Local Crop Research Articles

Climate change, cropland adjustments, and food security: Evidence from China

Climate change is expected to reduce crop yields, but knowledge on how it affects agricultural land use is still limited. This paper empirically investigates the induced cropland adjustments in responding to long-run climate change in China. Based on county-level data over several decades, we employ a moving-average specification that exploits within-county variation in local climate normals. We show that cropland expands with rising temperature (precipitation) in cold (dry) areas, while the effect is reversed in hot (humid) areas. The results are consistent with the “long-difference” estimates and robust to a host of different specifications. Besides, local crop mix also evolves with the changing climate. However, accounting for the crop-mix adjustments, climate change by the mid-century is still predicted to significantly lower the national calorie provision through induced cropland adjustments, and an average yield growth of 17.6% (21.2%) would be required to offset the associated loss under RCP 4.5 (RCP 8.5).

Extreme rainfall indices and their consequences on the local farming crop calendar: An agro-climatic zone based study

<p>The goal of this study is to investigate the extreme rainfall indices and their consequences on the local farming crop calendar among the agro-climatic zones (ACZs) of the Abiya watershed. Climate Hazards Group Infrared Precipitation (CHIRPS) provided long-term (1981–2019) rainfall data for 50 sample grid points with a spatial resolution of 5 × 5 km. Different crops are affected differently by the same extreme rainfall event depending on when it occurred and how extreme it was; this means crop calendars for a specific time may be properly governed by extreme climatic conditions. There hasn’t been a sufficient published study on extreme rainfall indices and their consequences on crop calendars by considering various ACZ in Ethiopia. The study defined local crop calendar timing and the consequences of the extreme rainfall indices through focus group discussions. INSTAT+ software was applied to calculate eight extreme rainfall indices. The indices were evaluated using Mann-Kendall’s (MK) and Sen’s slope techniques to identify trends and determine variations in the magnitude, respectively. Increase and decrease indications for various crop calendars were found in each ACZ. Further, going-up signals were seen in the highlands, midlands, and all ACZs for land preparation time (LPT), sowing and management time (SaMT), and harvesting and threshing time (HaTP), respectively. While HaTT was found to be uniform in all ACZs, some of the declining trends in the indices were detected for LPT and SaMT in the cold-highland and highland zones. The perceived trend in indices across the whole ACZ will have direct and unintended consequences for watershed crop production. The findings imply that to reduce the unfavourable consequences of these extreme rainfall occurrences in the agricultural sector, it is necessary to develop suitable crop varieties and drought-tolerant crops, as well as an effective early warning system.</p>

Health risk assessment of heavy metals in soils and crops in a mining area (Au-Ag-Cu-trona-oil et al.) of the Nanyang Basin, Henan Province, China

Heavy metal distribution in mining areas has always been a hot research topic due to the special environment of these areas. This study aims to explore the impact of heavy metal pollution on soils and crops in the study area, ensure the safety of local crops and the health of local residents, and provide a basis for the subsequent environmental restoration and the prevention and control of environmental pollution. Based on the analysis of the heavy metal concentrations in local soils and crops, the study investigated the spatial distribution, pollution degrees, and potential ecological risks of heavy metals in the farmland of a mining area in the southeastern Nanyang Basin, Henan province, China explored the sources of heavy metals and assessed the health risks caused by crop intake. The results of this study are as follows. The root soils of crops in the study area suffered heavy metal pollution to varying degrees. The degree of heavy metal pollution in maize fields is higher than that in wheat fields, and both types of fields suffer the most severe Cd pollution. Moreover, the root soils of different crops suffer compound pollution. The root soils in the maize fields suffer severe compound pollution at some sampling positions, whose distribution is similar to that of the mining area. Cd poses the highest potential ecological risks among all heavy metals, and the study area mainly suffers low and moderate comprehensive potential ecological risks. The principal component analysis (PCA) shows that the distribution of Zn, Cd, Pb, and As in soils of the study area is mainly affected by anthropogenic factors such as local mining activities; the distribution of Cr and Ni is primarily controlled by the local geological background; the distribution of Hg is mainly affected by local vehicle exhaust emissions, and the distribution of Cu is influenced by both human activities and the geological background. Different cereal crops in the study area are polluted with heavy metals dominated by Cd and Ni to varying degrees, especially wheat. As indicated by the health risk assessment results, the intake of maize in the study area does not pose significant human health risks; however, Cu has high risks to human health, and the compound heavy metal pollution caused by the intake of wheat in the study area poses risks to the health of both adults and children. Overall, the soils and crops in the study area suffer a high degree of heavy metal pollution, for which mining activities may be the main reason.©2023 China Geology Editorial Office.

