A Deep Learning-Based Decision Support Tool for Plant-Parasitic Nematode Management.

Plant-parasitic nematodes (PPN), especially sedentary endoparasitic nematodes like root-knot nematodes (RKN), pose a significant threat to major crops and vegetables. They are responsible for causing substantial yield losses, leading to economic consequences, and impacting the global food supply. The identification of PPNs and the assessment of their population is a tedious and time-consuming task. This study developed a state-of-the-art deep learning model-based decision support tool to detect and estimate the nematode population. The decision support tool is integrated with the fast inferencing YOLOv5 model and used pretrained nematode weight to detect plant-parasitic nematodes (juveniles) and eggs. The performance of the YOLOv5-640 model at detecting RKN eggs was as follows: precision = 0.992; recall = 0.959; F1-score = 0.975; and mAP = 0.979. YOLOv5-640 was able to detect RKN eggs with an inference time of 3.9 milliseconds, which is faster compared to other detection methods. The deep learning framework was integrated into a user-friendly web application system to build a fast and reliable prototype nematode decision support tool (NemDST). The NemDST facilitates farmers/growers to input image data, assess the nematode population, track the population growths, and recommend immediate actions necessary to control nematode infestation. This tool has the potential for rapid assessment of the nematode population to minimise crop yield losses and enhance financial outcomes.

Effects of polyethylene oxide particles on the photo-physical properties and stability of FA-rich perovskite solar cells.

In this paper, we use Polyethylene Oxide (PEO) particles to control the morphology of Formamidinium (FA)-rich perovskite films and achieve large grains with improved optoelectronic properties. Consequently, a planar perovskite solar cell (PSC) is fabricated with additions of 5 wt% of PEO, and the highest PCE of 18.03% was obtained. This solar cell is also shown to retain up to 80% of its initial PCE after about 140 h of storage under the ambient conditions (average relative humidity of 62.5 ± 3.25%) in an unencapsulated state. Furthermore, the steady-state PCE of the PEO-modified PSC device remained stable for long (over 2500 s) under continuous illumination. This addition of PEO particles is shown to enable the tuning of the optoelectronic properties of perovskite films, improvements in the overall photophysical properties of PSCs, and an increase in resistance to the degradation of PSCs.

Combined effects of biochar and fertilizer applications on yield: A review and meta-analysis.

The use of biochar is changing, and the combined application of biochar with fertilizer is increasingly gaining acceptance. However, the yield gains results reported in the existing literature through the co-application of fertilizer with biochar are conflicting. To resolve this, we utilized a meta-analysis of 627 paired data points extracted from 57 published articles to assess the performance of the co-application of biochar and fertilizers on crop yield compared with the corresponding controls. We also studied the impact of biochar characteristics, experimental conditions, and soil properties on crop yield. Our analysis showed that individually, biochar and inorganic fertilizer increased crop yield by 25.3% ± 3.2 (Bootstrap CI 95%) and 21.9% ± 4.4, respectively. The co-application of biochar with both inorganic and organic fertilizers increased crop yield by 179.6% ± 18.7, however, this data needs to be treated with caution due to the limited dataset. The highest yield increase was observed with amendments to very acidic soils (pH ≤5), but the benefits of biochar were not affected by the rate and the time after the application. In addition, the effects of biochar are enhanced when it is produced at 401-500 °C with a C:N ratio of 31-100. Our results suggest that the co-application of biochar with either inorganic and/or organic fertilizers in acidic soils increase crop productivity compared to amendment with either fertilizer or biochar. Our meta-analysis supports the utilization of biochar to enhance the efficiency and profitability of fertilizers.

Salinity-affected threshold yield loss: A signal of adaptation tipping points for salinity management of dry season rice cultivation in the coastal areas of Bangladesh.

