Xia Vivian Zhou

Crop rotations, cover crops, and poultry litter (PL) under no tillage (NT) may improve soil health and crop yields. However, farmers’ adoption depends on whether they can generate extra profits. This study evaluated profitability of NT corn (Zea mays L.) in monoculture versus rotations with soybean (Glycine max L.) and cotton (Gossypium hirsutum L.) with or without winter covers from 2002 to 2017. Whole‐block treatments were cropping rotations with monoculture (control) versus nine, 4‐yr cropping sequences (phases) repeated four times (I, II, III, and IV). Split‐block treatments were no cover versus winter covers of PL, hairy vetch (Vicia villosa L.), and wheat (Triticum aestivum L.). Different phases influenced yields and net returns (NRs; p < .05), with the greatest NRs in Phase IV, and the lowest in Phase III. Rotation interacted with phase to influence corn yield and NRs (p < .01), with positive rotation effects occurring in Phase IV. Covers influenced yields and NRs over 16 yr (p < .01). Vetch cover resulted in the highest corn yields, whereas wheat cover was the lowest. However, no cover plots produced NRs greater than any other cover. Enhanced yields or cost savings due to reduced fertilizer from covers did not offset cover costs. Lowering costs of PL, hairy vetch, and wheat by 70, 68, and 100%, respectively, from their base values produced equivalent NRs to no cover. Thus, farmers may need subsidies to adopt conservation agriculture‐based practices.

Pennycress can be used as a renewable biomass because its harvested seeds can be converted into biofuel, supplying, for example the aviation industry. Pennycress can be adopted as a winter cover crop to make extra profit in addition to summer cash crops. This study ascertains influences on row crop farmers’ interest in growing pennycress to supply a biofuels industry. The study uses data from a survey of row-crop farmers in seven US states. Effects of farm and farmer attributes on acceptance of a farmgate pennycress price are measured. Nearly 58% were interested in growing pennycress if profitable. Among those interested, 54.4% would accept the farmgate pennycress price offered. Positive influences on interest included farm size, education, and familiarity with pennycress, while concern about knowledge on growing pennycress, and use of no-till practices had negative influences. Farmers aged 40 to 65 were more likely to accept the price, while share of rented hectares and no debt had positive influences. More risk-averse farmers and those using no-till were less likely to accept. Results suggest that the majority of row crop farmers would be interested in growing pennycress if profitable, while the overall willingness to accept the farmgate price was when it was at $0.28/kg.

Crop rotations, cover crops, and manures may enhance yields, improve soils, and provide other ecosystem services. However, farmers may be reluctant to adopt the aforementioned practices because of uncertain profits. This study determined the profitability of cotton (Gossypium hirsutum L.) rotated with other crops and also utilizing cover crops and poultry litter (PL). Whole‐block treatments were 10 sequences of no‐tillage cotton, corn (Zea mays L.), and soybean [Glycine max (L.) Merr.] at Milan, TN. Sequences were repeated in 4‐yr cycles called Phases (Phases I, II, III, and IV) starting in 2002 and continuing through 2017 to assess effects of consecutive applications of sequences on cotton net returns (NRs). Split‐block treatments included winter wheat (Triticum aestivum L.), hairy vetch (Vicia villosa L.), PL, and fallow. The ANOVA was used to determine treatment NR differences compared to continuous cotton and fallow for 2002–2017 and for each Phase. Including soybean and corn in rotation with cotton did not positively affect cotton NRs in Phases I, II, and III. Droughts may explain lack of yield and NR response in Phases II and III. However, including soybean and corn in the rotation provided higher cotton NRs in Phase IV (2014–2017). Better weather and improved soils with residue diversity in Phase IV may explain higher yields and NRs of cotton in rotation with other crops. For cover crops and PL, yield benefits and/or N fertilizer savings did not offset input costs, indicating monetary incentives may be needed for famers to include these practices in their cropping system.

