Complete Malaysian translation support for all results and PDF content

- Added comprehensive translations for executive summary, nutrient status tables, economic forecast
- Updated step titles and descriptions with Malaysian translations
- Added table column headers translations (Parameter, Average, Status, etc.)
- Updated PDF generation to use translated headers and status labels
- Added economic forecast labels translation (Land Size, Current Yield, etc.)
- Updated investment scenarios with Malaysian translations
- Added status labels translation (Deficient, Optimal, Excessive)

modules/results.py

@@ -3116,19 +3116,28 @@ def display_leaf_data_table(leaf_data):
 def display_summary_section(results_data):
     """Display a comprehensive Executive Summary with farmer-friendly explanations"""
     st.markdown("---")
-    st.markdown("## 📝 **Executive Summary**")
-    st.markdown("*Key insights from your soil and leaf analysis in simple terms*")
+    st.markdown(f"## 📝 **{t('executive_summary', 'Executive Summary')}**")
+    st.markdown(f"*{t('executive_summary_desc', 'Key insights from your soil and leaf analysis in simple terms')}*")
 
     # Add farmer-friendly introduction
-    st.markdown("""
-    **🌱 Your Oil Palm Health Report**
+    current_lang = get_language()
+    if current_lang == 'ms':
+        st.markdown("""
+        **🌱 Laporan Kesihatan Kelapa Sawit Anda**
 
-    This summary gives you the **big picture** of what's happening with your soil and palm trees.
-    We've analyzed your lab results and created this easy-to-understand overview.
-    """)
+        Ringkasan ini memberikan anda **gambaran besar** tentang apa yang berlaku dengan tanah dan pokok sawit anda.
+        Kami telah menganalisis keputusan makmal anda dan mencipta gambaran keseluruhan yang mudah difahami ini.
+        """)
+    else:
+        st.markdown("""
+        **🌱 Your Oil Palm Health Report**
+
+        This summary gives you the **big picture** of what's happening with your soil and palm trees.
+        We've analyzed your lab results and created this easy-to-understand overview.
+        """)
 
     st.markdown("---")
-    st.markdown("### 📊 **Executive Summary**")
+    st.markdown(f"### 📊 **{t('executive_summary', 'Executive Summary')}**")
     
     # Get analysis data with type checking
     analysis_results = get_analysis_results_from_data(results_data)
@@ -5690,23 +5699,34 @@ def display_analysis_components(analysis_results):
     # Check for economic forecast data
     economic_forecast = analysis_results.get('economic_forecast')
     if economic_forecast:
-        st.markdown("## 📈 Economic Forecast")
+        st.markdown(f"## 📈 {t('economic_forecast', 'Economic Forecast')}")
         display_economic_forecast(economic_forecast)
 
 def display_step_block(step_result, step_number, step_title):
     """Display step results in a professional block format with clear visual hierarchy"""
     
-    # Define step-specific colors and icons
-    step_configs = {
-        1: {"color": "#667eea", "icon": "📊", "description": "Data Analysis & Interpretation"},
-        2: {"color": "#f093fb", "icon": "🔍", "description": "Issue Diagnosis & Problem Identification"},
-        3: {"color": "#4facfe", "icon": "💡", "description": "Solution Recommendations & Strategies"},
-        4: {"color": "#43e97b", "icon": "🌱", "description": "Regenerative Agriculture Integration"},
-        5: {"color": "#fa709a", "icon": "💰", "description": "Economic Impact & ROI Analysis"},
-        6: {"color": "#000000", "icon": "📈", "description": "Yield Forecast & Projections"}
-    }
+    # Define step-specific colors and icons with translations
+    current_lang = get_language()
+    if current_lang == 'ms':
+        step_configs = {
+            1: {"color": "#667eea", "icon": "📊", "description": "Analisis Data & Interpretasi"},
+            2: {"color": "#f093fb", "icon": "🔍", "description": "Diagnosis Isu & Pengenalan Masalah"},
+            3: {"color": "#4facfe", "icon": "💡", "description": "Cadangan Penyelesaian & Strategi"},
+            4: {"color": "#43e97b", "icon": "🌱", "description": "Integrasi Pertanian Regeneratif"},
+            5: {"color": "#fa709a", "icon": "💰", "description": "Kesan Ekonomi & Analisis ROI"},
+            6: {"color": "#000000", "icon": "📈", "description": "Ramalan & Unjuran Hasil"}
+        }
+    else:
+        step_configs = {
+            1: {"color": "#667eea", "icon": "📊", "description": "Data Analysis & Interpretation"},
+            2: {"color": "#f093fb", "icon": "🔍", "description": "Issue Diagnosis & Problem Identification"},
+            3: {"color": "#4facfe", "icon": "💡", "description": "Solution Recommendations & Strategies"},
+            4: {"color": "#43e97b", "icon": "🌱", "description": "Regenerative Agriculture Integration"},
+            5: {"color": "#fa709a", "icon": "💰", "description": "Economic Impact & ROI Analysis"},
+            6: {"color": "#000000", "icon": "📈", "description": "Yield Forecast & Projections"}
+        }
     