Linking crop availability, forest elephant visitation and perceptions of human–elephant interactions in villages bordering Ivindo National Park, Gabon

AbstractFeeding by Critically Endangered forest elephants Loxodonta cyclotis in rural plantations is a conservation issue in Gabon, but studies characterizing drivers of spatiotemporal patterns of human–elephant interactions remain sparse, hindering mitigation. In this study, we use GPS tracking data from two elephants to characterize temporal patterns of village visitation, and surveys of 101 local farmers across seven villages to determine local patterns of crop planting and harvesting and of human–elephant interactions. Local farmers' perceptions of elephant visitations and empirical data on such visits were positively correlated with local crop availability. However, considering the two elephants separately revealed that the correlations were driven by just one individual, with the second elephant showing weak links between crop availability and visitation, highlighting the challenges in reliably predicting human–wildlife interactions. The most popular local perceptions of the drivers of elephant visitation were the presence of crops (53% of responses) and logging (39%). The most popular proposed interventions were letting the government find a solution (32%), killing problem elephants (30%) and providing compensation for lost crops (22%). We discuss the potential feasibility and efficacy of the proposed solutions in the context of human–elephant interactions. Future research efforts should focus on collaring elephants in zones with high potential for negative human–elephant interaction and expanding perception surveys to villages with contrasting ecological contexts (e.g. with and without logging in their surrounding forests), as these could influence local perceptions of conflicts and conservation initiatives.

Implementation of a weather station to monitor agricultural crops

Abstract Various studies on local crop monitoring are presented in the literature, however there is insufficient research on low-cost IoT weather stations that can obtain weather information over a long period of time. To overcome the difficulties described above, this paper proposes the development of an IoT weather station for low-cost, sustainable and multi-functional agricultural crop monitoring. The objective of the work is to develop a local weather observation device for agricultural crops, to set up a server for storing and providing meteorological information and to perform an analysis of the acquired weather data. The weather station architecture developed and proposed in this project consists of four main blocks: sensor and controller module, power module, local data storage module and data communication module (gateway).

A decade drought monitoring through enhanced and standardized vegetation index in isolated karst environment: Nusa Penida Island, Bali, Indonesia

Nusa Penida is one of the regions in Indonesia that vunarablely experiences extreme drought. The worst drought occurred in December 2019, coinciding with the Covid-19 pandemic outbreak. At that time, drought caused major crises in many local primary economic aspects, such as clean-water crises and local crop failure. The situation worsened after the global pandemic lockdown was imposed. Many tourism-related hospitalities (i.e., hotels, resorts, and restaurants) also have crashed. Isolated karst islands such as Nusa Penida Island pose significant challenges for water and agricultural land management. Geologically, this area consists of hilly carbonate rock terrain, a lack of proper aquifers, low precipitation, and tend to had high concentrations of dissolved Ca and Mg in its water. These conditions make many areas less preferable for settlements and traditional agriculture. In this study, we assessed the area using geospatial data for drought monitoring. We analyzed weekly-22 years of data (18/02/2000-18/02/2022 or 507 weeks data) to understand the period pattern of seasonal droughts in Nusa Penida over the past decade. This study used compiled satellite raster-images data to compute the Enhanced Vegetation Index (EVI) to express the Standardized Vegetation Index (SVI), which is sensitive to vegetation change during drought. The results showed that the longest droughts in Nusa Penida occurred from December 2000 to October 2001 (20 weeks) and Feb 2002 to Jan 2023 (21 weeks). The worst droughts occurred in December 2019 (SVI: -1.903 to -1.236), 2006 (SVI: -1.872 to -1.374), and 2002 (SVI: up to -0.136). There are patterns in which droughts in Nusa Penida tend to occur towards the end of the year, including at the end of 2022. Additionally, we detected some evergreen areas in Nusa Penida that require further investigation. These areas potentially act as natural permanent aquifers even during droughts. Furthermore, this study provides more insights for other comprehensive research, especially to enhance mitigation policies for near-future drought periods in Nusa Penida.

