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  1. 81

    Microwave assisted popping of five Andean cultivars of ñuña beans: Process optimization and effect of grain’s moisture content by Juan Saavedra, Alberto Claudio Miano

    Published 2024-09-01
    “…In addition, this work found that for every studied cultivar, moisture content between 9 to 11% w.b (wet basis). is suitable to maximize popping percentage. …”
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  2. 82

    The Physical Quality of Milled Rice as Affected by Moisture Content and Relative Humidity during Delayed Rough Rice Drying by Tamrin Tamrin, Filli Pratama, Bagus Septian

    Published 2017-10-01
    “…Delayed rough rice drying was often found in tidal low land in Indonesia due to rice harvesting used to be in rainy season. …”
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  3. 83

    A new landslide detection approach using the combination of the normalized difference moisture index and slope classification analysis by Muhammad Rendana, Edy Sutriyono, Muhammad Said, Wan Mohd Razi Idris, Maulana Yusuf, Yogie Zulkurnia Rochmana

    Published 2024-12-01
    “…Landslides are the most common natural disasters that are often found in tropical and mountainous areas. This study aimed to identify the potency of the combination of the normalized difference moisture index (NDMI) and slope analysis in the Cameron Highlands region of Pahang State, Malaysia. …”
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  4. 84

    Coupling SAR and optical remote sensing data for soil moisture retrieval over dense vegetation covered areas. by Jiahao Shi, Huan Yang, Xinli Hou, Honglu Zhang, Guozhong Tang, Heng Zhao, Fuqiang Wang

    Published 2025-01-01
    “…Satisfactory accuracy of soil moisture retrieval result was obtained with the Oh model and the LUT algorithm, VV polarization is found to be more suitable for soil moisture retrieval compared to VH polarization, with an R2 of 0.672 and an RMSE of 0.048m3·m-3, the accuracy is higher than that of the direct retrieval method. …”
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  5. 85

    Effect of Synthetic and Biological Plant Growth Stimulants and Soil Amendments on the Development of Maize in Various Soil Moisture Conditions by Monika Grzanka, Łukasz Sobiech, Romana Głowicka-Wołoszyn, Dominika Radzikowska-Kujawska

    Published 2024-12-01
    “…Significant improvement was found for many parameters compared to the control combination plants, including maize weight and grain yield. …”
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  6. 86

    Melt-processing, moisture-resistance and strength retention properties of supercritical CO2-processed thermoplastic starch resins by X. L. Peng, M. C. Kuo, C. Y. Huang, W. Wei, D. W. Wang, L. S. Sun, J. Runt, J. T. Yeh

    Published 2018-05-01
    “…In comparison to TPS and TPS100GAx, more dissociated amylopectin chains with loosely hydrogen-bonded –OH groups and significantly less retrogradation was found for conditioned scCO2TPS and scCO2TPS100GAx.…”
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  7. 87

    Development of a Novel Microwave Powered Method for Reducing Moisture and Microbes for Mitigating Public and Environmental Health Risks by Aditya Pandey, Omeed Momeni, Pramod Pandey

    Published 2024-01-01
    “…We found that microwave based treatment technology is capable of inactivating dairy manure-borne bacteria, and moisture rapidly, which are potentially responsible for biological methane emissions and microbial risks to food, and public health. …”
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  8. 88

    Effect of Type of Coagulant and Addition of Stored Curd on Chemical, Rheological and Microstructural Properties of Low-Moisture Mozzarella Cheese by Cristina Alamprese, Paolo D’Incecco, Stefano Cattaneo, Fabio Masotti, Ivano De Noni

    Published 2025-01-01
    “…Low-moisture Mozzarella cheese (LMMC) was manufactured in a dairy factory by stretching fresh curd in hot water, with the addition of 0–30% commercial curd (stored curd) purchased as a semi-finished product. …”
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  9. 89

    Leveraging a Novel Straightforward Integration Approach for Independent CYGNSS Soil Moisture Retrieval across Vegetated Regions by Ziyue Zhu, Hoang Hai Nguyen, Venkataraman Lakshmi, Hyunglok Kim

    Published 2025-01-01
    “…The integration approach was found to be more superior under sparse canopies, together with high-SF and LST areas. …”
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    Article
  10. 90

    Impact of Soil Organic Matter Content on Soil Moisture and Temperature at Different Depths in the Central Qinghai-Xizang Plateau by Qing FU, Kun YANG, Donghai ZGENG, Yingying CHEN

    Published 2022-10-01
    “…Soil organic matter content is relatively high in the central and eastern Qinghai-Xizang Plateau, which may change the soil hydrothermal properties and thus affect the transport of soil water and heat.However, there is still a lack of systematic quantification on how soil organic matter content affects soil moisture and temperature profiles as well as their spatial heterogeneity on the Qinghai-Xizang Plateau.In this study, this effect is quantified using the in situ soil moisture and temperature data as well as soil organic carbon contents collected at 32 stations under similar climatic conditions in Naqu.The soil temperature and moisture dynamics in different depths (5, 10, 20 and 40 cm) with different organic matter contents and their spatial heterogeneity during the warm season were systematically analyzed.It is found that the soil organic matter content is a key factor determining the spatial distribution of soil moisture at 5 cm and 10 cm depth and temperature at 5 cm depth.The soil organic matter content also significantly affects the profile characteristics and dynamics of soil moisture from the surface to 20 cm depth.A higher organic matter content tends to produce a greater water holding capacity, resulting in higher soil moisture contents from the surface to 20 cm depth.In addition, the profile characteristics and variations of soil temperature are largely influenced by the soil organic matter content as well.The higher organic matter content leads to lower thermal inertia, smaller amplitudes of diurnal soil temperature variation, and thus longer time lag of heat transfer to the deeper layers.The findings of this study will provide an important reference for improving the soil moisture and temperature simulations of land surface models in alpine meadows.…”
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  11. 91