Farmers may be reluctant to adopt variable rate nitrogen (VRN) management because of uncertain profits. This study assessed field landscape, soil, and weather effects on optical sensing (OS)-based VRN on cotton (Gossypium hirsutum L.) N rates, yields, and net returns (NRs). Field data were collected from 21 locations in Louisiana, Mississippi, Missouri, and Tennessee, USA, between 2011 and 2014. Data included yields, N rates, and NRs for the farmer practice (FP), OS-based VRN, and OS-based VRN supplemented with other information. Production data were augmented with landscape, soils, and weather data, and ANOVA and logistic regressions were used to identify field conditions where VRN was profitable, provided risk management benefits, and improved N efficiency. Key findings indicate that NRs were improved with VRN by applying additional N on more erodible soils. Higher organic matter soils also benefited from VRN through enhanced yields and NRs. VRN may also have provided risk management benefits by providing a lower probability of NRs below NRs for the FP on soils associated with greater water-holding capacity, higher organic matter levels, or deeper profiles. Results from this study may help identify farm fields with similar characteristics for adoption of VRN management.

Core Ideas: Urea + NBPT and PCU provided significantly higher mean yields and net returns than conventional urea. Urea + NBPT and PCU provided significantly lower yields and net returns than ammonium nitrate. Urea + NBPT and PCU offer greater potential to improve net returns than urea + MICP. This study determined the effects of enhanced efficiency (EE) urea fertilizers relative to ammonium nitrate (AN) on no‐tillage (NT) corn (Zea mays L.) yields and net returns (NRs) in Tennessee. Corn yields were from experiments conducted at two N fertilization rates of 123 and 168 kg ha⁻¹ with four replications in a split‐plot design from 2013 through 2015 at three locations in middle (Springfield) and west Tennessee (Milan and Jackson). ANOVA analyses were used to identify differences in EE urea treatment yields and NRs. Breakeven and sensitivity analysis was used to compare yield and identify the threshold of positive NR of EE urea fertilizers relative to AN for a given premium price over conventional urea. Results indicated that urea + 20% or 26.7% N‐(n‐butyl)‐thiophosphoric triamide (NBPT) and polymer‐coated urea (PCU) provided significantly higher mean yields (2.0 Mg ha⁻¹ more on average) and NRs ($283 ha⁻¹ more) than conventional urea. Notwithstanding, these EE urea fertilizers had lower yields and produced lower benefits than AN in the course of this study. On the other hand, mean yield (8.7 Mg ha⁻¹) and NR ($1012 ha⁻¹) for urea + maleic–itaconic acid copolymer (MICP) were not significantly different from conventional urea (8.3 Mg ha⁻¹ and $959 ha⁻¹). In general, N fertilizer sources behaved similarly among N rates and locations. Given the growing reliance on urea fertilizer in NT corn production in Tennessee, urea + NBPT and PCU offer the greatest potential to improve expected NRs relative to conventional urea.

Core Ideas: Net returns were higher for conventional tillage than no‐tillage without cover crops. Net returns were higher for no‐tillage than conventional tillage with cover crops. A cotton producer would maximize profits by not planting cover crops. The objective of this study was to evaluate the long‐term effects of winter cover crops with and without tillage on profit‐maximizing N fertilization rate and net return for upland cotton (Gossypium hirsutum L.) production. Data came from a 29‐yr (1984–2012) cotton experiment located in Jackson, TN. The experiment included four cover crop treatments (no cover, winter wheat [Triticum aestivum L.], hairy vetch [Vicia villosa L.], and crimson clover [Trifolium incarnatum L.]); two tillage systems (no‐tillage [NT] and conventional tillage [CT]), and four N fertilizer rates (0, 34, 67, or 101 kg N ha⁻¹). Lint yield was de‐trended for temporal yield variation and quadratic yield response functions to N fertilizer were estimated for each cover crop and tillage system. Partial budgeting was used to determine the profit‐maximizing N rate and yields for each cover crop and tillage combinations under different cotton and N price scenarios. The highest profit‐maximizing N fertilizer rate savings, relative to no cover, under CT and NT were for cotton after clover, followed by cotton after hairy vetch and then cotton after wheat. Maximum net returns for cotton after hairy vetch, cotton after crimson clover, and cotton after wheat were lower than for cotton with no cover under CT and NT systems. The results show that revenue gains from producing cotton following cover crops did not offset the cost of cover establishment compared to cotton following no cover. A cotton producer would maximize profits by not planting cover crops under various price scenarios.

