Robert R. Schindelbeck

Farmer-oriented assessment of soil quality using field, laboratory, and VNIR spectroscopy methods

Soil quality and health are terms describing similar concepts, but the latter appeals to farmers and crop consultants as part of a holistic approach to soil management. We regard soil health as the integration and optimization of the physical, biological and chemical aspects of soils for improved productivity in an economic and sustainable manner. This paper describes the process used for the selection of soil quality/health indicators that comprise the new Cornell Soil Health Test. Over 1,500 samples collected from controlled research experiments and commercial farms were initially analyzed for 39 potential soil quality indicators. Four physical and four biological indicators were selected based on sensitivity to management, relevance to functional soil processes, ease and cost of sampling, and cost of analysis. Seven chemical indicators were also selected as they are part of the standard soil nutrient test. Soil health test reports were developed to allow for an overall assessment, as well as the identification of specific soil constraints. The new soil health test is being offered on a for-fee basis starting in 2007. In addition, visible near infrared reflectance spectroscopy was evaluated as a possible tool for low-cost soil health assessment. From preliminary analyses, the methodology shows promise for some but not all of the soil quality indicators. In conclusion, an inexpensive soil health test was developed for integrative assessment of the physical, biological, and chemical aspects of soils, thereby facilitating better soil management.

Soil and maize response to plow and no-tillage after alfalfa-to-maize conversion on a clay loam soil in New York

No-tillage in association with row crop production is generally believed to be poorly adapted to fine-textured soils, especially in temperate humid climates. The relative success of conservation tillage may be impacted by changes in soil structure. The objective of this study is to evaluate the performance of reduced tillage systems after rotation from a perennial sod crop. An experiment involving spring and fall moldboard plow till (PT), no-till (NT)/zone till (ZT), and ridge till (RT) under maize (Zea mays L.) production following alfalfa (Medicago sativa L.) was conducted on a Kingsbury clay loam soil (Gleyic Luvisol) in Northern New York. Soil water content, strength and temperature, plant height, leaf area and number, leaf, stem and root biomass, and root distribution were measured during the 1992 and 1993 growing seasons for spring PT and NT, while from 1994 to 1999 only yield measurements were made. Tillage in 1992 occurred under adequately dry conditions, but in 1993 under partially plastic consistency state, resulting in an underconsolidated plow layer. Soil water contents were generally higher for NT than PT in 1992, but equal in 1993. Root proliferation was good in the subsoil although soil strengths were generally above the 2 MPa level, suggesting that penetrometer measurements are not a good indicator of rooting potential in a well-structured soil. Soil strength was higher in both years under NT, and under both tillage treatments was negatively related to soil water content, except in the surface layer where soil penetrability appears mostly affected by aggregate arrangement. NT recorded higher plant heights, leaf area index and leaf numbers in 1993, while PT recorded higher per plant leaf area, stem and root biomass. Roots were generally more abundant under PT than NT at all depths, and were reduced in trafficked inter-row areas. Maize yield was significantly higher under PT in 1992, but similar to NT in 1993. Further yield data from 1994 to 1999 indicate that reduced tillage systems can perform equally or better compared to fall PT on this soil type. Spring PT generally yields lower than fall PT, NT/ZT, and RT. In general, long-term use of reduced tillage systems is economical on well-structured clay loam soils if adequate consideration is given to maintaining soil structure. # 2000 Elsevier Science B.V. All rights reserved.

Use of an integrative soil health test for evaluation of soil management impacts.

Understanding the response of soil quality indicators to changes in management practices is essential for sustainable land management. Soil quality indicators were measured for 2 years under established experiments with varying management histories and durations at four locations in New York State. The Willsboro (clay loam) and Aurora (silt loam) experiments were established in 1992, comparing no-till (NT) to plow-till (PT) management under corn ( Zea mays L.)–soybean ( Glycine max L.) rotation. The Chazy (silt loam) trial was established in 1973 as a factorial experiment comparing NT versus PT and the crop harvesting method (corn silage versus corn grain). The Geneva (silt loam) experiment was established in 2003 with vegetable rotations with and without intervening soil building crops, each under three tillage methods (NT, PT and zone-till (ZT)) and three cover cropping systems (none, rye and vetch). Physical indicators measured were wet aggregate stability (WAS), available water capacity (AWC) and surface hardness (SH) and subsurface hardness (SSH). Soil biological indicators included organic matter (OM), active carbon (AC), potentially mineralizable nitrogen (PMN) and root disease potential (RDP). Chemical indicators included pH, P, K, Mg, Fe, Mn and Zn. Results from the Willsboro and Aurora sites showed significant tillage effects for several indicators including WAS, AWC, OM, AC, pH, P, K, Mg, Fe and Mn. Generally, the NT treatment had better indicator values than the PT treatments. At the Chazy site, WAS, AWC, OM, AC, pH, K and Mg showed significant differences for tillage and/or harvest method, also with NT showing better indicator values compared to PT and corn grain better than corn silage. Aggregate stability was on average 2.5 times higher in NT compared to PT treatments at Willsboro, Aurora and Chazy sites. OM was also 1.2, 1.1 and 1.5 times higher in NT compared to PT treatments at Willsboro, Aurora and Chazy sites, respectively. At the Geneva site WAS, SH, AC, PMN, pH, P, K and Zn showed significant tillage effects. The cover crop effect was only significant for SH and PMN measurements. Indicators that gave consistent performance across locations included WAS, OM and AC, while PMN and RDP were site and management dependent. The composite soil health index (CSHI) significantly differentiated between contrasting management practices. The CSHI for the Willsboro site was 71% for NT and 59% for PT, while at the Aurora site it was 61% for NT and 48% for PT after 15 years of tillage treatments.