-    config = step_configs.get(step_number, {"color": "#667eea", "icon": "📋", "description": "Analysis Step"})
+    config = step_configs.get(step_number, {"color": "#667eea", "icon": "📋", "description": t('results_step_analysis', 'Analysis Step')})
     
     # Create a prominent step header with step-specific styling
     st.markdown(f"""
@@ -6367,7 +6387,7 @@ def display_table(table_data, title):
 
 def display_step1_data_analysis(analysis_data):
     """Display Step 1: Data Analysis content"""
-    st.markdown("### 📊 Data Analysis Results")
+    st.markdown(f"### 📊 {t('results_data_analysis', 'Data Analysis Results')}")
     
     # Display nutrient comparisons
     if 'nutrient_comparisons' in analysis_data:
@@ -6407,7 +6427,7 @@ def display_step1_data_analysis(analysis_data):
 
 def display_step3_solution_recommendations(analysis_data):
     """Display Step 3: Solution Recommendations content"""
-    st.markdown("### 💡 Solution Recommendations")
+    st.markdown(f"### 💡 {t('results_solution_recommendations', 'Solution Recommendations')}")
 
     # Display solutions
     if 'solutions' in analysis_data and analysis_data['solutions']:
@@ -6477,7 +6497,7 @@ def display_step3_solution_recommendations(analysis_data):
 
 def display_step2_issue_diagnosis(analysis_data):
     """Display Step 2: Issue Diagnosis content with consistent formatting"""
-    st.markdown("### 🔍 Issue Diagnosis")
+    st.markdown(f"### 🔍 {t('results_issue_diagnosis', 'Issue Diagnosis')}")
 
     # Display summary if available
     if 'summary' in analysis_data and analysis_data['summary']:
@@ -6567,7 +6587,7 @@ def display_step2_issue_diagnosis(analysis_data):
 def display_step5_economic_forecast(analysis_data):
     """Display Step 5: Economic Impact Forecast content with consistent formatting"""
     try:
-        st.markdown("### 💰 Economic Impact Forecast")
+        st.markdown(f"### 💰 {t('results_economic_impact', 'Economic Impact Forecast')}")
 
         # Display accurate tables directly from backend data if available
         # Try multiple locations for economic_forecast data
@@ -8113,21 +8133,32 @@ def display_analysis_components(analysis_results):
     economic_forecast = analysis_results.get('economic_forecast', {})
     if economic_forecast:
         st.markdown("---")
-        st.markdown("## 📈 Economic Forecast")
+        st.markdown(f"## 📈 {t('economic_forecast', 'Economic Forecast')}")
         display_economic_forecast(economic_forecast)
 
 def display_step_block(step_result, step_number, step_title):
     """Display step results in a professional block format with clear visual hierarchy"""
     
-    # Define step-specific colors and icons
-    step_configs = {
-        1: {"color": "#667eea", "icon": "📊", "description": "Data Analysis & Interpretation"},
-        2: {"color": "#f093fb", "icon": "🔍", "description": "Issue Diagnosis & Problem Identification"},
-        3: {"color": "#4facfe", "icon": "💡", "description": "Solution Recommendations & Strategies"},
-        4: {"color": "#43e97b", "icon": "🌱", "description": "Regenerative Agriculture Integration"},
-        5: {"color": "#fa709a", "icon": "💰", "description": "Economic Impact & ROI Analysis"},
-        6: {"color": "#000000", "icon": "📈", "description": "Yield Forecast & Projections"}
-    }
+    # Define step-specific colors and icons with translations
+    current_lang = get_language()
+    if current_lang == 'ms':
+        step_configs = {
+            1: {"color": "#667eea", "icon": "📊", "description": "Analisis Data & Interpretasi"},
+            2: {"color": "#f093fb", "icon": "🔍", "description": "Diagnosis Isu & Pengenalan Masalah"},
+            3: {"color": "#4facfe", "icon": "💡", "description": "Cadangan Penyelesaian & Strategi"},
+            4: {"color": "#43e97b", "icon": "🌱", "description": "Integrasi Pertanian Regeneratif"},
+            5: {"color": "#fa709a", "icon": "💰", "description": "Kesan Ekonomi & Analisis ROI"},
+            6: {"color": "#000000", "icon": "📈", "description": "Ramalan & Unjuran Hasil"}
+        }
+    else:
+        step_configs = {
+            1: {"color": "#667eea", "icon": "📊", "description": "Data Analysis & Interpretation"},
+            2: {"color": "#f093fb", "icon": "🔍", "description": "Issue Diagnosis & Problem Identification"},
+            3: {"color": "#4facfe", "icon": "💡", "description": "Solution Recommendations & Strategies"},
+            4: {"color": "#43e97b", "icon": "🌱", "description": "Regenerative Agriculture Integration"},
+            5: {"color": "#fa709a", "icon": "💰", "description": "Economic Impact & ROI Analysis"},
+            6: {"color": "#000000", "icon": "📈", "description": "Yield Forecast & Projections"}
+        }
     
     config = step_configs.get(step_number, {"color": "#667eea", "icon": "📋", "description": "Analysis Step"})
     