To improve irrigation management in the midsouthern United States, information is needed on the effects of irrigation on high available water holding capacity (AWHC) soils under humid, short‐growing season conditions. The objective of this research was to determine the effects of irrigation timing on lint yield, quality, and profit‐maximizing irrigation rates for cotton (Gossypium hirsutum L.) production in such an environment on high AWHC soils. Lint yield and quality data were collected during a 2006 to 2009 cotton irrigation experiment at Jackson, TN. Lint yield and adjusted price responses to total water (rainfall plus irrigation) were estimated as quadratic functions when irrigation was initiated at first square, first bloom, and mid‐bloom. The baseline rainfall scenario showed that the profit‐maximizing irrigation rate was 94 mm with lint yield of 1893 kg ha⁻¹ and net returns of US$2051 ha⁻¹ when irrigation was initiated at first square. For irrigation initiated at first bloom, the profit‐maximizing irrigation rate increased to 121 mm with lint yield of 2052 kg ha⁻¹ and net returns of $2213 ha⁻¹. Profit maximizing irrigation rate was 173 mm with lint yield of 2174 kg ha⁻¹ and net returns of $2361 ha⁻¹ when irrigation was initiated at mid‐bloom. Initiation of irrigation at mid‐bloom would maximize profits on high AWHC soils given the results of this research. However, there are some years in Tennessee when irrigating cotton will not increase expected net returns due to sufficient rainfall or insufficient heat‐unit accumulation to fully mature the crop.Core Ideas Determine the effects of irrigation timing on yield and profit maximizing irrigation rates for cotton production in humid short‐growing season on high available water holding capacity soils. Initiation of irrigation at mid‐bloom would maximize profits on high available water holding capacity soils given the results and costs described from this research. Baseline rainfall scenario shows that profit‐maximizing net return was US, 051, 213, and, 361 ha⁻¹ when irrigation was initiated at first square, first bloom, and mid‐bloom, respectively.

Over three million hectares of salt-affected soils characterized with high salinity and sodicity caused serious land degradation in Songnen Plain, northeast China. Soil salinity–sodicity heterogeneous distribution under microtopography is usually influenced by several environmental factors. The side direction movement of soil water driven by water from depression is the key factor that aggravates the soil salinization under microtopography in dry condition. In this study, the differences in surface soil salinity–sodicity (0–10 cm) between dry year and wet year were compared, and the relationship between soil salinity–sodicity and environment factors such as ground elevation, surface ponding time, surface ponding depth, and soil moisture at four soil layers (0–10, 10–30, 30–60, and 60–100 cm) were analyzed using redundancy analysis (RDA) and simple correlation analysis (Pearson analysis) for two different hydrological years. Analyzed soil salinity–sodicity parameters include soluble ions (Na⁺, K⁺, Ca²⁺, Mg²⁺, CO₃²⁻, HCO₃⁻, Cl⁻ and SO₄²⁻), salt content (SC), electrical conductivity (EC), sodium adsorption ratio (SAR), and pH. Results showed that values of SAR, Cl⁻, and SO₄²⁻ were significantly higher in dry year than in wet year, while Ca²⁺, Mg²⁺, K⁺, and HCO₃⁻ showed the opposite results. Values of Na⁺, CO₃²⁻, and EC were significantly higher at higher ground elevation gradient (20–40 cm) in dry year than wet year. Redundancy analysis indicated that spatial distributions and variations of salinity and sodicity in surface soil layer were related with environmental factors of ponding depth, ponding time and ground elevation in wet year, and they were related with ground elevation, ponding depth, ponding time, and soil moisture at 30–60 and 60–100 cm soil layer in dry year. Ponding depth and ground elevation rank first and second as the influential factors of the spatial distribution and variation of soil salinity–sodicity in wet year. However in dry year, primary and secondary influential factors are ground elevation and soil moisture at 60–100 cm soil layer.