Spatial and temporal variability of rainfall in Western Bahia

Western Bahia is a region widely recognized for its significance in large-scale agricultural production, being one of the mainstays of the local economy. However, agricultural activities in this area are often challenged by extended periods of low precipitation, posing a constant threat to the productivity of major crops. Deep concerns are raised by unpredictability of rainfall, especially in February during the critical period of crops, which encompasses the flowering and/or grain filling stages of most crops in the region. In this scenario, this study assumes a central role in search for answers. Thus, this paper aimed to analyze the behavior of spatial and temporal variability of rainfall in the Western region of Bahia. The research focused on the month of February due to its critical relevance to the life cycle of local crops and its direct influence in agricultural productivity. Rainfall data were obtained from the stations network of the National Water Agency (ANA) through the Hydroweb platform for the period from 1986 to 2015. The Rain Anomaly Index (RAI) for the month of February was then calculated using equations developed by Rooy (1965). To analyze the space-time variability of drought events in their different intensities, RAI maps were generated containing eight categories ranging from extremely wet to extremely dry, for the measurement and classification of rainfall anomalies in relation to the historical average. The results revealed that throughout the analyzed period, approximately 53.33% of the February months exhibited negative anomalies, denoting drought events ranging from mild to extreme, while approximately 30% of the months displayed positive anomalies, indicating moisture levels ranging from low to extremely wet. Notably, in the years with the most significant negative anomalies (drought events), there was a predominance of spatial variability from east to west, with the lowest negative anomalies on the western side and the highest on the eastern side of the region. On the other hand, positive anomalies (wet events) exhibited a predominance of spatial variability from south to north in the region. This study provides valuable insights for the agricultural sector, water resource planning, and environmental management. It underscores the importance of adaptive strategies to address climatic fluctuations and ensure the sustainability of agricultural production in the Western Region of Bahia.

Insect-Mediated Pollination of Strawberries in an Urban Environment.

Pollination services provided by a diversity of pollinators are critical in agriculture because they enhance the yield of many crops. However, few studies have assessed pollination services in urban agricultural systems. We performed flower-visitor observations and pollination experiments on strawberries (Fragaria × ananassa) in an urban area near Paris, France, in order to assess the effects of (i) insect-mediated pollination service and (ii) potential pollination deficit on fruit set, seed set, and fruit quality (size, weight, and malformation). Flower-visitor observations revealed that the pollinator community solely comprised unmanaged pollinators, despite the presence of beehives in the surrounding landscape. Based on the pollination experiments, we found that the pollination service mediated by wild insects improved the fruit size as a qualitative value of production, but not the fruit set. We also found no evidence of pollination deficit in our urban environment. These results suggest that the local community of wild urban pollinators is able to support strawberry crop production and thus plays an important role in providing high-quality, local, and sustainable crops in urban areas.

Occurrence, seasonal variation and gas/particle partitioning of current used pesticides (CUPs) across 60 °C temperature and 30° latitudes in China

Gas and particle phases samples were collected at three sites in China in 2019–2020, with 60 °C temperature span and 30° latitude range. Totally, among 76 target current used pesticides (CUPs) with four types, 51 were quantified in at least one sample. The concentrations of individual CUPs ranged from 8 orders of magnitude, indicating different pollution levels. Herbicides were the dominated CUPs in Northeast China, while higher concentrations of fungicides were found in Southeast China. The highest concentrations of CUPs were observed in Southeast China in spring and winter, while in summer and autumn in Northeast China, caused by local climates and crop cultivation patterns. The gas/particle (G/P) partitioning of CUPs was mainly influenced by their physicochemical properties and ambient temperature. The G/P partitioning study indicated that the L-M-Y model was the optimum prediction model for herbicides, fungicides and pyrethroids. The L-M-Y model and the H-B model presented equal performance for organophosphate insecticides. To our knowledge, the L-M-Y model was firstly applied for the study of the G/P partitioning of CUPs, which provided new insights into the related fields of new emergency contaminates.

