Summer crops: relative water use efficiencies and legacy impacts in farming systems

Take home message • While summer crops offer rotational options in the farming system, choose the correct crop to match your available soil water and crop history • Sorghum is a reliable performer often exceeding other options in terms of $returned per mm used • Cotton and maize require higher water availability and produce less reliable WUE ($/mm). However, cotton has legacy impacts on water availability for subsequent crops that should be considered • Mungbean can produce higher $/mm in low water availability situations ( 150 mm of plant available water will maximise crop WUE and profitability. Every extra mm at sowing could be worth as much as$35-70 extra return/ha • Higher density sorghum crops may provide greater crop competition against weeds and potential upside yield benefits in good season. We have seen limited legacy benefits (e.g. improved ground cover) or costs (e.g. greater soil water/nutrient extraction) for soil water or nutrient availability

Water, nitrogen, crown rot and common root rot interact to limit wheat production in northern NSW cropping systems

A multi-variate approach was undertaken to identify the major components of the cropping system that interact to affect yield and water use efficiency (WUE) in wheat in northern NSW. The major components identified from an on-farm monitoring program were rainfall, soil plant available water (PAW) and nitrogen (N) at sowing, grass weeds (GW), crown rot (CR) and common root rot (CRR). Combined, these factors accounted for 80% and 60% of the variation in yield and WUE, respectively. Principal components analysis showed that the region has two seasons; summer and winter, and cluster analysis identified six rainfall zones. The three northern zones have summer dominant rainfall patterns, while the three southern zones have uniform patterns. In general, rainfall declines and variability increases moving in a westerly direction. There were 12 major soil types identified and plant available water capacity (PAWC) ranged from 45 mm (red kurosol) to 221 mm (brown vertosol). While PAWC is largely determined by clay content, sub-soil sodicity (based on exchangeable Na percentage = ESP) and salinity also reduced the amount of plant available water (PAW). The impact of ESP on PAWC in the vertosols varied, as the negative effect of high ESP was off-set by electrolyte concentrations and the fact that these soils can ‘self—repair’ by cracking. In the low to medium clay content sub-soils that have no shrink-swell capability, high ESP caused major reductions in PAWC and this effect started at ESP values below 6%. A multiple regression model, set at mean in-crop rainfall of 263 mm, predicted yields (kg/ha) for the maximum, or best observed values, for each variable (holding the other four at their mean value) as: soil N at sowing 3164, PAW at sowing 3124, CR severity 2966, CR severity 2990 and GW at tillering 3120. Yield differences between these predicted values and the mean (2847 kg/ha) were 317, 277, 119, 143 and 273 kg/ha, respectively. Yield gains for each of these components were minimal. While PAW and N at sowing were the main components that drive the system, these model outcomes show that optimising only one component if the others are sub-optimal will not realise a substantial yield gain. Holding PAW at sowing and rainfall at average values, with N not limiting (200 ng/ha), eliminating grass weeds and disease resulted in a predicted yield of 3983 kg/ha which is a gain of 40% over the mean. This equates to a WUE of 12 kg/ha/mm. To maximise yield, growers need to target all of these components within a cropping system. Fallows that retain stubble residue now dominate the cropping system and N use has risen substantially in the last 15 years. The interaction between water, N, CR and CR on wheat yield and water use was examined in a replicated experiment. The incidence of the CR pathogen, Fusarium pseudograminearum (F.ps) increased under drought conditions and the application of N, while the incidence of the CR pathogen, Bipolaris sorokiniana (B.so) increased under non—water limited conditions. F.ps led to a reduction in grain number per head and grain weight, while B.so reduced yields through the reduction of tiller density and grain weight. Yield loss due to the interaction between these disease components in the absence of severe plant water stress is discussed. Zero-tillage cropping system strategies are proposed that target high and low PAWC soils and N fertility. How growers might manage these diseases under these different cropping system regimes is discussed

Farming system profitability and impacts of commodity price risk

Take home messages • Large gaps in profitability are possible between the best and worst systems – differences of $92-494/ha per year were found between systems at each site • Intensity is the major factor driving good/poor economic performance of the farming system - more so than crop choice. Matching intensity to environmental potential seems to be the most important lever to optimise farming system profitability • Increasing crop intensity increased costs and risks, but potentially higher crop income wasn’t realised over the dry run of seasons and hence has produced lower gross margins than more conservative systems • Lower crop intensity had lower system gross returns, but because of lower inputs and costs may achieve a more favourable return on investment at lower risk when there are limited planting opportunities. These systems have achieved lower gross margins than the baseline system in all but one comparison • Increasing legume frequency has the potential to capitalise on favourable legume prices but using long-term prices has rarely exceeded gross margins of baseline systems • Increasing nutrient supply incurred higher costs and required favourable seasonal conditions to increase grain yields and gross margins – this rarely occurred over the experimental years (excluding Trangie 2016 and Emerald 2017 where significant crop responses were obtained) • Systems involving crops with higher price variability (e.g. pulses, cotton) had limited downside risk but increased upside opportunities of higher economic returns. Even when comparing recent and long-term grain prices, the relative profitability ranking of systems rarely changed • Selecting a crop system is a long-term decision with unknown future yield and prices, hence choose systems that maximise system productivity and resilience, rather than responding to current commodity prices