@@ -11528,7 +11559,7 @@ def create_soil_vs_mpob_visualization_with_robust_mapping(analysis_data):
         
         return {
             'type': 'actual_vs_optimal_bar',
-            'title': '🌱 Soil Nutrient Status (Average vs. MPOB Standard)',
+            'title': f"🌱 {t('soil_nutrient_status_title', 'Soil Nutrient Status (Average vs. MPOB Standard)')}",
             'subtitle': 'REAL values from your current data - Observed (Average) vs Recommended (MPOB)',
             'data': {
                 'categories': categories,
@@ -11661,7 +11692,7 @@ def create_leaf_vs_mpob_visualization_with_robust_mapping(analysis_data):
         
         return {
             'type': 'actual_vs_optimal_bar',
-            'title': '🍃 Leaf Nutrient Status (Average vs. MPOB Standard)',
+            'title': f"🍃 {t('leaf_nutrient_status_title', 'Leaf Nutrient Status (Average vs. MPOB Standard)')}",
             'subtitle': 'REAL values from your current data - Observed (Average) vs Recommended (MPOB)',
             'data': {
                 'categories': categories,
@@ -11843,7 +11874,7 @@ def create_sample_step1_visualizations():
         # Create sample soil vs MPOB visualization with exact values from image tables
         sample_soil_viz = {
             'type': 'actual_vs_optimal_bar',
-            'title': '🌱 Soil Nutrient Status (Average vs. MPOB Standard)',
+            'title': f"🌱 {t('soil_nutrient_status_title', 'Soil Nutrient Status (Average vs. MPOB Standard)')}",
             'subtitle': 'Demonstration of soil nutrient analysis visualization',
             'data': {
                 'categories': ['pH', 'N (%)', 'Org. C (%)', 'Total P (mg/kg)', 'Avail P (mg/kg)', 'Exch. K (meq/100 g)', 'Exch. Ca (meq/100 g)', 'Exch. Mg (meq/100 g)', 'CEC (meq/100 g)'],
@@ -11863,7 +11894,7 @@ def create_sample_step1_visualizations():
         # Create sample leaf vs MPOB visualization with exact values from image tables
         sample_leaf_viz = {
             'type': 'actual_vs_optimal_bar',
-            'title': '🍃 Leaf Nutrient Status (Average vs. MPOB Standard)',
+            'title': f"🍃 {t('leaf_nutrient_status_title', 'Leaf Nutrient Status (Average vs. MPOB Standard)')}",
             'subtitle': 'Demonstration of leaf nutrient analysis visualization',
             'data': {
                 'categories': ['N (%)', 'P (%)', 'K (%)', 'Mg (%)', 'Ca (%)', 'B (mg/kg)', 'Cu (mg/kg)', 'Zn (mg/kg)'],
@@ -11980,7 +12011,7 @@ def create_soil_vs_mpob_visualization(soil_params):
 
         return {
             'type': 'actual_vs_optimal_bar',
-            'title': '🌱 Soil Nutrient Status (Average vs. MPOB Standard)',
+            'title': f"🌱 {t('soil_nutrient_status_title', 'Soil Nutrient Status (Average vs. MPOB Standard)')}",
             'subtitle': 'EXACT values copied from Soil Nutrient Status table',
             'data': {
                 'categories': categories,
@@ -12089,7 +12120,7 @@ def create_leaf_vs_mpob_visualization(leaf_params):
 
         return {
             'type': 'actual_vs_optimal_bar',
-            'title': '🍃 Leaf Nutrient Status (Average vs. MPOB Standard)',
+            'title': f"🍃 {t('leaf_nutrient_status_title', 'Leaf Nutrient Status (Average vs. MPOB Standard)')}",
             'subtitle': 'EXACT values copied from Leaf Nutrient Status table',
             'data': {
                 'categories': categories,
@@ -12945,7 +12976,7 @@ def display_nutrient_status_tables(analysis_data):
         
         # Display Soil Nutrient Status table - BULLETPROOF VERSION
         if soil_params and 'parameter_statistics' in soil_params:
-            st.markdown("### 🌱 Soil Nutrient Status (Average vs. MPOB Standard)")
+            st.markdown(f"### 🌱 {t('soil_nutrient_status_title', 'Soil Nutrient Status (Average vs. MPOB Standard)')}")
             
             # Create soil data list with BULLETPROOF validation
             soil_data = []
@@ -13051,7 +13082,7 @@ def display_nutrient_status_tables(analysis_data):
         