Mapping melliferous potential in productive honey areas through spatial tools: Towards a rationalization of beekeeping

Climatic conditions, drought and frost severely affect honey sector. Nevertheless, beehives have increased significantly, leading to overcrowding and competition between beekeepers. The recognition of unfavourable spatial patterns of beehives and the identification of new potential honey production areas are therefore desirable to better rationalize beekeeping. With these premises, in this work a GIS-based mapping approach is proposed aiming at: (i) giving a local estimate of melliferous potential; (ii) providing an estimation of the maximum amount of honey that bees can locally collect in their home range; (iii) mitigating overcrowding of beehives; (iv) quantifying honey potential production at municipal and hive level. With reference to the 2021 year, a study area located within the Torino province (NW Italy) was selected as pilot site. With reference to the local main crops and forest types the melliferous potential was mapped using reference unitary values from literature. Unfavourable and restricted zones for beekeeping were masked out and an estimation of suitable honey productive areas given. Assuming a bees' home range of 3 km, a squared moving window (sizing 3 × 3 km) was used to quantify local potential areas providing food for bees. These were used to investigate the optimal beehives density and the potential of honey production at municipal level. Resulting maps are useful to support beekeepers' associations for addressing management and monitoring beekeeping sites towards a more sustainable direction. Specifically, new sites for hive hosting could be planned in unexplored areas having high melliferous potential minimizing unfavourable effects related to beehive overcrowding and beekeepers competition.

Plant blindness profile of high school students in Hulu Gurung sub-district, Kapuas Hulu district

People often forget about plants as living organisms that are essential for life which characterizes plant blindness. Plant blindness can occur in students. The objectives of this study are identifying plant blindness in high school student in Hulu Gurung. This research was conducted in January 2023 in the even semester of 2022/2023. The population in this study were all students of SMPN 1 Hulu Gurung (Junior High School) and SMAN 1 Hulu Gurung (Senior High School). Sample selection using Simple Random Sampling technique. The instruments used were questionnaires and direct interviews. Methods for data analysis using qualitative descriptive methods. The results showed that students still lack knowledge about local vegetables. The percentage of students recognizing vegetables was 15% in senior high school students and 4% in junior high school students. There were 6 vegetable species that were not recognized at all, namely Solanum lasiocarpum, Ficus sp., Mangifera pajang, Polypodium sp., Ficus sp., and Smilax leucophylla. In the future local vegetables can be better recognized amidst the presence of imported vegetables. The diversity of local vegetable crops must be maintained through conservation strategies, one of which is to avoid plant blindness as early as possible.

Modification of the RothC model to evaluate the inconsistent effect of conservation tillage on SOC stock and a suggestion of a national-scale assessment framework

Simulation of conservation tillage effect on soil organic carbon (SOC) stock on the national scale is essential for Tier 3 level greenhouse gas inventory in the agricultural sector. However, the conservation tillage effects varied depending on different soil conditions, potentially leading to inaccurate national assessments. This study aimed to propose a framework for estimating the national scale impact of conservation tillage on SOC. As even in the most commonly used SOC dynamic model, the Rothamsted Carbon Model (RothC), does not reflect the conservation tillage effect in an explicit way, we modified it by developing the tillage rate modifiers (TRMs). First, we investigated the conditions for the inconsistent conservation tillage effects using the decision tree analysis based on 210 field experiment data from the mid-latitude region. The results highlighted that soil sand content and the existing SOC stock were the main factors driving the inconsistencies. After we categorized into four distinctive conditions, the TRMs for each condition were parameterized using a genetic algorithm. The average TRMs were 0.88 in the soils with sand content >37.6 % and 1.58 in the soils with sand content ≤37.6 %, indicating that conservation tillage is more effective in coarse-textured soil, and there is a risk of decreasing SOC stock in the latter condition. Using the modified RothC model, a three-step national-scale simulation framework was suggested: compiling country-specific data, establishing baseline and conservation tillage scenarios, and modeling conservation tillage effects with uncertainty analysis. Our approach also defined the maximum conservation tillage area, factoring in local cropping systems and soil conditions. Our refined RothC model with TRMs provides a nuanced understanding of conservation tillage effects, emphasizing the role of soil characteristics. The proposed national-scale simulation framework offers a reliable tool for evaluating conservation tillage impact on SOC, ensuring more accurate greenhouse gas inventories in agriculture.

