainable agricultural practices, and enhanced conservation efforts are essential to mitigate these effects. Increased research and collaborative efforts are necessary to safeguard these vital resources for future generations.

Anthropogenic land uses lead to changes in limnological variables in Neotropical streams.

Streams are vulnerable to anthropogenic impacts, such as changes in land use, which reflect on water quality and can be evaluated by abiotic variables. In this context, the aims were to compare the abiotic values recorded in streams of different land use categories with the limits established by National legislation, and to analyze changes in abiotic variables in response to different land use impacts. Thus, 17 streams located in southern Brazil were sampled and grouped into urban, rural, and protected areas (PA) categories. The results showed the major impacts in urban streams. However, some variables in rural streams and PA also exceeded local legislation limits. Conductivity, total dissolved solids, salinity, ammoniacal nitrogen and coliforms were significantly higher in the urban streams. Contrary to expectations, the highest levels of manganese were found in PA streams. The relationship between abiotic variables and land uses suggests possible contamination by sewage in urban streams and by pesticides in rural streams. The abiotic similarity between rural and PA streams indicates that the conservation of these water bodies is ineffective. We suggest the monitoring of these environments and measures to mitigate the impacts to seek the restoration of ecosystem services and the well-being of human populations.

Gelatin Nanoparticles can Improve Pesticide Delivery Performance to Plants.

Nanomaterials associated with plant growth and crop cultivation revolutionize traditional concepts of agriculture. However, the poor reiterability of these materials in agricultural applications necessitates the development of environmentally-friendly approaches. To address this, biocompatible gelatin nanoparticles (GNPs) as nanofertilizers with a small size (≈150 nm) and a positively charged surface (≈30 mV) that serve as a versatile tool in agricultural practices is designed. GNPs load agrochemical agents to improve maintenance and delivery. The biocompatible nature and small size of GNPs ensure unrestricted nutrient absorption on root surfaces. Furthermore, when combined with pesticides, GNPs demonstrate remarkable enhancements in insecticidal (≈15%) and weed-killing effects (≈20%) while preserving the efficacy of the pesticide. That GNPs have great potential for use in sustainable agriculture, particularly in inducing plant growth, specifically plant root growth, without fertilization and in enhancing the functions of agrochemical agents is proposed. It is suggested conceptual applications of GNPs in real-world agricultural practices.

Visible intruders: Tracing (micro-) plastic in organic fertilizers.

Agricultural soils have been identified as potential reservoirs for plastic pollution, with adverse effects on soil properties. Primary sources of plastic input in agricultural landscapes are associated with the application of sewage sludge or compost. Understanding the sources and anticipated plastic content is crucial in mitigating plastic pollution in agricultural fields. This study presents one of the first investigations into the plastic content and other impurities, e.g. glass, of seven organic fertilizers (biowaste compost, digested pig slurry, sewage sludge compost, dry chicken manure, green waste compost, sewage sludge, and a mixed digestate comprising pig slurry, chicken manure, and 74 % renewable raw materials). Potentially visible foreign substances were assessed on the surface of each fertilizer pile. No impurities could be detected in digested pig slurry, chicken manure, and mixed digestate. For the remaining fertilizers, visible potential foreign substances were collected, cleaned, visually described, weighed, photographed, size measured, and chemically characterized using ATR-FTIR. The quantification revealed that plastic particles are the most abundant and are contained in all other fertilizers, in contrast to glass and metal. An increasing trend in plastic particle number per m2: green waste < biowaste < sewage sludge compost < sewage sludge, which is about 4 times greater in sewage sludge than in green waste compost, could be observed. However, sewage sludge compost has the largest plastic mass and surface area per square meter. This illustrates that sewage sludge compost application can be a significant entry pathway for visual plastics into agricultural soils.

Biofabricated nanomaterials in sustainable agriculture: insights, challenges and prospects.

One ever-evolving and ever-demanding critical human endeavour is the provision of food security for the growing world population. It could be done by adopting sustainable agriculture through horizontal (expanding the aerable land area) and vertical (intensifying agriculture through sound technological approaches) interventions. Customised formulated nanomaterials have numerous advantages. With their specialised physicochemical properties, some nanoparticulised materials improve plant's natural development and stress tolerance and some other are good nanocarriers. Nanocarriers in agriculture often coat chemicals to form composites having utilities with crop productivity enhancement abilities, environmental management (like ecotoxicity reduction ability), and biomedicines (like the ability of controlled and targeted release of useful nanoscale drugs). The Ag, Fe, Zn, TiO2, ZnO, SiO2 and MgO nanoparticles often employed in advanced agriculture are covered here. Some nanoparticles used for various extended purposes in modern farming practices, including disease diagnostics and seed treatment are covered too. Thus, nanotechnology has revolutionised agrotechnology, which holds promises to transform agricultural (eco)system as a whole to ensure food security in future. Considering the available literature, the article further probes the emergent regulatory issues governing the synthesis and use of nanomaterials in the agriculture sector. If applied responsibly, nanomaterials could help improve soil health. The article provides an overview of the used nanomaterials in distribution of biomolecules, to aid in devising a safer and eco-friendly sustainable agriculture strategy. Through this, agri-systems depending on advanced farming practices might function more effectively and enhance agri-productivity to meet the food demand of the rising world population.