EVALUATION OF LABORATORY-MEASURED SOIL PROPERTIES AS INDICATORS OF SOIL PHYSICAL QUALITY

Routine soil analyses provide an approach for assessment and monitoring of soil quality and targeted implementation of management practices, but suitable indicators are mostly undefined. We used three long-term experiments on several soil types where maize (Zea mays L.) was grown under different tillage (no till and plow till), rotation (continuous maize and maize after grass), and harvesting (silage and grain) methods to identify suitable indicators for evaluating soil physical quality. Disturbed and undisturbed soil samples were collected, and laboratory-based analyses were performed for water-stable aggregation, saturated hydraulic conductivity, several pore size parameters, penetration resistance at &PSgr; = −10 MPa, and bulk density. Sensitivity to management, expense of measurement, measurement consistency, and relevance to critical physical soil processes were used as criteria to evaluate indicator suitability. Indicators varied significantly seasonally and by soil type, and several showed significant differences and trends between management treatments. Small water-stable aggregates (0.25-2 mm) showed the most consistent and significant treatment differences. Bulk density, available water capacity, and air-filled pores at field capacity (PO > 30) were also related to treatment effects and had low variability. Penetration resistance and effective porosity (PO > 0.2) were not sensitive to management practices, whereas aeration pores and saturated hydraulic conductivity were too variable to use as indicators. Several indicators measured on undisturbed cores may be predicted from those measured from disturbed samples using pedotransfer functions. Small water-stable aggregates (0.25-2 mm), available water capacity, bulk density, and PO > 30 appear most promising as indicators for routine evaluation and monitoring of soil physical quality.

Evaluation of the PNM model for simulating drain flow nitrate-N concentration under manure-fertilized maize

Mathematical models may be used to develop management strategies that optimize the use of nutrients from complex sources such as manure in agriculture. The Precision Nitrogen Management (PNM) model is based on the LEACHN model and a maize N uptake/growth and yield model and focuses on developing more precise N management recommendations. The PNM model was evaluated for simulating drain flow nitrate-nitrogen (NO3-N) in a 3-yr study involving different times of liquid manure application on two soil textural extremes, a clay loam and a loamy sand under maize (Zea mays, L.) production. The model was calibrated for major N transformation rate constants including mineralization, nitrification and denitrification, and its performance was tested using two different calibration scenarios with increasing levels of generalization: (i) separate sets of rate constants for each individual soil type and (ii) a single set of rate constants for both soil types. When calibrated for each manure application treatment for each soil type, the model provided good simulations of monthly and seasonal drain flow NO3-N concentrations. The correlation coefficient (r) and Willmott’s index of agreement (d) ranged from 0.63 to 0.96 and 0.72 to 0.92, respectively. The calibrated model performed reasonably well when rate constant values averaged over manure application treatment for each soil type were used, with r and d values between 0.54 and 0.97, and 0.70 and 0.94, respectively, and greater accuracy for the clay loam soil. When rate constant values were averaged over manure application treatments and soil types, model performance was reasonably accurate for the fall time manure application on the clay loam (r and d of 0.60 and 0.91 and 0.72 and 0.92, respectively) and satisfactory for the spring time on the clay loam and the fall and spring times for the loamy sand soil (r and d between 0.56 and 0.90 and 0.58 and 0.84, respectively). The use of the model for predicting N dynamics under manure-fertilized maize cropping appears promising.

Developing Standard Protocols for Soil Quality Monitoring and Assessment

Africa’s agricultural viability and food security depend heavily on its soil quality. However, while approaches to measuring air and water quality are widely established, standardized, publicly-available soil quality assessment protocols are largely non-existent. This chapter describes the process we have used in selecting and developing a set of inexpensive, agronomically meaningful, low-infrastructure-requiring indicators of soil quality (SQ), which make up the Cornell Soil Health Test (CSHT). In 2006, the CSHT was made available to the public in New York State (NYS), United States, similar to the widely available soil nutrient tests. Case studies show the CSHT’s success at measuring constraints in agronomically essential soil processes and differences between management practices in NYS. It thus helps farmers to specifically target management practices to alleviate quantified constraints. Such indicators have the potential to be developed into standardized soil quality tests for use by African agricultural non-governmental and government organizations and larger commercial farmers to better understand agricultural problems related to soil constraints and to develop management solutions. Low cost and infrastructure requirements make these tests excellent tools for numerous low-budget extension and NGO-based experiments established in collaboration with local small farmers, as well as to quantify the status and trends of soil degradation at regional and national scales.