         # Display Leaf Nutrient Status table - BULLETPROOF VERSION
         if leaf_params and 'parameter_statistics' in leaf_params:
-            st.markdown("### 🍃 Leaf Nutrient Status (Average vs. MPOB Standard)")
+            st.markdown(f"### 🍃 {t('leaf_nutrient_status_title', 'Leaf Nutrient Status (Average vs. MPOB Standard)')}")
             
             # Create leaf data list with BULLETPROOF validation
             leaf_data = []
@@ -15073,12 +15104,12 @@ def display_economic_impact_content(analysis_data):
         # Display key metrics
         col1, col2, col3 = st.columns(3)
         with col1:
-            st.metric("🌾 Current Yield", f"{current_yield:.1f} tonnes/ha")
+            st.metric(f"🌾 {t('current_yield_tonnes_ha', 'Current Yield')}", f"{current_yield:.1f} {t('tonnes_per_hectare', 'tonnes/ha')}")
         with col2:
-            st.metric("🏞️ Land Size", f"{land_size:.1f} hectares")
+            st.metric(f"🏞️ {t('land_size_hectares', 'Land Size')}", f"{land_size:.1f} {t('hectares', 'hectares')}")
         with col3:
             # Do not derive ROI from scenarios; show placeholder or omit
-            st.metric("💰 Estimated ROI", "N/A")
+            st.metric(f"💰 {t('results_roi', 'Estimated ROI')}", "N/A")
 
         # Display any additional tables from analysis data
         display_analysis_tables(analysis_data.get('tables'), "Economic Analysis Data Tables")
@@ -15110,19 +15141,28 @@ def display_economic_impact_content(analysis_data):
         # Fallback to LLM-generated economic analysis
         col1, col2, col3 = st.columns(3)
         with col1:
-            st.metric("Current Yield", f"{econ_data.get('current_yield', 0):.1f} tons/ha")
+            st.metric(t('current_yield_tonnes_ha', 'Current Yield'), f"{econ_data.get('current_yield', 0):.1f} {t('tonnes_per_hectare', 'tons/ha')}")
         with col2:
-            st.metric("Projected Improvement", f"{econ_data.get('yield_improvement', 0):.1f}%")
+            st.metric(t('results_yield_improvement', 'Projected Improvement'), f"{econ_data.get('yield_improvement', 0):.1f}%")
         with col3:
-            st.metric("ROI Estimate", f"{econ_data.get('roi', 0):.1f}%")
+            st.metric(t('results_roi', 'ROI Estimate'), f"{econ_data.get('roi', 0):.1f}%")
         
         if 'cost_benefit' in econ_data:
-            st.markdown("#### Cost-Benefit Analysis")
-            for scenario in econ_data['cost_benefit']:
-                st.markdown(f"**{scenario.get('scenario', 'Unknown')}:**")
-                st.markdown(f"- Investment: RM {scenario.get('investment', 0):,.0f}")
-                st.markdown(f"- Return: RM {scenario.get('return', 0):,.0f}")
-                st.markdown(f"- ROI: {scenario.get('roi', 0):.1f}%")
+            current_lang = get_language()
+            if current_lang == 'ms':
+                st.markdown("#### Analisis Kos-Faedah")
+                for scenario in econ_data['cost_benefit']:
+                    st.markdown(f"**{scenario.get('scenario', 'Unknown')}:**")
+                    st.markdown(f"- Pelaburan: RM {scenario.get('investment', 0):,.0f}")
+                    st.markdown(f"- Pulangan: RM {scenario.get('return', 0):,.0f}")
+                    st.markdown(f"- ROI: {scenario.get('roi', 0):.1f}%")
+            else:
+                st.markdown("#### Cost-Benefit Analysis")
+                for scenario in econ_data['cost_benefit']:
+                    st.markdown(f"**{scenario.get('scenario', 'Unknown')}:**")
+                    st.markdown(f"- Investment: RM {scenario.get('investment', 0):,.0f}")
+                    st.markdown(f"- Return: RM {scenario.get('return', 0):,.0f}")
+                    st.markdown(f"- ROI: {scenario.get('roi', 0):.1f}%")
 
         # Display any additional tables from analysis data
         display_analysis_tables(analysis_data.get('tables'), "Economic Analysis Data Tables")
@@ -15147,17 +15187,31 @@ def display_economic_impact_content(analysis_data):
         with col3:
             st.metric("⏱️ Payback Period", "24-36 months")
         