The potential existence of threshold yield loss in dry season rice growing systems under coastal saline environment remains unexplored, a scenario that could have policy relevance in government planning of rice intensification in the coastal areas of Bangladesh. This study applied the adaptation tipping points (ATPs) approach to investigate threshold yield loss from multiple perspectives of farmers affected by salinity. Data were generated from 280 randomly-selected farmers (rice farmers, n = 109; shrimp farmers, n = 107; salt farmers, n = 64) from two coastal sub-districts using a semi-structured survey. Key informant interviews and focus group discussions were conducted to complement the survey results. Our study revealed that despite government actions to promote dry season rice cultivation, farmers have been growing less rice in this season, with salinity-affected yield loss being the prime reason. Most of the rice farmers have considered that they would discontinue rice cultivation in this season due to yield loss, while shrimp and salt farmers have already reduced rice cultivation for the same reason and shifted to shrimp and salt farming as they perceived these enterprises as highly profitable and require less labour than rice farming. Rice farmers would tolerate a greater rice yield loss (23%) under saline conditions compared with the shrimp (16%) and salt farmers (14%). The yield loss thresholds indicate the need for government actions to support and encourage integrated land management for rice, shrimp and salt farming, rather than research and extension efforts for dry season rice expansion alone. These actions could strengthen sustainable livelihood options to ensure food security, and contribute to the achievement of sustainable development goals, for instance no poverty (SDG-1), zero hunger (SDG-2), and good health and well-being (SDG-3).

GIS-based geomorphometric analysis for potential applications in reversing land and biosystem degradation.

Watershed morphometric assessment is about measurements and calculations of land surface forms for the purpose of understanding hydro-geomorphological character and patterns. Important natural environment geo-information and summary of the spatial characteristics of Tana River Basin (TRB) in Kenya have been obtained through hydro-geomorphometric analysis. Advanced Spaceborne Thermal Emission and Reflection Radiometer Digital Elevation Model (ASTERDEM) data and ArcGIS (ESRI Inc., version 10.4.1) together with published mathematical equations were applied to extract morphometric parameters of the drainage basin, which covers a total area of 94,930 km2 and a span of 527.75 km. The quantitative morphometric analysis considered a total of 28 relief, areal, and linear hydro-morphometric characteristics of the TRB. Relief parameters of the basin suggest moderate-to-low overall watershed steepness, upland with rolling land surface patterns, rugged landforms susceptible to erosion and sediment transportation, and a landscape in evolution process tending towards maturity. This means stability of the land surface can be attained with intensive land degradation reversing strategies like erosion control measures. Areal characteristics further support the basin's susceptibility to erosion as shown by stream length, stream drainage density, and circulatory ratio values. Also, the areal aspects portray peak runoffs with short duration flashes. Linear parameter value results such as bifurcation ratio imply that infiltration capacity varies with stream orders across the watershed. This hydro-geomorphometric analysis would be useful to land and water managers, researchers and practitioners of TRB, and other similar systems in designing and planning soil and water conservation and management practices such as soil erosion control, groundwater recharge activities, catchment modelling, runoff and flood studies, prospecting groundwater mapping, and biological applications.

The importance of farmers' perceptions of salinity and adaptation strategies for ensuring food security: Evidence from the coastal rice growing areas of Bangladesh.

Coastal salinity causes substantial adverse impacts on agricultural productivity and food security. Farmers' choice of salinity adaptation strategies might depend on how they perceive the problem. This research examined rice farmers' perceptions of salinity, adaptation strategies, and its implications for policy initiatives to sustain rice production in the affected coastal areas of Bangladesh. Boro rice growers (n = 109) randomly selected from two coastal sub-districts were interviewed using a semi-structured survey. Awareness of salinity and its increase over the past 20 years was widespread among rice farmers. A high proportion of farmers (90%) perceived the reproductive (e.g. booting, heading, and flowering) stages of the rice plant as the most sensitive to salinity problems. Salinity (ECe) was measured in the farmers' fields and were categorized according to farmers' perceptions and scientific interpretation (e.g. high or low). Farmers perceived a field affected by high salinity at a lower EC reading than the scientific interpretation of the salinity level. Most of the farmers (67%) were undertaking early transplanting and applying irrigation in order to adapt to salinity problems which occur later in rice crop growth during Boro season. Thus, farmers' actions demonstrated that their perceptions of salinity and adaptation responses were pre-emptive of when salinity was most likely to have an impact on the rice crop. Farmers' perceptions of salinization and measures to manage salinity need to be considered in research prioritization and policy formulation by the government. This action could potentially secure rice production and thus contribute to the achievement of Sustainable Development Goals (SDG-1, 2 and 3).