Dynamic Model Improves Agronomic and Environmental Outcomes for Maize Nitrogen Management over Static Approach

Large temporal and spatial variability in soil nitrogen (N) availability leads many farmers across the United States to over-apply N fertilizers in maize ( L.) production environments, often resulting in large environmental N losses. Static Stanford-type N recommendation tools are typically promoted in the United States, but new dynamic model-based decision tools allow for highly adaptive N recommendations that account for specific production environments and conditions. This study compares the Corn N Calculator (CNC), a static N recommendation tool for New York, to Adapt-N, a dynamic simulation tool that combines soil, crop, and management information with real-time weather data to estimate optimum N application rates for maize. The efficiency of the two tools in predicting the Economically Optimum N Rate (EONR) is compared using field data from 14 multiple N-rate trials conducted in New York during the years 2011 through 2015. The CNC tool was used with both realistic grower-estimated potential yields and those extracted from the CNC default database, which were found to be unrealistically low when compared with field data. By accounting for weather and site-specific conditions, the Adapt-N tool was found to increase the farmer profits and significantly improve the prediction of the EONR (RMSE = 34 kg ha). Furthermore, using a dynamic instead of a static approach led to reduced N application rates, which in turn resulted in substantially lower simulated environmental N losses. This study shows that better N management through a dynamic decision tool such as Adapt-N can help reduce environmental impacts while sustaining farm economic viability.

Using Air Pressure Cells to Evaluate the Effect of Soil Environment on the Transmission of Soilborne Viruses of Wheat

ABSTRACT An air pressure cell, a laboratory tool that precisely controls soil matric potential, was utilized in a novel approach to investigate the epidemiology and management of soilborne disease. Matric potentials of -1, -5, -20, and -40 kPa were established in cores of field soil infested with Wheat soilborne mosaic virus (WSBMV) and its presumed vector Polymyxa graminis. Equilibrated soil cores were planted to wheat (Triticum aestivum), and after intervals of growth under controlled environment, virus transmission was assessed by serological detection of the virus in washed roots. Transmission occurred at all but the driest soil matric potential tested, -40 kPa, in which only pores with a diameter of 7.4 mum or less were water-filled, possibly obstructing movement of P. graminis zoospores. By starting plants at -40 kPa for 10.5 days and then watering them to conducive matric potential, we found that WSBMV transmission occurred between 12 to 24 h at 15 degrees C, and within 36 h at 20 degrees C. No significant transmission occurred within 96 h at 6.5 degrees C. In contrast, transmission of Wheat spindle streak mosaic virus (WSSMV) did not occur at 15 degrees C (the only transmission temperature tested), suggesting either that WSSMV is unable to establish infection at 15 degrees C or that a different vector is involved. The air pressure cell is a novel tool with many potential applications in research on the epidemiology and management of soilborne pathogens. Applications of the precise environmental control attained through the use of air pressure cells range from assessing the effects of cultural practices on soilborne inoculum to standardized virulence assays for soilborne pathogens to preliminary screens of host resistance and pesticide efficacy.

Distribution, Impact, and Soil Environment of Phoma sclerotioides in Northeastern U.S. Alfalfa Fields

We report brown root rot (BRR) of alfalfa, caused by the fungal pathogen Phoma sclerotioides, for the first time in the eastern United States. Alfalfa production fields in New York, Vermont, and New Hampshire were sampled in spring 2005, and soil characteristics were related to variability in BRR incidence and severity in two New York fields sampled extensively. BRR was detected in 8 of 10 fields sampled in New York, 6 of 7 fields sampled in Vermont, and 5 of 6 fields sampled in New Hampshire. Lesions on both roots and crowns were common in all three states, and most BRR lesions extended into the cortical tissues. Diagnostic polymerase chain reaction (PCR) of P. sclerotioides isolates produced a single amplicon of the expected size. In vivo conidia and pycnidia morphology of northeastern isolates was consistent with published descriptions of P. sclerotioides, and P. sclerotioides was reisolated from symptomatic lesions after pathogenicity testing. In two New York fields sampled extensively, BRR severity varied with soil strength, soil texture, soil saturation, and alfalfa stand density. The spatial pattern of BRR within fields suggests the pathogen was not recently introduced. The results suggest BRR is widespread in alfalfa production fields in New York, Vermont, and New Hampshire.

Using Soil Health Indicators to Follow Carbon Dynamics in Disturbed Urban Environments – A Case Study of Gas Pipeline Right-of-Way Construction

Intense use of urban soils causes perturbations in soil ecosystem functioning. Construction activities often involve soil removal, compaction by heavy equipment, mixing of topsoil and subsoil materials, etc. Urban soil environments share many of the same properties of soils found in other areas of managed and natural systems. The Cornell Soil Health Test (CSHT) can be used as a tool to evaluate these negative impacts through a holistic soil assessment framework which provides an evaluation of indicators of soil physical and biological and chemical processes. The suite of soil tests in the CSHT measures key soil processes. Land managers use the CSHT to first identify the soil quality functional constraints and then adapt soil management to address identified limitations.