Optimization of a formula to develop iron-dense novel composite complementary flour with a reduced phytate/minerals molar ratio from dabi teff-field pea-based blends using a D-optimal mixture design.

Iron deficiency anemia is one of the major public health problems in children associated with the inadequate intake of bioavailable iron. Thus, this research was aimed at incorporating dabi teff, an underutilized/forgotten crop, into other pre-processed local food crops, viz., germinated maize, roasted barley, roasted field pea, dehulled oats, and linseed, to develop optimized iron-dense novel composite complementary flour with a reduced phytate/minerals molar ratio. Nutrisurvey software was employed to define ranges, and they were constrained at 20-35% dabi teff, 0-30% field pea, and 5-20% maize, while the remaining were kept constant at 25% barley, 15% oats, and 5% linseed. Eleven experimental runs were generated from the six mixture components using Stat-Ease Design Expert® software version 11, D-optimal. Inductively coupled plasma-optical emission spectrometry was used to determine micronutrients. 'Scheffe' regression was used to fit and test the model's adequacy, and numerical multi-response optimization was performed using the Design Expert® to identify the optimal points. Dabi teff had a significantly higher (p < 0.05) iron content at 86.5 mg/100 g, iron density at 24.53 mg/100 kcal, and calcium content at 123.59 mg/100 g. The new formulations had a significantly higher iron content (3.31-4.36 times), iron density (3.25-4.27 times), and calcium content (1.49-1.58 times), as compared to the control flour, and fulfilled FAO/WHO recommendations. The optimal formula was identified at 34.66% dabi teff, 25% barley, 15% oats, 15.34% field pea, 5% linseed, and 5% maize flour ratios, with response values at the overall optimization as 32.21 mg/100 g iron, 77.51 mg/100 g calcium, 2.59 mg/100 g zinc, 0.233 phytate/iron molar ratio (Ph:Fe), 0.067 phytate/calcium molar ratio (Ph:Ca), 3.43 phytate/zinc molar ratio (Ph:Zn), and 6.63 phytate by calcium to zinc molar ratio (Ph*Ca:Zn). Furthermore, it contained iron at a level that is 2.01 times higher than the standard and 4.44 times higher than the control, as well as an iron density of 8.47 mg/100 kcal, which was 4.39 times higher than that of the control. These findings showed that the optimized dabi teff-field pea based iron-dense novel composite complementary flour with enhanced bioavailability can be developed and used as a sustainable food-based strategy to combat iron deficiency anemia among children in less developed countries, such as Ethiopia.

Modifikasi Serat Kenaf (Hibiscus cannabinus L.) Menggunakan Anhidrida Propionat

Kenaf is a local crop that has great potential as a polymer composite reinforcement. However, the main weakness in strengthening composites using kenaf fiber is its hydrophilic or water-absorbing properties. To improve composite properties, surface modification of kenaf fiber is needed to enhance the structure and chemical properties of kenaf fiber. This study aims to explore the potential of chemical modification of kenaf fiber for use in composites. Chemical modification treatment of kenaf fibers was intended to improve the hydrophobicity that the compatibility between the fiber and matrix bonds are enhanced. In this study, chemical modification of kenaf fiber was performed using propionic anhydride. The modification process was done through a three-variation of retention time; 100, 200, 300 minutes at 100 °C. This research also compared the kenaf fiber properties with and without the modification process, including the analysis of the weight percent gain and surface morphological structure. The results showed that the optimal weight gain and morphological structure was at a retention time of 200 minutes.