Early agriculture and crop transitions at Kakapel Rockshelter in the Lake Victoria region of eastern Africa.

The histories of African crops remain poorly understood despite their contemporary importance. Integration of crops from western, eastern and northern Africa probably first occurred in the Great Lakes Region of eastern Africa; however, little is known about when and how these agricultural systems coalesced. This article presents archaeobotanical analyses from an approximately 9000-year archaeological sequence at Kakapel Rockshelter in western Kenya, comprising the largest and most extensively dated archaeobotanical record from the interior of equatorial eastern Africa. Direct radiocarbon dates on carbonized seeds document the presence of the West African crop cowpea (Vigna unguiculata (L.) Walp) approximately 2300 years ago, synchronic with the earliest date for domesticated cattle (Bos taurus). Peas (Pisum sativum L. or Pisum abyssinicum A. Braun) and sorghum (Sorghum bicolor (L.) Moench) from the northeast and eastern African finger millet (Eleusine coracana (L.) Gaertn.) are incorporated later, by at least 1000 years ago. Combined with ancient DNA evidence from Kakapel and the surrounding region, these data support a scenario in which the use of diverse domesticated species in eastern Africa changed over time rather than arriving and being maintained as a single package. Findings highlight the importance of local heterogeneity in shaping the spread of food production in sub-Saharan Africa.

Corn leaf disease: insightful diagnosis using VGG16 empowered by explainable AI.

The agricultural sector is pivotal to food security and economic stability worldwide. Corn holds particular significance in the global food industry, especially in developing countries where agriculture is a cornerstone of the economy. However, corn crops are vulnerable to various diseases that can significantly reduce yields. Early detection and precise classification of these diseases are crucial to prevent damage and ensure high crop productivity. This study leverages the VGG16 deep learning (DL) model to classify corn leaves into four categories: healthy, blight, gray spot, and common rust. Despite the efficacy of DL models, they often face challenges related to the explainability of their decision-making processes. To address this, Layer-wise Relevance Propagation (LRP) is employed to enhance the model's transparency by generating intuitive and human-readable heat maps of input images. The proposed VGG16 model, augmented with LRP, outperformed previous state-of-the-art models in classifying corn leaf diseases. Simulation results demonstrated that the model not only achieved high accuracy but also provided interpretable results, highlighting critical regions in the images used for classification. By generating human-readable explanations, this approach ensures greater transparency and reliability in model performance, aiding farmers in improving their crop yields.

Impact of crop rotation and tillage operations on mitigating greenhouse gas emissions and evaluation of sustainability index in rice- wheat-green gram cropping system of north Bihar.

In North Bihar (NB), the conventional rice-wheat cropping system has led to soil, water, and environmental degradation, alongside low profitability, threatening sustainability. To address these concerns, a thorough field research was conducted over the course of three years to assess different methods of tillage and crop establishment in a rice, wheat, and greengram cycle. The experiment involved five scenarios with different combinations of crop rotation, tillage techniques, seeding procedures, fertilizer use, and irrigation strategies. Uncertainty analysis showed no significant change in mean and variance estimation among seven scenario replications at 5% significance level. Compared to traditional farming (SN-1), managing DSR-rice (SN-5) increased profitability by 17.56%, improved energy use efficiency (EUE) by 32.16%, and reduced irrigation by 24.76% and global warming potential (GWP) by 23.46%. Similarly, substituting zero tillage wheat (ZTW) SN-5 resulted in comparable profitability gains (18.25%) and significant improvements in irrigation (10 %), EUE (+48.65%), and GWP (-20 %) compared to SN-1. Green gram ZT also showed increased profitability (17.35%), with notable improvements in EUE (+38.31%) and GWP (-12.92%) compared to SN-1. Principal component and correlation analyses revealed relationships between total energy inputs, yields, economic returns, and sustainability indices, highlighting the benefits of crop rotation and tillage practices in optimizing resource use. The study suggests that compared to conventional systems, significant improvements in productivity, profitability, energy-use efficiency, and environmental mitigation can be achieved with Crop Rotation and Tillage Operations techniques.

Positive public attitudes towards agricultural robots.

Robot technologies could lead to radical changes in farming. But what does the public know and think about agricultural robots? Recent experience with other agricultural technologies-such as plant genetic engineering-shows that public perceptions can influence the pace and direction of innovation, so understanding perceptions and how they are formed is important. Here, we use representative data from an online survey (n = 2269) to analyze public attitudes towards crop farming robots in Germany-a country where new farming technologies are sometimes seen with skepticism. While less than half of the survey participants are aware of the use of robots in agriculture, general attitudes are mostly positive and the level of interest is high. A framing experiment suggests that the type of information provided influences attitudes. Information about possible environmental benefits increases positive perceptions more than information about possible food security and labor market effects. These insights can help design communication strategies to promote technology acceptance and sustainable innovation in agriculture.