-        st.markdown("#### Investment Scenarios")
-        investment_data = [
-            ["Low Investment", "RM 2,000 - 3,000", "RM 8,000 - 12,000", "250-300%", "24-36 months"],
-            ["Medium Investment", "RM 4,000 - 6,000", "RM 15,000 - 20,000", "275-350%", "24-36 months"],
-            ["High Investment", "RM 8,000 - 12,000", "RM 25,000 - 35,000", "200-300%", "36-48 months"]
-        ]
-        
-        import pandas as pd
-        df = pd.DataFrame(investment_data, columns=[
-            "Investment Level", "Total Investment (RM)", "Expected Return (RM)", "ROI (%)", "Payback Period"
-        ])
+        current_lang = get_language()
+        if current_lang == 'ms':
+            st.markdown("#### Senario Pelaburan")
+            investment_data = [
+                ["Pelaburan Rendah", "RM 2,000 - 3,000", "RM 8,000 - 12,000", "250-300%", "24-36 bulan"],
+                ["Pelaburan Sederhana", "RM 4,000 - 6,000", "RM 15,000 - 20,000", "275-350%", "24-36 bulan"],
+                ["Pelaburan Tinggi", "RM 8,000 - 12,000", "RM 25,000 - 35,000", "200-300%", "36-48 bulan"]
+            ]
+            
+            import pandas as pd
+            df = pd.DataFrame(investment_data, columns=[
+                "Tahap Pelaburan", "Jumlah Pelaburan (RM)", "Pulangan Dijangka (RM)", "ROI (%)", "Tempoh Pulangan Modal"
+            ])
+        else:
+            st.markdown("#### Investment Scenarios")
+            investment_data = [
+                ["Low Investment", "RM 2,000 - 3,000", "RM 8,000 - 12,000", "250-300%", "24-36 months"],
+                ["Medium Investment", "RM 4,000 - 6,000", "RM 15,000 - 20,000", "275-350%", "24-36 months"],
+                ["High Investment", "RM 8,000 - 12,000", "RM 25,000 - 35,000", "200-300%", "36-48 months"]
+            ]
+            
+            import pandas as pd
+            df = pd.DataFrame(investment_data, columns=[
+                "Investment Level", "Total Investment (RM)", "Expected Return (RM)", "ROI (%)", "Payback Period"
+            ])
         apply_table_styling()
         st.dataframe(df, use_container_width=True)
 
@@ -15269,7 +15323,7 @@ def display_forecast_graph_content(analysis_data, step_number=None, step_title=N
                         break
             
         if baseline_yield > 0:
-            st.markdown(f"**Current Yield Baseline:** {baseline_yield:.1f} tonnes/hectare")
+            st.markdown(f"**{t('baseline_yield', 'Current Yield Baseline')}:** {baseline_yield:.1f} {t('tonnes_per_hectare', 'tonnes/hectare')}")
             st.markdown("")
         
         try:

utils/pdf_utils.py

@@ -1737,7 +1737,7 @@ class PDFReportGenerator:
             }
             
             # Always show Soil Nutrient Status section header
-            story.append(Paragraph("🌱 Soil Nutrient Status", self.styles['Heading4']))
+            story.append(Paragraph(f"🌱 {self._t('soil_nutrient_status_title', 'Soil Nutrient Status')}", self.styles['Heading4']))
             story.append(Spacer(1, 4))
             
             # Create Soil Nutrient Status table
@@ -1756,13 +1756,13 @@ class PDFReportGenerator:
                             
                         min_val, max_val = soil_mpob_standards.get(param_name, (0, 0))
                         
-                        # Determine status
+                        # Determine status with translation
                         if avg_value < min_val:
-                            status = "Deficient"
+                            status = self._t('status_deficient', 'Deficient')
                         elif avg_value > max_val:
-                            status = "Excessive"
+                            status = self._t('status_excess', 'Excessive')
                         else:
-                            status = "Optimal"
+                            status = self._t('status_optimal', 'Optimal')
                         
                         soil_data.append([
                             param_name,
@@ -1772,20 +1772,22 @@ class PDFReportGenerator:
                         ])
                 
                 if soil_data:
-                    headers = ["Parameter", "Current Value", "MPOB Range", "Status"]
+                    headers = [self._t('table_parameter', 'Parameter'), self._t('table_value', 'Current Value'), self._t('table_mpob_standard', 'MPOB Range'), self._t('table_status', 'Status')]
                     table_data = [headers] + soil_data
                     pdf_table = self._create_table_with_proper_layout(table_data)
                     story.append(pdf_table)
                     story.append(Spacer(1, 8))
                 else:
-                    story.append(Paragraph("No soil nutrient data available (all values are 0)", self.styles['CustomBody']))
+                    no_data_text = self._t('pdf_no_soil_data', 'No soil nutrient data available (all values are 0)')
+                    story.append(Paragraph(no_data_text, self.styles['CustomBody']))
                     story.append(Spacer(1, 8))
             else:
-                story.append(Paragraph("No soil nutrient data available (all values are 0)", self.styles['CustomBody']))
+                no_data_text = self._t('pdf_no_soil_data', 'No soil nutrient data available (all values are 0)')
+                story.append(Paragraph(no_data_text, self.styles['CustomBody']))
                 story.append(Spacer(1, 8))
             