Bee pollination efficiency in watermelon (Citrullus lanatus) crops in Panama

This study evaluated the bee pollination efficiency of wild neotropical bees visiting watermelon flowers in Azuero, Panama. We determined the quantity of pollen grains deposited on stigmas of excluded flowers by Apis mellifera, Nannotrigona perilampoides, Trigona corvina, Trigona fulviventris, and Lasioglossum spp. We also determined the number of produced fruits and their quality by weighing and counting the seeds inside the fruits produced by 1, 8, 12, and 16 visits of A. mellifera, N. perilampoides, and T. corvina. Finally, we calculated Spear's Pollination Efficiency Index. We found differences in the pollen grain number deposited by the studied bee species. On average, T. corvina deposited the largest amount of pollen (n = 379 ± 35), and T. fulviventris deposited the least (n = 86± 20). The fruit weight and seed number showed a positive correlation with the number of visits the flowers received. No differences were observed in weight and seed number in the fruits visited by the three bee species. The best quality fruits were obtained with 16 visits and no visit restriction treatment, with no differences between them. Our results show the studied bee species are capable of efficiently pollinating watermelon flowers, and have the potential for being used in the pollination of local crops. However, the best production results are obtained when the bee species act together.

Nutritional quality assessment of complementary food from plantain, velvet bean and crayfish

Complementary foods are needed to supplement breast milk with essential nutrients needed for general wellbeing of growing children. In developing countries these children still suffer from nutritional deficiencies which can be ameliorated by development of nutrient dense and acceptable complementary foods from locally available crops. Mixture design of design expert was used to obtain optimized flour blend from plantain, velvet beans and crayfish flours for the production of complementary food which was analyzed for its nutritional and sensory qualities. This was analyzed for its proximate composition, nutritional quality and sensory properties. Result of proximate composition for moisture, crude protein, fat, fibre, ash and carbohydrate was 6.49 %, 12.18 %, 1.50 %, 0.35 %, 2.10 % and 82.93 % respectively. The complementary food had 64.80 % in-vitro protein, 21.80 % starch digestibility, gross energy of 4132.21 Cal, in-vitro total sugar content of 3.29g/100g and a total carbohydrate content of 50.87 %. The complementary food had sensory attributes comparable to commercial complementary foods, was nutrient dense and could be used as alternative to expensive complementary foods. There is therefore need to continue to formulate nutritionally dense and acceptable weaning food from local crops in order to ameliorate the nutritional deficiencies among infants and hence improve their general wellbeing.

Irrigation Water and Nitrogen Fertilizer Management in Potato (Solanum tuberosum L.): A Review

Intensive irrigation and nutrient management practices in agriculture have given rise to serious issues in aquifer water depletion and groundwater quality. This review discusses the effects of irrigation and nitrogen management practices on potato growth, yield, and quality, and their impacts on water and nitrogen use efficiencies. This review also highlights the economics and consequences of applying deficit irrigation strategies in potato production. Many researchers have demonstrated that excessive irrigation and nitrogen application rates negatively impact potato tuber yield and quality while also increasing nitrate leaching, energy consumption, and the overall costs of production. An application of light-to-moderate deficit irrigation (10–30% of full irrigation) together with reduced nitrogen rates (60–170 kg/ha) has a great potential to improve water and nitrogen use efficiencies while obtaining optimum yield and quality in potato production, depending on the climate, variety, soil type, and water availability. There is an opportunity to reduce N application rates in potato production through deficit irrigation practices by minimizing nitrate leaching beyond the crop root zone. The best irrigation and nitrogen management techniques for potato production, as discussed in this review, include using sprinkle and drip irrigation techniques, irrigation scheduling based on local crop coefficients, soil moisture content, and crop modeling techniques, applying slow-release nitrogenous fertilizers, split nitrogen application, and applying water and nitrogenous fertilizers in accordance with crop growth stage requirements.

