Using Crop Models to Evaluate Climatic Yield Potential and Yield Gaps from Resource Limitation and Pest Damage

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Using Crop Models to Evaluate Climatic Yield Potential and Yield Gaps from Resource Limitation and Pest Damage K. J. Boote 1, J. W. Jones 1, J. B. Naab 2 & P. Singh 3 1 Univ. of Florida, 2 SARI-Ghana, 3 ICRISAT-India India Presented at AGRO21 - ESA Aug 29-Sep 3, 21

1 2 What are they? Production situation potential attainable Crop Model Concepts Yield increasing measures defining factors: CO2 radiation temperature crop characteristics -physiology, phenology -canopy architecture limiting factors: a: water b: nutrients -nitrogen -phosphorous 3 actual Yield protecting measures reducing factors: Weeds pests diseases pollutants 15 5 1, 2, Production level (kg ha -1 ) Source: World Food Production: Biophysical Factors of Agricultural Production, 1992.

Crop Models: Tools to Diagnose Yield Gaps Climatic Potential Yield (CPY): That attainable for the solar irradiance, temperature, daylength, and season length for a given location, assuming no limitations from water, N, fertility, or pests. CPY varies by site and season!!! Assumption: Set process inputs (e.g., Amax) and climatic sensitivities from literature. Calibrate model for fields with no resource or pest limitations. In new fields: run model with actual solar radiation, temperature, daylength, actual soil & mgt. Yield Gap defined: Where actual yield is less than predicted climatic potential yield. Is slope of DM accumulation less than simulated? What are causes? Soil infertility, soil water deficit, soil aeration, soil impedance, soil-borne pests, aerial pests. Genetics as a yield gap? If season is not fully used? Presented at AGRO21 - ESA Aug 29-Sep 3, 21

Accounting for Yield Gap of Peanut in Benin Decrease pop 11 to 6.6 plants/m2, add leafspot dis, SLFP from.92 to.85 Crop or Pod Mass, kg/ha 6 5 4 Std -Sim Pop - Sim Dis - Sim Fert - Sim Obs - B Obs - P 2 4 6 8 1 12 Days after Planting Peanut CRSP Project Florida, Benin

LEAF WEIGHT, kg/ha 14 a) Chinese, 1997 season 12 8 6 4 2 D1, DEF (Sim.) D3, DEF (Sim.) D1 (Sim.) D3 (Sim.) D1 (Obs.) D3 (Obs.) 15 2 25 3 35 24 b) F-Mix, 1997 season 16 12 8 4 15 2 25 3 35 JULIAN DAY Peanut CRSP J. Naab Ghana, Two peanut cult. Simulated with no disease effect Simulated with input defoliation to match observed. Crop had no fungicide applied

6 5 a) Chinese, 1998 1997 season 4 J. Naab Ghana, TOTAL BIOMASS, kg/ha 15 2 25 3 35 8 6 4 b) F-Mix, 1998 1997 season D1, DEF (Sim.) D3, DEF (Sim.) D1 (Sim.) D3 (Sim.) D1 (Obs.) D3 (Obs.) 15 2 25 3 35 Two peanut cult. Simulated with no disease effect Simulated with input defoliation and leafspot injury Crop had no fungicide applied JULIAN DAY Peanut CRSP Project Florida, Ghana

35 a) Chinese, 1997 season POD WEIGHT, kg/ha 25 15 5 4 35 25 15 5 15 2 25 3 35 b) F-Mix, 1997 season D1, DEF (Sim.) D3, DEF (Sim.) D1 (Sim.) D3 (Sim.) D1 (Obs.) D3 (Obs.) 15 2 25 3 35 JULIAN DAY J. Naab Ghana, Two peanut cult. Simulated with no disease effect Simulated with input defoliation and leafspot injury Crop had no fungicide applied Peanut CRSP Project Florida, Ghana

Yield gap (kg/ha) of peanut due to water deficit and biotic stress during 1997 in Ghana. Sowing Date Water nonlimiting (Sim) (1) Water limiting (Sim) 1 (2) Observed Pod Yield kg/ha (3) Yield Gap (water deficit) (1)-(2) Yield Gap (biotic stress) (2)-(3) Cultivar Chinese 29 May 2952 2866 3163 86-297 26 June 376 2972 1484 14 1488 24 July 348 2941 74 17 221 Cultivar F-Mix 29 May 433 3889 3124 441 765 26 June 4316 3925 229 391 1896 24 July 4587 2894 1421 1693 1473 Peanut CRSP Project Florida, Ghana 1 Soil water balance calibrated from measured soil water data