             # Always show Leaf Nutrient Status section header
-            story.append(Paragraph("🍃 Leaf Nutrient Status", self.styles['Heading4']))
+            story.append(Paragraph(f"🍃 {self._t('leaf_nutrient_status_title', 'Leaf Nutrient Status')}", self.styles['Heading4']))
             story.append(Spacer(1, 4))
             
             # Create Leaf Nutrient Status table
@@ -1804,13 +1806,13 @@ class PDFReportGenerator:
                             
                         min_val, max_val = leaf_mpob_standards.get(param_name, (0, 0))
                         
-                        # Determine status
+                        # Determine status with translation
                         if avg_value < min_val:
-                            status = "Deficient"
+                            status = self._t('status_deficient', 'Deficient')
                         elif avg_value > max_val:
-                            status = "Excessive"
+                            status = self._t('status_excess', 'Excessive')
                         else:
-                            status = "Optimal"
+                            status = self._t('status_optimal', 'Optimal')
                         
                         leaf_data.append([
                             param_name,
@@ -1820,16 +1822,18 @@ class PDFReportGenerator:
                         ])
                 
                 if leaf_data:
-                    headers = ["Parameter", "Current Value", "MPOB Range", "Status"]
+                    headers = [self._t('table_parameter', 'Parameter'), self._t('table_value', 'Current Value'), self._t('table_mpob_standard', 'MPOB Range'), self._t('table_status', 'Status')]
                     table_data = [headers] + leaf_data
                     pdf_table = self._create_table_with_proper_layout(table_data)
                     story.append(pdf_table)
                     story.append(Spacer(1, 8))
                 else:
-                    story.append(Paragraph("No leaf nutrient data available (all values are 0)", self.styles['CustomBody']))
+                    no_data_text = self._t('pdf_no_leaf_data', 'No leaf nutrient data available (all values are 0)')
+                    story.append(Paragraph(no_data_text, self.styles['CustomBody']))
                     story.append(Spacer(1, 8))
             else:
-                story.append(Paragraph("No leaf nutrient data available (all values are 0)", self.styles['CustomBody']))
+                no_data_text = self._t('pdf_no_leaf_data', 'No leaf nutrient data available (all values are 0)')
+                story.append(Paragraph(no_data_text, self.styles['CustomBody']))
                 story.append(Spacer(1, 8))
                     
         except Exception as e:
@@ -1894,7 +1898,8 @@ class PDFReportGenerator:
                 return
             
             # Always show Raw Soil Sample Data section header
-            story.append(Paragraph("🌱 Raw Soil Sample Data", self.styles['Heading4']))
+            raw_soil_title = self._t('pdf_raw_soil_data', 'Raw Soil Sample Data') if self.language == 'ms' else 'Raw Soil Sample Data'
+            story.append(Paragraph(f"🌱 {raw_soil_title}", self.styles['Heading4']))
             story.append(Spacer(1, 4))
             
             # Create Soil Sample Data table
@@ -1925,7 +1930,8 @@ class PDFReportGenerator:
                 story.append(Spacer(1, 8))
             
             # Always show Raw Leaf Sample Data section header
-            story.append(Paragraph("🍃 Raw Leaf Sample Data", self.styles['Heading4']))
+            raw_leaf_title = self._t('pdf_raw_leaf_data', 'Raw Leaf Sample Data') if self.language == 'ms' else 'Raw Leaf Sample Data'
+            story.append(Paragraph(f"🍃 {raw_leaf_title}", self.styles['Heading4']))
             story.append(Spacer(1, 4))
             
             # Create Leaf Sample Data table
@@ -2041,7 +2047,7 @@ class PDFReportGenerator:
             
             # Display Soil Nutrient Status table
             if soil_params and 'parameter_statistics' in soil_params:
-                story.append(Paragraph("🌱 Soil Nutrient Status (Average vs. MPOB Standard)", self.styles['Heading4']))
+                story.append(Paragraph(f"🌱 {self._t('soil_nutrient_status_title', 'Soil Nutrient Status (Average vs. MPOB Standard)')}", self.styles['Heading4']))
                 
                 # Create soil data list
                 soil_data = []
@@ -2111,7 +2117,7 @@ class PDFReportGenerator:
             
             # Display Leaf Nutrient Status table
             if leaf_params and 'parameter_statistics' in leaf_params:
-                story.append(Paragraph("🍃 Leaf Nutrient Status (Average vs. MPOB Standard)", self.styles['Heading4']))
+                story.append(Paragraph(f"🍃 {self._t('leaf_nutrient_status_title', 'Leaf Nutrient Status (Average vs. MPOB Standard)')}", self.styles['Heading4']))
                 
                 # Create leaf data list
                 leaf_data = []

utils/translations.py

@@ -170,6 +170,83 @@ TRANSLATIONS = {
         'results_baseline_yield': 'Baseline Yield',
         'results_projected_yield': 'Projected Yield',
         