Priorities for narrowing the yield gap and increasing farming systems resilience in the Fiji sugar industry

Sugarcane (Saccharum officinarum L.) is the single most important agricultural industry in Fiji and occupies half of the nation's cropped area while supporting 25% of the labour force. However, the industry is facing comprehensive challenges across the supply chain, underlain by declining productivity and changing climate. The purposes of this study were to: (1) use model simulation to determine the potential of conservation agriculture (CA) practices to narrow yield gaps in sugarcane production systems under historical and projected climates in a case study; (2) identify and rank candidate practices that would contribute to narrowing such yield gaps; and (3) identify the limitations of the modelling approach and make recommendations for improving it. We simulated nine scenarios of CA practices with potential to reduce the estimated yield gap (55 ​Mg ​ha-1) by increasing nitrogen (N) fertiliser rates (30 ​Mg ​ha−1), liming (25 ​Mg ​ha−1), improved weed control (5–9 ​Mg ​ha−1), replacing uncropped fallow with legume crops (2–3 ​Mg ​ha−1), crop cycle duration (0 ​Mg ​ha−1), and retaining crop residues (−2 ​Mg ​ha−1). The yield benefit of CA practices was similar under projected climates that were warmer and wetter or drier, or hotter and wetter. For a projected climate that was hotter and drier, the greatest yield benefit was obtained from liming, weed control, and retaining crop residues. The study was limited by the availability of daily weather data, and it would be complemented by additional studies incorporating more local crops, evaluation of barriers to mechanisation needed to implement new practices, and economic assessment of scenarios.

A Real-Time Strand Breakage Detection Method for Power Line Inspection with UAVs

Power lines are critical infrastructure components in power grid systems. Strand breakage is a kind of serious defect of power lines that can directly impact the reliability and safety of power supply. Due to the slender morphology of power lines and the difficulty in acquiring sufficient sample data, strand breakage detection remains a challenging task. Moreover, power grid corporations prefer to detect these defects on-site during power line inspection using unmanned aerial vehicles (UAVs), rather than transmitting all of the inspection data to the central server for offline processing which causes sluggish response and huge communication burden. According to the above challenges and requirements, this paper proposes a novel method for detecting broken strands on power lines in images captured by UAVs. The method features a multi-stage light-weight pipeline that includes power line segmentation, power line local image patch cropping, and patch classification. A power line segmentation network is designed to segment power lines from the background; thus, local image patches can be cropped along the power lines which preserve the detailed features of power lines. Subsequently, the patch classification network recognizes broken strands in the image patches. Both the power line segmentation network and the patch classification network are designed to be light-weight, enabling efficient online processing. Since the power line segmentation network can be trained with normal power line images that are easy to obtain and the compact patch classification network can be trained with relatively few positive samples using a multi-task learning strategy, the proposed method is relatively data efficient. Experimental results show that, trained on limited sample data, the proposed method can achieve an F1-score of 0.8, which is superior to current state-of-the-art object detectors. The average inference speed on an embedded computer is about 11.5 images per second. Therefore, the proposed method offers a promising solution for conducting real-time on-site power line defect detection with computing sources carried by UAVs.

Insights into agroecological farming practice implementation by conservation-minded farmers in North America

IntroductionThe transformation of our food system towards a more resilient agroecological framework is one of the most pressing needs faced by our global community. Understanding the use of multiple conservation practices is important in the development of research, education, and policy to accelerate their more widespread integration of into farming systems.MethodsThe aim of this study was to conduct a preliminary investigation of the trends regarding multiple practice adoption of conservation farming practices by conventional and organic farmers engaging with sustainable farming methods. Forty farmers were interviewed regarding their use of conservation practices, as well as their motivations, barriers, and future plans for new implementation and expansion of current practices.ResultsFarmers spontaneously identified cover crops and vegetation strips as the most frequently used conservation practices; however, upon more specific inquiry, we found that more than 50% of farmers used additional agroecological conservation practices including local crop varieties, intercropping, managed grazing, crop rotations, and no-till, with many farmers using multiple practices. Overall, we found no correlation of organic certification with the number of conservation practices implemented by farmers. The major motivations towards the adoption of practices included improved soil quality and profitability. Main identified barriers included financial means and risk, lack of knowledge, and access to resources. Farmers showed interest in further implementation of additional conservation practices, including expanded use of cover crops, tree plantings, and no-till practices.DiscussionFurther understanding complementarities, as well as differences in barriers and motivations, can contribute to the design of effective education strategies and financial incentives to promote the simultaneous implementation of agroecological conservation practices.