Soil health indicators for Central Washington orchards

Soil health assessment can be a critical soil testing tool that includes biological and physical indicators of soil function related to crop and environmental health. Soil health indicator minimum data sets should be regional and management goal specific. The objective of this study was to initiate the steps to develop a soil assessment tool for irrigated orchard soils in Central Washington, United States including defining objectives, gathering baseline data and selecting target indicators. This study measured twenty-one biological, physical and chemical properties of soils in irrigated Central Washington apple orchards including indicators of water availability, root health, fertility, and biological activity. Soil factors were related to fruit yield and quality. Principal components and nonlinear Bayesian modeling were used to explore the relationship between soil health indicators and yield. Soil indicators measurements in Washington state orchards varied widely but generally had lower organic matter, available water capacity, wet aggregate stability and higher percent sand than in other regions. Linear mixed effects models for available water capacity and percent sand showed significant effects on yield, and models for root health ratings and Pratylenchus nematodes had moderate effects. The minimum dataset of soil health indicators for Central Washington orchards should include measurements of water availability (available water capacity, percent sand) and of root health (bean root health rating, Pratylenchus nematodes) in addition to standard fertility indicators to meet stakeholder management goals.

BALANÇO HÍDRICO CLIMATOLÓGICO E CLASSIFICAÇÃO CLIMÁTICA PARA O MUNICÍPIO DE PARANAVAÍ, PARANÁ

The study of climatic conditions of Paranavaí region is necessary due to its importance in the national agricultural scenario. The study aimed to calculate the climatological water balance (CWB) as well as performing the climate classification by the method of Thornthwaite e Mather for the municipality of Paranavaí, Paraná. Data from a historical series from 1975 to 2018 were used. For the calculation of the CWB was adopted the value of 100 mm for the available water capacity (AWC). The municipality studied presentes na annual average of 1523,8 mm precipitation and 1090,62 evapotranspiration. The municipality presented a trend climate o fone month of water deficiency (August) and eleven months of water excess (Setember to July). Regarding climate classification, was found C1dA’a’ climate, characterized as a mesothermic climate, with little or no water deficiency.

Determination of the effects of tillage on the productivity of a sandy loam soil using soil productivity models

Based on the hypothesis that soil properties and productivity components should be affected by different tillage methods, field and laboratory experiments were conducted to study the effects of zero tillage (ZT), one pass of disc plough tillage (P), one pass of disc plough plus one pass of disc harrow tillage (PH) and one pass of disc plough plus two passes of disc harrow tillage (PHH) on the distribution of the bulk density, available water capacity, pH, organic matter, available phosphorus, iron oxide and aluminium oxide at different soil depths, and their effects on the soil productivity. The available water capacity, pH, organic matter and available phosphorus were found to increase with the degree of tillage, while the bulk density, iron oxide and aluminium oxide were found to decrease with the degree of tillage. The results show that the soil productivity index was significantly (P ≤ 0.05) affected by the tillage methods and found to increase with the degree of tillage.

Mapping the Available Water Capacity in tropical climate soils for soybean (Glycine max) cultivation in the state of Tocantins-Brazil

Brazilian soybean has undergone considerable economic growth. Its production depends on the demand for some inputs. One of these inputs is the soil water supply, which can be made artificially or obtained by natural rainfall. Knowledge of available water capacity (AWC), which depends on total water availability (TWA), is poorly accessible and difficult to measure in the field. This study aimed to map the AWC of the state of Tocantins, based on pedotransfer functions (PTFs), to evaluate the water availability of the soils of the microregions of that state. We used the Arya and Paris model, aided by a computer program, Qualisolo, made by Embrapa Instrumentação. One hundred fifty-seven tropical soil samples were extracted from the Embrapa Solos portal. Preliminarily, the soil water retention curve (SWRC) was obtained and, subsequently, the TWA and AWC for this oilseed were estimated. Multiple linear regressions show the correlation between TWA and clay (CL), Silt (ST) and total sand (TS) contents. The correlation established was TWA = 3.2993 – 0.0028TS – 0.0034CL. This main conclusion reflects a fruitful AWC for decision-making by the soybean agribusiness and exposes the regional weaknesses for this crop under a rainfed regime in some regions of Tocantins. We could observe that, in terms of water availability, agribusiness is a potential threat to the environment protection area (APA) of the Ilha do Bananal/Cantão, Formoso River microregion.

Machine Learning-Based Modeling of Spatio-Temporally Varying Responses of Rainfed Corn Yield to Climate, Soil, and Management in the U.S. Corn Belt

Better understanding the variabilities in crop yield and production is critical to assessing the vulnerability and resilience of food production systems. Both environmental (climatic and edaphic) conditions and management factors affect the variabilities of crop yield. In this study, we conducted a comprehensive data-driven analysis in the U.S. Corn Belt to understand and model how rainfed corn yield is affected by climate variability and extremes, soil properties (soil available water capacity, soil organic matter), and management practices (planting date and fertilizer applications). Exploratory data analyses revealed that corn yield responds non-linearly to temperature, while the negative vapor pressure deficit (VPD) effect on corn yield is monotonic and more prominent. Higher mean yield and inter-annual yield variability are found associated with high soil available water capacity, while lower inter-annual yield variability is associated with high soil organic matter (SOM). We also identified region-dependent relationships between planting date and yield and a strong correlation between planting date and the April weather condition (temperature and rainfall). Next, we built machine learning models using the random forest and LASSO algorithms, respectively, to predict corn yield with all climatic, soil properties, and management factors. The random forest model achieved a high prediction accuracy for annual yield at county level as early as in July (R2 = 0.781) and outperformed LASSO. The gained insights from this study lead to improved understanding of how corn yield responds to climate variability and projected change in the U.S. Corn Belt and globally.

Impact of Land Management on Available Water Capacity and Water Storage of Peat

<p>In Germany, more than 95% of peatlands have been drained for agriculture and forestry leading to water as well as carbon storage loss, soil degradation, and water eutrophication. Soil available water capacity (AWC) is one of the most important soil properties regulating the water balance and plays a pivotal role in plant growth. Compared with that of mineral substrates, our understanding of the impact of land management on water storage and the AWC of peat is limited. In this study, we aimed to deduce possible alterations of the AWC and water storage of peat following land drainage and rewetting. We analyzed a comprehensive database (674 measurements from boreal and temperate peatlands) to seek relations between bulk density (BD), field capacity, wilting point, and AWC. Bulk density was used as a proxy for soil degradation. The AWC increases with BD up to a value of 0.2 g cm<sup>−3</sup>; a further increase in BD leads to a considerable decrease in AWC. The derived function between BD and AWC enables us to upscale the AWC to a regional scale. The average AWC of agricultural peatlands in Germany is estimated to be 37 ± 11 vol% (mean ± standard deviation). Currently, the water storage of agricultural peatlands in Germany is approximately 1.0 m<sup>3</sup> per m<sup>2</sup>. We estimated that water storage in the natural peatlands in Germany was 33.8 km<sup>3</sup> prior to drainage. Converting natural peatlands into agricultural land resulted in a water storage loss of approximately 18.6 km<sup>3</sup>. Several decades of peatland rewetting have a limited effect on water storage recovery due to a substantial loss of peat thickness because of former drainage and a low porosity of degraded peat.</p>