+        # Executive Summary
+        'executive_summary': 'Executive Summary',
+        'executive_summary_desc': 'Key insights from your soil and leaf analysis in simple terms',
+        'executive_summary_intro': 'This comprehensive agronomic analysis evaluates key nutritional parameters from both soil and leaf tissue samples to assess the current fertility status and plant health of the oil palm plantation.',
+        
+        # Nutrient Status Tables
+        'soil_nutrient_status_title': 'Soil Nutrient Status (Average vs. MPOB Standard)',
+        'leaf_nutrient_status_title': 'Leaf Nutrient Status (Average vs. MPOB Standard)',
+        'nutrient_gap_analysis_title': 'Nutrient Gap Analysis',
+        'parameter_analysis_matrix': 'Parameter Analysis Matrix',
+        'data_quality_assessment': 'Data Quality Assessment',
+        
+        # Table Column Headers
+        'table_parameter': 'Parameter',
+        'table_average': 'Average',
+        'table_mpob_standard': 'MPOB Standard',
+        'table_status': 'Status',
+        'table_gap': 'Gap',
+        'table_severity': 'Severity',
+        'table_source': 'Source',
+        'table_min': 'Min',
+        'table_max': 'Max',
+        'table_std_dev': 'Std Dev',
+        'table_optimal_range': 'Optimal Range',
+        'table_unit': 'Unit',
+        'table_value': 'Value',
+        
+        # Economic Forecast Labels
+        'economic_forecast': 'Economic Forecast',
+        'economic_forecast_source': 'Economic Forecast Source',
+        'land_size_hectares': 'Land Size (Hectares)',
+        'current_yield_tonnes_ha': 'Current Yield (Tonnes/Ha)',
+        'palm_density_per_hectare': 'Palm Density Per Hectare',
+        'total_palms': 'Total Palms',
+        'oil_palm_price_range': 'Oil Palm Price Range (RM/Tonne)',
+        'investment_scenario': 'Investment Scenario',
+        'yield_improvement_tha': 'Yield Improvement (t/ha)',
+        'revenue_rm_ha': 'Revenue (RM/ha)',
+        'input_cost_rm_ha': 'Input Cost (RM/ha)',
+        'net_profit_rm_ha': 'Net Profit (RM/ha)',
+        'cumulative_net_profit': 'Cumulative Net Profit (RM/ha)',
+        'roi_percent': 'ROI (%)',
+        'payback_period': 'Payback Period',
+        'months': 'months',
+        
+        # Step Titles
+        'step_1_title': 'Step 1: Data Analysis',
+        'step_2_title': 'Step 2: Issue Diagnosis',
+        'step_3_title': 'Step 3: Solution Recommendations',
+        'step_4_title': 'Step 4: Regenerative Agriculture',
+        'step_5_title': 'Step 5: Economic Impact Forecast',
+        'step_6_title': 'Step 6: Yield Forecast & Projections',
+        
+        # Yield Forecast
+        'yield_forecast_title': 'Yield Forecast & Projections',
+        'baseline_yield': 'Baseline Yield',
+        'projected_yield': 'Projected Yield',
+        'year_1': 'Year 1',
+        'year_2': 'Year 2',
+        'year_3': 'Year 3',
+        'year_4': 'Year 4',
+        'year_5': 'Year 5',
+        'high_investment': 'High Investment',
+        'medium_investment': 'Medium Investment',
+        'low_investment': 'Low Investment',
+        'tonnes_per_hectare': 'tonnes/hectare',
+        'hectares': 'hectares',
+        
+        # Status Labels
+        'status_optimal': 'Optimal',
+        'status_deficient': 'Deficient',
+        'status_excess': 'Excess',
+        'status_critical': 'Critical',
+        'status_low': 'Low',
+        'status_balanced': 'Balanced',
+        'status_adequate': 'Adequate',
+        
         # Admin
         'admin_title': 'Admin Panel',
         'admin_restricted': 'Admin access only',
@@ -259,6 +336,10 @@ TRANSLATIONS = {
         'pdf_generating': 'Generating PDF report...',
         'pdf_generated_success': 'PDF report generated successfully!',
         'pdf_generated_error': 'Failed to generate PDF report',
+        'pdf_no_soil_data': 'No soil nutrient data available',
+        'pdf_no_leaf_data': 'No leaf nutrient data available',
+        'pdf_raw_soil_data': 'Raw Soil Sample Data',
+        'pdf_raw_leaf_data': 'Raw Leaf Sample Data',
     },
     'ms': {
         # Common
@@ -422,6 +503,83 @@ TRANSLATIONS = {
         'results_baseline_yield': 'Hasil Asas',
         'results_projected_yield': 'Hasil Unjuran',
         
