What is a Healthy Soil for Wine Grape Production? Assessing Soil Health Across California Vineyards

Objective #1: To develop a definition of soil health for wine grape vineyards that meets the unique production goals.

During the summer of 2020, we conducted semi-structured interviews to 15 wine grape growers of the Napa Valley region to understand their perception of soil health for wine grape production (Gonzalez-Maldonado et al., in preparation). These interviews were key for understanding the grower's knowledge, thoughts, and actions towards soil health and sustainable soil management practices. However, a quantitative approach was integrated to complement the assessment of  grower’s perception of soil health for vineyards, a crop that requires unique and specific practices and goals compared to other crops. Therefore, following Mann et al. (2019) as inspiration, farmers were asked to rate two areas where they believe their soils better reflected their production goals (an ideal soil) and the opposite (a challenging soil). After these soil ratings were made by farmers, we proceeded with the second objective of sampling soils and assessing soil health indicators in those exact sites. The purpose of rating soils is to quantify and understand the most important attributes of a soil for wine grape production by comparing them with quantitative soil health data. To complement the ratings, we asked growers to provide a set of detailed information on soil management practices to be integrated into the analysis. 

Objective #2: To assess the variability of diverse soil health indicators in vineyards across the Napa Valley region.

Samplings

This project took place in 32 vineyards from Napa Valley, California with the collaboration of the Napa Valley Grape Growers Association and 16 local wine grape growers. Soil sampling, preparation, and storage happened from late February to May of 2021 upon growers' availability for collaboration. Soil samples were taken from selected representative areas of each vineyard and rating (ideal and challenging soils) guided by the grower. Samples were taken for two depth intervals (0-10 cm and 10-20 cm) and two locations (vine row and tractor row). The sampling was divided into two depths and two locations due to organic material inputs and microbial activity usually being higher in the top depth of soils and differences in inputs from differing plants growing. For instance, growers grow cover crops in the tractor rows (or alleys) which might drive different results compared to the vines row. Three sample replicates were taken per vineyard leading to a total of 384 soil samples. The geographic coordinates of the sampling locations were recorded to categorize each vineyard into a soil type (or soil cluster) classification system. Additionally, soil taxonomy information was collected using the SoilWeb online tool (https://casoilresource.lawr.ucdavis.edu/gmap/) including soil textural class and soil series. 

For this grant, focus was given to the soil health indicators analyses performed in the laboratory. The laboratory soil health analyses were performed from August 2021 to December of 2022. After laboratory processing, data organization and analysis will happen from January to March 2023. The findings will be written starting in April of 2023 and will be presented during the summer of 2023. The project will conclude by July 31, 2023. The soil health analyses costs are covered by a grant awarded by the American Vineyard Foundation to the PI Dr. Cristina Lazcano and collaborators.

Soil management practices information:

A detailed list of soil management practices history was provided by growers of the previous three years prior to sampling for each area sampled. Examples of practices include tillage, no-tillage, disking, cover crops, compost applications, among others.

Soil health analyses

Soil Physical Properties

The soil physical properties quantified in this study were gravimetric soil moisture, water holding capacity, and soil texture. We assessed soil infiltration and soil compaction in the field but these remained out of the scope of this grant due to time limitations. In California, water is an important limiting factor, so we need to assess how much moisture potential and availability there is in the soils. Gravimetric soil moisture was measured by calculating the difference between field moist soil and dried soil (105 C°). The available water holding capacity was quantified from capillary soil saturation at field capacity of dried soil. Soil texture was quantified to determine particle size following the rapid method described in Kettler et al 2001. The soil texture method allowed us to classify our soil types according to textural class. 

Soil Chemical properties:

Soil pH and electrical conductivity (EC) were measured in a 2:1 (soil:water) paste using a pH and EC electrode (Fisher Scientific, Waltham, MA). Soil pH and salinity (obtained through EC) are important factors that drive soil biological processes including plant growth. Also, soil organic matter % was calculated from total C assessed through dry combustion. Permanganate oxidizable carbon (POXC) was assessed to estimate the active carbon pool of the soil organic matter (Culman et al., 2012). Organic matter has been shown to be an important factor in soil health, so total soil organic matter is an overall good indicator of soil quality. However, active carbon, in particular, has been shown to be sensitive to short and long-term management practices (Culman et al 2012) and is also related to the amount of carbon that could be mineralized; so, this indicator is important to determine how much soil organic carbon will be eventually lost as CO2 rather than being stabilized in the soil (Hurisso et al 2016). Quantifying both total and active soil organic matter is a good way of considering the spectrum of soil organic matter in the soil. Soil organic matter is one of the main drivers of soil health since it has the capacity to influence other soil properties for good like water infiltration, reduce soil erosion, increase soil microbial diversity, achieve higher yields in some crops, among others. 

Soil Biological Properties:

Soil biological properties, especially soil microbial diversity and activity, are one of the most important soil properties and drivers of soil health but this area remains largely understudied due to its complexity. Soil microorganisms are essential drivers of key soil processes for agriculture and environmental quality like nutrient cycling, soil organic matter turnover and stabilization, nutrient availability, aggregate stability and reduced soil erosion, water filtration, pest suppression, among others. We used several methods that have been shown to provide useful general information regarding microbial diversity and activity like soil respiration, potentially mineralizable nitrogen, and Phospholipid fatty acids. Soil microbial respiration was measured using a LICOR-850 infrared gas analyzer that quantifies CO2 respired by microorganisms from re-wetted soil samples to 50% water holding capacity and incubated (2 days) in an air-sealed gas jar. Microbial respiration is an indicator of how active soil microorganisms can be when adequate moisture is added. Also, potentially mineralizable N (PMN) was estimated by measuring ammonium and nitrate produced in incubated soils under anaerobic conditions for 7 days in the laboratory (Moebius-Clune et al. 2016). Measuring PMN helps us understand potential nitrogen, which is one of the most needed and limited nutrients, for cycling and availability for plants. Soil microbial diversity was analyzed by a commercial laboratory through a phospholipid fatty acid (PLFA) assay from the 0-10 cm depth which is where typically most microorganisms are concentrated in the soil. The PLFA method is great for studying the structure of the soil microbial community by differentiating bacterial and fungal microorganisms. Studying soil biodiversity helps us understand what type of organisms are present in the soil and obtain an idea of functions they could carry which can have different impacts on nutrient cycling and availability, soil carbon, and ultimately in soil health.

Statistical Analyses    

The interviews were analyzed by following inductive coding and a grounded theory approach. In summary, the codes are keywords identified and grouped as main ideas from the growers answers. Inductive coding means that codes were not predetermined prior to data analysis but emerged from the interviewee responses.

We evaluated growers’ soil rating factors and quantitative soil health data performing a general linear model using the soil health ranking as response variables, and grower rating, and depth as fixed effects using the "glmmPQL" function from the MASS package (Venables and Ripley, 2002) in RStudio (RStudio Team, 2020). Additionally, descriptive statistics like ranges, medians, averages, and standard deviations were calculated for each soil health indicator. Data from the interviews and growers' ratings were compared to meet objective 1. The relationship between biological, physical and chemical soil health indicators were studied through multivariate statistics such as Principal Component Analysis (PCA). Data visualization using the "ggplot2" (Wickham H, 2016) function from RStudio of descriptive statistics was performed to understand soil health indicators trends by soil type and grower rating in the Napa Valley Area.