Yield Gaps Causes in Ghana Soil Water? Not as much as expected. Had soil water data to test simulated soil water balance. Fertility? Indirect. SLPF of.86 (Ghana) vs.92 (US). Confirmed with P experiments. Management? Simulate effect of good vs. poor stands (a farmer problem). Simulate good sowing dates vs. non-optimum. Foliar Diseases? Indirect, enter leaf defoliation. Confirmed with fungicide trials. The yield gaps suggested the need for experiments to verify yield increase possible with P and fungicide. J. B. Naab & F. K Tsigbey designed split-plot fungicide trials with Folicure and Abound. Started on-farm tests of P and fungicide.

Effect of time of sowing, varieties and fungicide on peanut pod yield. Naab and Tsigbey, two sites, 3 years in Ghana. Nyankpala Wa Treatment 1999 21 21 Time of planting (P) Early sowing: 22 and 6 % more than D2 or D3 Early 2478 2572 2254 367 331 Mid 193 241 1788 29 2953 Late 1431 2197 147 136 2445 SE ** NS ** *** ** Variety (V) Longer cycle cultivar yielded 41% more Chinese 151 1732 141 25 2722 F-mix 2392 348 2223 2339 2899 SE *** *** *** ** * Fungicide Fungicide increased yield 75% - Fungicide 127 1367 1327 1966 253 + Fungicide 2624 3413 236 2378 3117 SE *** *** *** *** ***

Leaf dry weight (kg hā 1 ) 25 15 5 25 15 5 Nyankpala: 1999 Fungicide Chinese 175 2 225 25 275 3 F-mix No Fungicide J. Naab Ghana, Two peanut cult. In on-station test. Growth analysis showed that leaf area remained high for fungicidetreated peanut 175 2 225 25 275 3 Day of the year Peanut CRSP Project Florida, Ghana

Total dry weight (kg hā 1 ) 8 6 4 8 6 4 Nyankpala: 1999 Fungicide Chinese 15 175 2 225 25 275 3 F-mix No Fungicide J. Naab Ghana, Two peanut cult. In on-station test. Growth analysis showed dry matter accumulation continued longer for fungicidetreated peanut 15 175 2 225 25 275 3 Day of the year Peanut CRSP Project Florida, Ghana

Pod dry weight (kg hā 1 ) 5 4 5 4 Nyankpala: 1999 Fungicide Chinese 175 2 225 25 275 3 F-mix No Fungicide 175 2 225 25 275 3 Day of the year J. Naab Ghana, Two peanut cult. In on-station test. Growth analysis showed greater pod yield for fungicide treated peanut Peanut CRSP Project Florida, Ghana

On-farm tests in Ghana to evaluate fungicide & phosphorus application Naab Presented at AGRO21 - ESA Aug 29-Sep 3, 21 No P + P

On-Farm Studies - Ghana (2 villages over 4 years) Foliar diseases and P deficiency are yield-limiting factors for peanut under on-farm conditions. Fungicide application was effective in controlling leafspot and increased pod yield on average by 8% in on-farm trials. P fertilization increased yield about 16-4% under on-farm trials. Effects of fungicide and P fertilizer were additive and combination of both increased yields by 18%, over 4 years: (5 to 14 kg/ha) Presented at AGRO21 - ESA Aug 29-Sep 3, 21

7 Total biomass growth simulated with, and without P fertilizer, both with fungicide treatment. On-farm peanut trial in Ghana. Top Wt, FgPo, 21 Top Wt, FgPg, 21 Obs Top Wt, FgPo, 21 Obs Top Wt, FgPo, 21 6 5 Plus P fertilizer 4 No P fertilizer Soil fertility factor (SLPF) was set for each treatment: control and +P fertilizer, to account for differences due to P fertilizer Presented at AGRO21 - ESA Aug 29-Sep 3, 21 2 4 6 8 1 12 Days after Planting

14 12 Leaf mass simulated with, and without fungicide treatment, both with no P fertilizer. On-farm peanut trial in Ghana. Leaf wt kg/ha, FgPo Leaf wt kg/ha, FoPo Obs Leaf wt kg/ha, FgPo Obs Leaf wt kg/ha, FoPo 8 6 4 2 Presented at AGRO21 - ESA Aug 29-Sep 3, 21 PCLA (% leaf loss accumulative) is computed from decline in leaf mass from a 1-time maximum of fungicide treated plot. PCLA is input to create leaf abscission. 2 4 6 8 1 12 Days after Planting