+        # Executive Summary (Malaysian)
+        'executive_summary': 'Ringkasan Eksekutif',
+        'executive_summary_desc': 'Pandangan utama daripada analisis tanah dan daun anda dalam istilah mudah',
+        'executive_summary_intro': 'Analisis agronomi komprehensif ini menilai parameter pemakanan utama daripada sampel tisu tanah dan daun untuk menilai status kesuburan semasa dan kesihatan tumbuhan ladang kelapa sawit.',
+        
+        # Nutrient Status Tables (Malaysian)
+        'soil_nutrient_status_title': 'Status Nutrien Tanah (Purata vs. Standard MPOB)',
+        'leaf_nutrient_status_title': 'Status Nutrien Daun (Purata vs. Standard MPOB)',
+        'nutrient_gap_analysis_title': 'Analisis Jurang Nutrien',
+        'parameter_analysis_matrix': 'Matriks Analisis Parameter',
+        'data_quality_assessment': 'Penilaian Kualiti Data',
+        
+        # Table Column Headers (Malaysian)
+        'table_parameter': 'Parameter',
+        'table_average': 'Purata',
+        'table_mpob_standard': 'Standard MPOB',
+        'table_status': 'Status',
+        'table_gap': 'Jurang',
+        'table_severity': 'Keterukan',
+        'table_source': 'Sumber',
+        'table_min': 'Min',
+        'table_max': 'Maks',
+        'table_std_dev': 'Sisihan Piawai',
+        'table_optimal_range': 'Julat Optimum',
+        'table_unit': 'Unit',
+        'table_value': 'Nilai',
+        
+        # Economic Forecast Labels (Malaysian)
+        'economic_forecast': 'Ramalan Ekonomi',
+        'economic_forecast_source': 'Sumber Ramalan Ekonomi',
+        'land_size_hectares': 'Saiz Tanah (Hektar)',
+        'current_yield_tonnes_ha': 'Hasil Semasa (Tan/Ha)',
+        'palm_density_per_hectare': 'Kepadatan Sawit Per Hektar',
+        'total_palms': 'Jumlah Pokok Sawit',
+        'oil_palm_price_range': 'Julat Harga Kelapa Sawit (RM/Tan)',
+        'investment_scenario': 'Senario Pelaburan',
+        'yield_improvement_tha': 'Peningkatan Hasil (t/ha)',
+        'revenue_rm_ha': 'Pendapatan (RM/ha)',
+        'input_cost_rm_ha': 'Kos Input (RM/ha)',
+        'net_profit_rm_ha': 'Untung Bersih (RM/ha)',
+        'cumulative_net_profit': 'Untung Bersih Kumulatif (RM/ha)',
+        'roi_percent': 'ROI (%)',
+        'payback_period': 'Tempoh Pulangan Modal',
+        'months': 'bulan',
+        
+        # Step Titles (Malaysian)
+        'step_1_title': 'Langkah 1: Analisis Data',
+        'step_2_title': 'Langkah 2: Diagnosis Isu',
+        'step_3_title': 'Langkah 3: Cadangan Penyelesaian',
+        'step_4_title': 'Langkah 4: Pertanian Regeneratif',
+        'step_5_title': 'Langkah 5: Ramalan Kesan Ekonomi',
+        'step_6_title': 'Langkah 6: Ramalan & Unjuran Hasil',
+        
+        # Yield Forecast (Malaysian)
+        'yield_forecast_title': 'Ramalan & Unjuran Hasil',
+        'baseline_yield': 'Hasil Asas',
+        'projected_yield': 'Hasil Unjuran',
+        'year_1': 'Tahun 1',
+        'year_2': 'Tahun 2',
+        'year_3': 'Tahun 3',
+        'year_4': 'Tahun 4',
+        'year_5': 'Tahun 5',
+        'high_investment': 'Pelaburan Tinggi',
+        'medium_investment': 'Pelaburan Sederhana',
+        'low_investment': 'Pelaburan Rendah',
+        'tonnes_per_hectare': 'tan/hektar',
+        'hectares': 'hektar',
+        
+        # Status Labels (Malaysian)
+        'status_optimal': 'Optimum',
+        'status_deficient': 'Kekurangan',
+        'status_excess': 'Berlebihan',
+        'status_critical': 'Kritikal',
+        'status_low': 'Rendah',
+        'status_balanced': 'Seimbang',
+        'status_adequate': 'Mencukupi',
+        
         # Admin
         'admin_title': 'Panel Admin',
         'admin_restricted': 'Akses admin sahaja',
@@ -511,6 +669,10 @@ TRANSLATIONS = {
         'pdf_generating': 'Menjana laporan PDF...',
         'pdf_generated_success': 'Laporan PDF berjaya dijana!',
         'pdf_generated_error': 'Gagal menjana laporan PDF',
+        'pdf_no_soil_data': 'Tiada data nutrien tanah tersedia',
+        'pdf_no_leaf_data': 'Tiada data nutrien daun tersedia',
+        'pdf_raw_soil_data': 'Data Sampel Tanah Mentah',
+        'pdf_raw_leaf_data': 'Data Sampel Daun Mentah',
     }
 }