    Cascaded Machine Learning of Soil Moisture and Salinity Prediction in Estuarine Wetlands Based on In Situ Internet of Things Monitoring by Jie Song, Yujun Yi

    Published 2025-04-01
    “…Artificial Neural Networks, Support Vector Machines, Random Forests (RF), and Gradient Boosting Decision Trees (GBDT) were used to develop the soil moisture and salinity prediction models. The cascaded framework, in combination with a moisture and a salinity sub‐model, which inspired by soil water and salt transport processes, was found to be an effective approach for capturing moisture‐salinity dynamics. …”
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  12. 92

    Effects of air temperature, photoperiod, and soil moisture on leaf senescence and dormancy depth in four subtropical tree species by Fucheng Wang, Yiming Liu, Heikki Hänninen, Jinbin Zheng, Yu Zhao, Wenwen Chang, Jiasheng Wu, Rui Zhang

    Published 2025-01-01
    “…To address this gap, using climate chambers, we experimentally examined the effects of air temperature, photoperiod, and soil moisture on leaf senescence and dormancy depth in seedlings of four subtropical tree species. …”
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  13. 93

    Relationship between Vegetation and Soil Moisture Anomalies Based on Remote Sensing Data: A Semiarid Rangeland Case by Juan José Martín-Sotoca, Ernesto Sanz, Antonio Saa-Requejo, Rubén Moratiel, Andrés F. Almeida-Ñauñay, Ana M. Tarquis

    Published 2024-09-01
    “…Notably, November to the beginning of February showed an average increase of 20–30% in the predictability of vegetation anomalies, knowing moisture soil anomalies four lags in advance. We found other periods of relevant increment in the predictability, such as March and April for Los Vélez, and from July to September for Bajo Aragón.…”
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  14. 94

    Pooled error variance and covariance estimation of sparse in situ soil moisture sensor measurements in agricultural fields in Flanders by M. G. A. Hendrickx, M. G. A. Hendrickx, J. Vanderborght, J. Vanderborght, P. Janssens, P. Janssens, P. Janssens, S. Bombeke, E. Matthyssen, A. Waverijn, J. Diels, J. Diels

    Published 2025-06-01
    “…<p>Accurately quantifying errors in soil moisture measurements from in situ sensors at fixed locations is essential for reliable state and parameter estimation in probabilistic soil hydrological modeling. …”
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  15. 95

    Lablab purpureus: Evaluation and Selection of Drought-tolerant - High-yielding Accessions in Dry Farming Systems Based on Drought Tolerance Indices and Multi-environmental Yield Tr... by Julius Missanga, Patrick Ndakidemi, Pavithravani Venkataramana

    Published 2023-03-01
    “…Three sites from different agro-ecological conditions were selected for the study and each site involved trials with moisture stress-free (MSF) and early terminal moisture stress (TMS) conditions. …”
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  16. 96

    Effect of melamine urea formaldehyde (MUF) resin on some properties of moisture resistant P5 type particle boards by Mehmet Erdal Kara

    Published 2025-06-01
    “…In this study, the effect of specially produced melamine urea formaldehyde (MUF) resin was investigated to improve the water and moisture resistance properties of particle boards. …”
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  17. 97

    Comparison of Recent Remote Sensing Data Using an Artificial Neural Network to Predict Soil Moisture by Focusing on Radiometric Indices by Miraç Kılıç, Recep Gündoğan

    Published 2022-12-01
    “…RMSE values of MLP models were found to be respectively 0.79, 1.16 and 1.17 for Landsat 9 (OLI-2), Landsat 8 (OLI) and Sentinel 2A (MSI). …”
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  18. 98

    Storage effect on the moisture content (%) and sensory quality parameters of silver carp (Hypophthalmichthys molitrix) fish noodles and consumers’ preference to it by M. I. Hossain

    Published 2020-12-01
    “…The present study was conducted to assess the changes in percent moisture content and sensory quality parameters of noodles prepared with silver carp mince along with wheat flour and to study the consumer’s preference to the fish noodles. …”
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  19. 99

    Machine Learning Modelling for Soil Moisture Retrieval from Simulated NASA-ISRO SAR (NISAR) L-Band Data by Dev Dinesh, Shashi Kumar, Sameer Saran

    Published 2024-09-01
    “…The study found that the random forest regression technique produced the most precise soil moisture estimations for soybean fields, with an R<sup>2</sup> of 0.89 and RMSE of 0.050 without considering vegetation effects and an R<sup>2</sup> of 0.92 and RMSE of 0.042 considering vegetation effects. …”
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  20. 100