7 Tops wt kg/ha, FgPo Tops wt kg/ha, FgP6 Tops wt kg/ha, FoPo Obs Top Wt kg/ha, FgPo Obs Top Wt kg/ha, FoPo Obs Top Wt kg/ha, FoPo 6 5 4 Effect of leaf abscission (PCLA input) reduces canopy light interception and assimilation, whereas P fertilizer acts via increased SLPF. 2 4 6 8 1 12 Presented at AGRO21 - ESA Aug 29-Sep 3, 21 Days after Planting

35 Pod wt kg/ha, FgPo Pod wt kg/ha, FgP6 Pod wt kg/ha, FoPo Obs Pod wt kg/ha, FgPo Obs Pod wt kg/ha, FoPo Obs Pod wt kg/ha, FoPo 25 Effect on pod mass production depends on increase in SLPF (from P fertilizer) and loss of LAI (PCLA input). 15 5 2 4 6 8 1 12 Days after Planting Presented at AGRO21 - ESA Aug 29-Sep 3, 21

Can Weather be a Yield Gap? Requires that you define what normal weather should be. This year versus last year? Your site vs. the best? Conduct seasonal analyses of multi-year weather risk related to rainfall deficit/excess or adverse temperature or cloudy weather. Requires that the models be wellparameterized for effects of temperature, soil water, solar radiation, and extreme events (freeze, frost, flood?). Expts! Presented at AGRO21 - ESA Aug 29-Sep 3, 21

Hypothesizing Yield Gap from Rainfall, Genetics, and Management in India Soybean and maize models on Alfisol soil, with 28 years of weather at Patencheru, India. Evaluated response to sowing date, irrigation, and MG (for soybean only) Auto-plant when soil water >7%, where initial soil water set at 5% FC Irrigate when 4% of FC left in top 4 cm. For Maize, initial N at 25 kg/ha, +12 kg/ha Soybean at 25 plants/m2, maize at 6 plants/m2 Presented at AGRO21 - ESA Aug 29-Sep 3, 21

Soybean yield response to sowing date for five MG under rainfed and irrigated conditions, average of 28 weather years at Patancheru, India. Yield gaps from rainfall, sowing date management, and cultivar. 4 MG 6 Yield, kg/ha 35 25 15 MG 7 MG 8 MG 9 MG 1 MG9+IR 5 15 17 19 21 23 25 Sowing Date, Day of Year

Simulated maize yield response to sowing date under rainfed and irrigated conditions, with 12 kg N/ha, averaged over 28 years at Patancheru, India. 9 Yield under irrigation increased with late sowing, when cooler temperature extended grain filling. Yield, kg/ha 8 7 6 5 4 Rainfed Irrigated Irrigation Amt 15 17 19 21 23 25 Sowing Date, Day of Year 5 4 3 2 1 Irrigation Amount, mm Later sowing increased water deficit during grainfilling, increasing irrigation req.

Weather (flood, frost, freeze) and management as Yield Gaps: Box plot of yield vs. sowing date for K2828 soybean, 22 rainfed weather years at Ames, Iowa. Flood in mid- to late June. Evaluating yield under replanting in late June in 28 flood in Iowa. May 1 May 16 June 1 June 16 July 1 July 16 Non-killing frost 1 4 12 18 Freeze prior to mature 4 14

Water-limited climatic potential (?) yield of soybean in Georgia simulated with CROPGRO-Soybean, with water balance on, Calibration showing: 1) yield variations due to weather and 2) yield gap observed for crop reporting district yields. Yield (kg/ha) 4 35 25 15 5 1973 1976 1979 1982 1984 1987 199 1992 1995 Presented at AGRO21 - ESA Aug 29-Sep 3, 21 RMSE fitting = 167 kg/ha Year M S-A S Not Scaled Measured Scaled Yield gap in USA decreases from North to South. Why?

Larger Yield Gaps in Developing Countries: Greater Opportunity!!! Developing countries (low fertilization, poor weed and pest control, poor cultivars) have much larger yield gaps (maybe 8% gap). Actual may be 2% of CPY, leaving room for 2-, 3-, and 4-fold yield increases. Developed countries (high fertilization, good weed & pest control, improved cultivars) have smaller yield gaps. Actual is 5 to 9% of CPY. Less room to improve. How to feed the world? More room for improvement in developing countries. Put resources there. Genetics alone will not do it!!! Presented at AGRO21 - ESA Aug 29-Sep 3, 21